Summary: ClickSquared is marketing services agency that, unlike most of its peers, has built its own marketing automation system. The main advantage is tight integration of database build, campaign management and message delivery. The vendor has just officially launched its system, which should meet the needs of most mid-tier consumer marketers.
In a post last week, I casually described ClickSquared as a vendor delivering multi-channel messages for external campaign management systems. This was not wholly accurate. Although integrated multi-channel delivery is indeed a key differentiator for ClickSquared, the firm also offers its own campaign management system, called “Click 3G”. In fact, Click 3G was officially launched last week, although the company has been migrating clients to the platform since Fall 2008.
The more important clarification is that ClickSquared is a marketing services agency, offering database management, campaign development, creative, execution and analysis. The company got its start in 1999 as a direct mail house specializing in overnight execution of trigger marketing programs. Since then it has added email and other services through acquisitions and internal expansion. It now offers a relationships relationships ranging from full-service to self-service, with a particular focus on full-service solutions for mid-tier businesses and on special programs for very large enterprises. It sends emails for about 85% of its 150 clients and maintains marketing databases for about half of them.
In other words, ClickSquared competes with firms like Epsilon, Merkle and Acxiom for enterprise clients, and with a host of smaller firms for mid-tier clients. It also competes to some degree with email providers like Responsys, ExactTarget and InfoGroup YesMail, which are themselves expanding into other channels. (Apologies to all for over-simplification. Properly identifying the overlapping spheres of industry competitors would take a post of its own.)
One feature that stands out about ClickSquared is its choice to build its own campaign management system. This contrasts with the vast majority of marketing services agencies, which rely on industry-standard products such as Unica and Alterian. The fundamental argument for using industry-standard software is that continuously updating a home-grown system costs too much for most marketing services vendors, who can’t spread the expense across as many clients as a dedicated software company. Nor is software development a core competency of many marketing services agencies. Ultimately, this line of reasoning concludes, marketing services agencies compete on database management, analytics, marketing strategy and client service, so software is a poor investment for their necessarily limited resources.
To put matters in historical perspective, most big marketing services agencies did create their own campaign management systems when the category first developed in the 1990’s. But once satisfactory third-party products became widely available, the big firms largely dropped their in-house products. So it’s intriguing that ClickSquared (and a few other firms including Entiera , which I reviewed last July) have again chosen to build their own.
It’s much too soon to consider this a trend, but perhaps the cost/value relationship has shifted back in favor of in-house systems. The logic would be something like this: the prices of commercial systems haven't change, while the cost of building in-house systems has fallen because the requirements are well understood and developers can take advantage of third-party components and agile development methods. Thus, in-house development is relatively more attractive.
But in talking with ClickSquared (and Entiera, for that matter), I hear slightly a different story. It’s true that they avoid hefty license fees by using their own software. But main savings seems to come from integrating several capabilities, including customer data integration, message delivery and reporting, in addition to campaign management itself. This reduces both the total software cost and the labor needed to combine the separate systems. For example, ClickSquared says it can deliver a new marketing database in one to three months, compared with six months or more using third party systems.
Of course, an in-house system must still meet business needs for the savings to be worthwhile. Part of the reason that ClickSquared targets Click 3G at mid-tier companies is that their needs are somewhat less complex than enterprise marketers. That said, the system offers a respectable set of capabilities.
- Customer data can be loaded via API posts or self-service file uploads. The system provides automated data cleansing and customer matching capabilities. It can also gather data with an advanced email survey tool that supports for dynamic questions (i.e., questions change based on previous responses) and complex question types such as rankings and allocations. Marketing content can be uploaded and edited within the system and then shared across campaigns.
- Analytics are largely handled outside the system. These is no built-in predictive modeling, although scores can be imported and used as variables into segment definitions and business rules. The system does provide its own Web analytics module, or it can import data from Omniture or Coremetrics. ClickSquared captures online response using standard link tracking and can generate heat map reports showing how often different links were clicked within an email or Web form. Users can execute custom attribution rules during their database build.
- Campaigns are based on business rules. These can be executed in batch or triggered by events posted to the system API in real time. The rules can consider file segmentation, offer selection, channel preferences and limits on contact frequency when selecting messages. Click 3G also supports “distributed marketing” campaigns that allow users such as branch offices to execute predefined programs by setting a limited number of parameters. Campaign outputs can include dynamically-customized content for direct mail, email, and mobile (SMS) messages, as well as messages sent to CRM systems via an API.
- Message delivery for email is handled directly by ClickSquared, which helps to manage ISP relationships, ensures compliance with anti-spam regulations, and can spread large blasts over time. The system provides similar services for wireless (SMS) messages, although (like most marketing service vendors) it works with a third party to integrate with carriers. For direct mail, ClickSquared can handle preprocessing such as NCOA and then deliver a file of printer-ready personalized PDFs. Although campaign manager-to-email integration is more common today than when ClickSquared began, its multi-channel integration is still an advantage.
- The system also provides several “Web 2.0” options. Most notable is “clickShare”, which lets users register and then upload, share and comment on materials in an online forum. Other applications support referrals, mapping mash-ups and product ratings. Activities in these applications are fed into the marketing database, where they can be used for segmentation and triggers.
Click 3G lacks some refinements of the main commercial campaign management products, such as embedded predictive modeling and detailed project management. The vendor argues that its mid-tier clients don’t necessarily need such features, or at least need them less than tightly integrated database building and message delivery. Click 3G’s largest installations are currently in 15 to 20 million customer range, firmly within mid-tier territory.
Pricing for ClickSquared is based on the combination of professional and technical services used by each client. For Click 3G, factors include database size, channels used, message volume and system modules. A self-service client with 50,000 customers and 100,000 emails per month would pay $1,500 per month for the system. A client with two million customers and a proportionate mix of email, direct mail, text messages, surveys and social content would pay $15,000 per month. Clients commit to a contract of one year or longer.
Monday, March 22, 2010
Friday, March 19, 2010
Real Examples of Social Media ROI
Summary: some published examples of "hard" ROI from social media.
As part of the preparation for next Tuesday’s Webinar with 1to1 Media and Neolane (register here), I poked around for some concrete examples of ROI from social media. Here’s what I found.
Socialnomics blog by Erik Qualman offers a dynamic video with 33 “salient examples and data points” about social media ROI. Some are pretty vague but the concrete ones include:
- Wine TV Library gained 1,800 new customers from Twitter
- Lenovo attributed a 20% reduction in call center activity to use of a community website for answers
- Burger King received 32 million media impressions from a Facebook app promotion costing less than $50,000
- Genius.com reports that 24% of its social media leads convert to sales opportunities
- Moonfruit sales of its Web hosting service increased 20% on a $15,000 social media investment
Jacob Morgan cites a Computerworld article describing how online community platform vendor Reality Digital generated 72 leads over the first three months of its social media project, at a cost of roughly $9,000. The company expected this to yield at least one sale which would cover the entire annual cost of the program.
ReadWriteWeb reports “a Cisco study in 2004 found that 43% of visits to online support forum are in lieu of opening up a support case through standard methods.”
Socialtext corporate blog cites an estimate by TransUnion CTO John Parkinson that his $50,000 investment in Socialtext has avoided $2.5 million in tech spending by helping users share ideas on how to solve their problems more cheaply.
10e20 corporate blog gives three examples of social media conversion:
- response to a LinkedIn group query became a 10e20 client
- a "couple of hours per week" spent social bookmarking the contents of an online magazine at StumbleUpon and other sites drove “10’s of thousands of visitors as opposed to hundreds”, resulting in much higher ad pay-per-click ad revenue
- major national fashion brand invested the equivalent of "one mid-level employee’s salary" to run a dedicated social media presence, yielding 75,000 fans and followers and “several hundred thousand dollars in new sales in three months of marketing” as well as reaching a new audience, improving public relations and customer service, and gaining feedback for product development
HubSpot's The State of Inbound Marketing 2010 survey found that 41% to 46% of the companies using Twitter, LinkedIn, Facebook or a company blog had acquired a customer from that channel.
Predictive Marketing Blog by Bob Hodgson reported that eight Tweets by a high tech conference with 350 followers generated 10 completed registrations worth $15,000.
I also found plenty of insightful content that doesn’t include specific numbers. In general, there are two schools of thought on social media ROI: some think it really must be tied to revenue and profits to be meaningful; others argue just as passionately that different measures are appropriate depending on the program objective.
Truth be told, my heart is with the “revenue and profits” school. But I suspect it may be too simplistic, so I do accept alternative measures as a valid alternative. The problem with tying social media to "hard" ROI is this often relies on complex intermediate calculations, which are subjective in themselves. That being the case, alternative measures are not necessarily less valid; it depends on the details. (Fallacy alert: just because neither is perfect, it doesn’t follow that both are equally bad).
In any case, here are a few discussions I found particularly worthwhile:
A SlideShare presentation from Peashoot (a social media campaign manager) listing different metrics for different campaigns. These are good examples even though there are no actual results.
An eConsultancy blog post sharing comments on social media ROI from a collection of British experts.
Another eConsultancy post listing ten specific ways to measure social media success.
As part of the preparation for next Tuesday’s Webinar with 1to1 Media and Neolane (register here), I poked around for some concrete examples of ROI from social media. Here’s what I found.
Socialnomics blog by Erik Qualman offers a dynamic video with 33 “salient examples and data points” about social media ROI. Some are pretty vague but the concrete ones include:
- Wine TV Library gained 1,800 new customers from Twitter
- Lenovo attributed a 20% reduction in call center activity to use of a community website for answers
- Burger King received 32 million media impressions from a Facebook app promotion costing less than $50,000
- Genius.com reports that 24% of its social media leads convert to sales opportunities
- Moonfruit sales of its Web hosting service increased 20% on a $15,000 social media investment
Jacob Morgan cites a Computerworld article describing how online community platform vendor Reality Digital generated 72 leads over the first three months of its social media project, at a cost of roughly $9,000. The company expected this to yield at least one sale which would cover the entire annual cost of the program.
ReadWriteWeb reports “a Cisco study in 2004 found that 43% of visits to online support forum are in lieu of opening up a support case through standard methods.”
Socialtext corporate blog cites an estimate by TransUnion CTO John Parkinson that his $50,000 investment in Socialtext has avoided $2.5 million in tech spending by helping users share ideas on how to solve their problems more cheaply.
10e20 corporate blog gives three examples of social media conversion:
- response to a LinkedIn group query became a 10e20 client
- a "couple of hours per week" spent social bookmarking the contents of an online magazine at StumbleUpon and other sites drove “10’s of thousands of visitors as opposed to hundreds”, resulting in much higher ad pay-per-click ad revenue
- major national fashion brand invested the equivalent of "one mid-level employee’s salary" to run a dedicated social media presence, yielding 75,000 fans and followers and “several hundred thousand dollars in new sales in three months of marketing” as well as reaching a new audience, improving public relations and customer service, and gaining feedback for product development
HubSpot's The State of Inbound Marketing 2010 survey found that 41% to 46% of the companies using Twitter, LinkedIn, Facebook or a company blog had acquired a customer from that channel.
Predictive Marketing Blog by Bob Hodgson reported that eight Tweets by a high tech conference with 350 followers generated 10 completed registrations worth $15,000.
I also found plenty of insightful content that doesn’t include specific numbers. In general, there are two schools of thought on social media ROI: some think it really must be tied to revenue and profits to be meaningful; others argue just as passionately that different measures are appropriate depending on the program objective.
Truth be told, my heart is with the “revenue and profits” school. But I suspect it may be too simplistic, so I do accept alternative measures as a valid alternative. The problem with tying social media to "hard" ROI is this often relies on complex intermediate calculations, which are subjective in themselves. That being the case, alternative measures are not necessarily less valid; it depends on the details. (Fallacy alert: just because neither is perfect, it doesn’t follow that both are equally bad).
In any case, here are a few discussions I found particularly worthwhile:
A SlideShare presentation from Peashoot (a social media campaign manager) listing different metrics for different campaigns. These are good examples even though there are no actual results.
An eConsultancy blog post sharing comments on social media ROI from a collection of British experts.
Another eConsultancy post listing ten specific ways to measure social media success.
Thursday, March 18, 2010
Pegasystems Buys Chordiant to Help Coordinate Customer Treatment Decisions
Summary: Pegasystems purchased Chordiant last week, adding a sophisticated cross-channel decision engine to its stable. It's been hard for independent decision engines to survive, even though it seems an independent product should make it easier for marketers to unify their customer treatments.
Business process technology vendor Pegasystems announced on Monday that it was purchasing Chordiant, which offers a central decision engine for customer interactions. Although the news is interesting in its own right, it also triggered a twinge of personal regret because I’ve been meaning to write about Chordiant for nearly a year. At that time, they had just added some slick simulation capabilities that estimated outcomes if a different set of rules had been applied to historical interactions.
This type of simulation allows business managers, rather than technicians, to directly assess the impact of alternative business rules. It's an important sign of maturity, showing that the vendor has shifted resources from primary system functions (making things work) to supporting functions (making things work better).
If you’re not familiar with the Chordiant decision engine, its primary function is to apply business rules that guide real-time customer treatments. It has been deployed primarily in call centers, although it is designed to work across multiple touchpoints. To accomplish this, the system must accept inputs from each touchpoint about a current interaction, apply rules to select an offer, and feed the selection back to the touchpoint. Tracking results also requires a second loop for the touchpoint to report whether the offer was actually delivered and whether it was accepted.
The business rules can use both data provided by the touchpoint and data from other systems such as transaction and marketing databases. The rules frequently include predictive models that can either be built within Chordiant or imported from other systems such as SAS or SPSS. Chordiant also supports self-adjusting models that monitor outcomes and modify future recommendations based on the results of different offers.
The appeal of a stand-alone decision engine like Chordiant is that companies can coordinate treatments without using a single vendor for all their touchpoint systems. This makes perfect sense, since in practice most firms do use different products for different touchpoints. In particular, Web interactions are often managed outside of the CRM system.
Yet it’s still been difficult for stand-alone decision engines to survive. Most firms use whatever interaction management features are built into the separate touchpoint engines and coordinate the rules administratively (if at all). Or they rely on interaction management features provided by their marketing automation system.
A few independent decision engine vendors remain, notably thinkAnalytics (another product I’ve been meaning to write about for months) and eGlue (which I wrote about here [update: a week after this post was written, eGlue was apparently purchased by interaction management vendor NICE Systems, although I've yet to see a formal announcement]). But it’s ultimately not surprising that Chordiant should end up as part of Pegasystems, with which Chordiant had already been integrated. The new relationship will let Pegasystems offer added value to its clients and better compete with CRM vendors.
As an aside, it's interesting to compare the position of decision management vendors with execution vendors like Conversen (which I wrote about last month) and ClickSquared (yet another vendor I hope to review shortly). Both sets of products unify a single function that is otherwise spread across multiple systems: offer selection for decision engines and message delivery for execution engines.
The challenges faced by independent decision engines may suggest that the execution engines will face similar problems. But the execution engines sit at the end of the messaging sequence, rather than in its middle: that is, they process outputs from marketing systems and send them elsewhere, rather than feeding them back into the same systems for delivery. This may make it easier for them to survive.
Business process technology vendor Pegasystems announced on Monday that it was purchasing Chordiant, which offers a central decision engine for customer interactions. Although the news is interesting in its own right, it also triggered a twinge of personal regret because I’ve been meaning to write about Chordiant for nearly a year. At that time, they had just added some slick simulation capabilities that estimated outcomes if a different set of rules had been applied to historical interactions.
This type of simulation allows business managers, rather than technicians, to directly assess the impact of alternative business rules. It's an important sign of maturity, showing that the vendor has shifted resources from primary system functions (making things work) to supporting functions (making things work better).
If you’re not familiar with the Chordiant decision engine, its primary function is to apply business rules that guide real-time customer treatments. It has been deployed primarily in call centers, although it is designed to work across multiple touchpoints. To accomplish this, the system must accept inputs from each touchpoint about a current interaction, apply rules to select an offer, and feed the selection back to the touchpoint. Tracking results also requires a second loop for the touchpoint to report whether the offer was actually delivered and whether it was accepted.
The business rules can use both data provided by the touchpoint and data from other systems such as transaction and marketing databases. The rules frequently include predictive models that can either be built within Chordiant or imported from other systems such as SAS or SPSS. Chordiant also supports self-adjusting models that monitor outcomes and modify future recommendations based on the results of different offers.
The appeal of a stand-alone decision engine like Chordiant is that companies can coordinate treatments without using a single vendor for all their touchpoint systems. This makes perfect sense, since in practice most firms do use different products for different touchpoints. In particular, Web interactions are often managed outside of the CRM system.
Yet it’s still been difficult for stand-alone decision engines to survive. Most firms use whatever interaction management features are built into the separate touchpoint engines and coordinate the rules administratively (if at all). Or they rely on interaction management features provided by their marketing automation system.
A few independent decision engine vendors remain, notably thinkAnalytics (another product I’ve been meaning to write about for months) and eGlue (which I wrote about here [update: a week after this post was written, eGlue was apparently purchased by interaction management vendor NICE Systems, although I've yet to see a formal announcement]). But it’s ultimately not surprising that Chordiant should end up as part of Pegasystems, with which Chordiant had already been integrated. The new relationship will let Pegasystems offer added value to its clients and better compete with CRM vendors.
As an aside, it's interesting to compare the position of decision management vendors with execution vendors like Conversen (which I wrote about last month) and ClickSquared (yet another vendor I hope to review shortly). Both sets of products unify a single function that is otherwise spread across multiple systems: offer selection for decision engines and message delivery for execution engines.
The challenges faced by independent decision engines may suggest that the execution engines will face similar problems. But the execution engines sit at the end of the messaging sequence, rather than in its middle: that is, they process outputs from marketing systems and send them elsewhere, rather than feeding them back into the same systems for delivery. This may make it easier for them to survive.
Friday, March 12, 2010
Matching Social Media to Your Needs and Resources
Summary: Marketers face so many choices that just deciding what to test is a major challenge in itself. Here are some ways to match social media to your business objectives and resources.
I’ll be giving a Webinar on March 23 (register here) with Neolane about cross channel marketing. At least that’s the official topic. In my mind, it’s really about helping marketers choose among the ever-increasing media options available today and in the future.
I won’t go into the details of the presentation, but thought I’d share this chart for selecting among social media.
The chart makes two major points:
- different social media meet different business objectives. I suppose this is self-evident, but it still helps to think about this systematically when you’re trying to decide which to explore. As the chart indicates, most social media can in fact serve more than one objective. Incidentally, the chart lists the objectives in roughly the sequence of the customer life cycle, starting with market preparation activities at the left and moving through purchase and post-purchase support, which further helps you visualize where a particular project fits into your larger customer treatment strategy. You may disagree with particular details on this chart, but that’s less the point than thinking about putting each medium into a larger context.
- media must be matched to your resources. This is also pretty obvious, but, again, it’s easy to ignore it when considering your options. It's also worth pointing out that resources include more than data, technology and experience. My list also includes public interest in your topic and media reach (i.e., your firm’s ability to attract attention to its program, largely by paid advertising). Both make possible social programs that would otherwise fail because no one would participate. It's worth noting that funding can make up for shortfalls in other areas and that strengths in other areas reduce the need for funds.
An Example
The table below gives a simple example of these ideas in action. It analyzes the situation of a hypothetical company facing a major product recall. Objectives in this case are “monitor and respond” to public opinion and provide “customer support” to previous buyers. Highlighting these shows that social networks, Twitter, message boards and Wikis are appropriate options. But let’s assume it’s a small company, with limited media reach and funding, and that it also lacks technology and experience for social networks and Wikis. This leaves Twitter and message boards as the best candidates -- Twitter because there's very little technology involved, and message boards because we assume that company has the necessary resources in place.
Although this example is limited to social media, the same approach can be applied to other media as well. Tune into the Webinar for more details.
I’ll be giving a Webinar on March 23 (register here) with Neolane about cross channel marketing. At least that’s the official topic. In my mind, it’s really about helping marketers choose among the ever-increasing media options available today and in the future.I won’t go into the details of the presentation, but thought I’d share this chart for selecting among social media.
The chart makes two major points:- different social media meet different business objectives. I suppose this is self-evident, but it still helps to think about this systematically when you’re trying to decide which to explore. As the chart indicates, most social media can in fact serve more than one objective. Incidentally, the chart lists the objectives in roughly the sequence of the customer life cycle, starting with market preparation activities at the left and moving through purchase and post-purchase support, which further helps you visualize where a particular project fits into your larger customer treatment strategy. You may disagree with particular details on this chart, but that’s less the point than thinking about putting each medium into a larger context.
- media must be matched to your resources. This is also pretty obvious, but, again, it’s easy to ignore it when considering your options. It's also worth pointing out that resources include more than data, technology and experience. My list also includes public interest in your topic and media reach (i.e., your firm’s ability to attract attention to its program, largely by paid advertising). Both make possible social programs that would otherwise fail because no one would participate. It's worth noting that funding can make up for shortfalls in other areas and that strengths in other areas reduce the need for funds.
An Example
The table below gives a simple example of these ideas in action. It analyzes the situation of a hypothetical company facing a major product recall. Objectives in this case are “monitor and respond” to public opinion and provide “customer support” to previous buyers. Highlighting these shows that social networks, Twitter, message boards and Wikis are appropriate options. But let’s assume it’s a small company, with limited media reach and funding, and that it also lacks technology and experience for social networks and Wikis. This leaves Twitter and message boards as the best candidates -- Twitter because there's very little technology involved, and message boards because we assume that company has the necessary resources in place.
Although this example is limited to social media, the same approach can be applied to other media as well. Tune into the Webinar for more details.
Tuesday, March 02, 2010
Eloqua SmartStart Speeds Marketing Automation Deployment, But It's Still Work
Summary: Eloqua's SmartStart gets marketers rolling in less than one week. It does require extensive preparation, but Eloqua leads you through that too. Let's face it, folks: putting a good demand generation program in place is real work.
Eloqua last week announced a money-back satisfaction guarantee for clients who participate in its SmartStart deployment program. Skeptical creature that I am, I wanted to hear the details before writing about it. By happy coincidence (OR WAS IT?), Eloqua Director of Key Accounts Jill Rowley scheduled a talk with me a few days later and filled me in.
SmartStart is a two-to-five day paid consulting engagement that helps new Eloqua clients fully deploy their systems. It’s not to be confused with the free QuickStart program (which I wrote about last May) which provides a smaller set of services. More than 150 Eloqua clients have now completed the SmartStart process, which is delivered by both Eloqua’s own professional services group and certified consulting partners.
The scope of SmartStart is indeed impressive. By the end of the program, marketers have initial email, forms, landing pages, Website tracking, CRM integration, reporting, and either lead scoring or nurturing programs. One key is preparation – the on-site sessions are preceded by extensive information gathering and technical groundwork, guided by Eloqua templates. This covers CRM integration, adding Web tracking scripts to company Web pages, assembling images and email formats, data cleansing, landing page subdomain set-up, specifying forms content and designing the lead scoring matrix. The process also includes a marketing maturity assessment that helps to define long term plans for improving the client’s marketing operations.
Rowley said most small companies can assemble the necessary information in a few days, although larger organizations take longer. Similarly, the SmartStart process itself works best for firms with relatively simple marketing operations, which Rowley said has less to do with size than numbers of regional offices and lead scoring programs, CRM integration, and existing automation. The single biggest challenge is the complexity of rules that govern CRM data synchronization, which can get very detailed when companies want different treatments in different situations.
The other key to the program is concentration during the SmartStart execution itself. The primary system administrator must devote full time to the project, while other users are brought in as needed. Because most policy decisions are made in advance, the company’s chief marketer doesn’t need to be constantly present.
The price of SmartStart varies from $4,000 to $19,000 depending on the version of Eloqua and type of CRM integration. Although that particular bit of information isn’t published, Rowley did point out to me that Eloqua’s Web site now shows basic price data, which used to be a closely-guarded secret. Pricing rules have also been vastly simplified.
That money-back guarantee? It’s good for six months and applies only to future portions of a subscription: so if you pay for a year and cancel after four months, you get refunded for the remaining eight months. That’s not quite a full refund, but it puts Eloqua on par with competitors who allow month-to-month agreements without an annual contract.
Eloqua last week announced a money-back satisfaction guarantee for clients who participate in its SmartStart deployment program. Skeptical creature that I am, I wanted to hear the details before writing about it. By happy coincidence (OR WAS IT?), Eloqua Director of Key Accounts Jill Rowley scheduled a talk with me a few days later and filled me in.
SmartStart is a two-to-five day paid consulting engagement that helps new Eloqua clients fully deploy their systems. It’s not to be confused with the free QuickStart program (which I wrote about last May) which provides a smaller set of services. More than 150 Eloqua clients have now completed the SmartStart process, which is delivered by both Eloqua’s own professional services group and certified consulting partners.
The scope of SmartStart is indeed impressive. By the end of the program, marketers have initial email, forms, landing pages, Website tracking, CRM integration, reporting, and either lead scoring or nurturing programs. One key is preparation – the on-site sessions are preceded by extensive information gathering and technical groundwork, guided by Eloqua templates. This covers CRM integration, adding Web tracking scripts to company Web pages, assembling images and email formats, data cleansing, landing page subdomain set-up, specifying forms content and designing the lead scoring matrix. The process also includes a marketing maturity assessment that helps to define long term plans for improving the client’s marketing operations.
Rowley said most small companies can assemble the necessary information in a few days, although larger organizations take longer. Similarly, the SmartStart process itself works best for firms with relatively simple marketing operations, which Rowley said has less to do with size than numbers of regional offices and lead scoring programs, CRM integration, and existing automation. The single biggest challenge is the complexity of rules that govern CRM data synchronization, which can get very detailed when companies want different treatments in different situations.
The other key to the program is concentration during the SmartStart execution itself. The primary system administrator must devote full time to the project, while other users are brought in as needed. Because most policy decisions are made in advance, the company’s chief marketer doesn’t need to be constantly present.
The price of SmartStart varies from $4,000 to $19,000 depending on the version of Eloqua and type of CRM integration. Although that particular bit of information isn’t published, Rowley did point out to me that Eloqua’s Web site now shows basic price data, which used to be a closely-guarded secret. Pricing rules have also been vastly simplified.
That money-back guarantee? It’s good for six months and applies only to future portions of a subscription: so if you pay for a year and cancel after four months, you get refunded for the remaining eight months. That’s not quite a full refund, but it puts Eloqua on par with competitors who allow month-to-month agreements without an annual contract.
Thursday, February 25, 2010
Conversen Simplifies Complex Messages Through Multi-Channel Dynamic Content
Summary: Conversen makes it easy to generate dynamic messages across multiple channels. It's more a supplement than a replacement for conventional campaign management but should save a lot of work for marketers and their agencies.
One of the fundamental challenges in database marketing is that a seriously sophisticated campaign may send different messages to hundreds or even thousands of customer segments. The traditional approach has been to define these segments during the selection process, creating a tree with one end-point for each segment, and then to assign the appropriate message to each end-point. The problem is that this requires creating hundreds of versions of the messages and making sure that each is matched to the correct end-point. This is both labor-intensive and error-prone.
An alternative is to create "dynamic content" the messages that select the appropriate contents for each individual. In essence, this is moving some of the segmentation logic from the selection process to inside the message. Even though this ultimately produces the same number of variations, it lets marketers create fewer messages and segments, reducing manual effort.
Let’s take a concrete example. Suppose you’re sending offers for winter vacation travel. People in New York will be sent offers for Florida and people in Los Angeles will get offers for Mexico. In addition, people in high-income zip codes will be offered a deluxe package while those in middle-income zip codes get an economy offer. A segmentation-based approach would use three segmentation rules (New York or Los Angeles; if New York, high or middle income; if Los Angeles, high or middle income) to create four segments, each tied to a separate message. A dynamic content approach would require just two decisions (New York or Los Angeles, high or middle income) that are each tied to a specific content block.
It’s still possible to make a mistake: you could accidentally link the Mexico offer to New York. But each assignment is made only once so it’s easier to be sure it’s correct.
Note that the advantage of dynamic content increases as you add complexity: a three city-pair, three level program would require four segmentation rules (one for city, three for city/level combination) and nine unique messages, while dynamic content still needs only two rules (one for city, one for level) and six message blocks (three destination cities, three luxury levels).
So where’s the catch? Well, dynamic content requires the marketing automation vendor to work inside the message itself, using different technologies for each medium. This is significantly trickier than just pointing each segment to a message created elsewhere.
One way to avoid this complexity is to generate a file containing the customer records and segmentation variables and let channel-specific output systems generate the customized messages. But this adds its own costs and risks, since the external systems must be configured separately for each project. As a practical matter, most high-end marketing automation vendors have compromised by providing dynamic customization for email and Web pages, and letting external systems handle the other channels.
Conversen has taken a different approach, building a specialized system to support dynamic content across as many channels as possible. This puts it in a somewhat confusing business position, since it can sometimes replace a traditional campaign management system but more often receives output from one. Resolving this confusion is largely Conversen's own problem, however, since it sells to marketing service providers rather than end-users.
Conversen is organized primarily around campaigns. These include filters to select an audience, processing steps and content. The key here is consistency: the rules used in filters, steps and dynamic content are exactly the same. It's not just that they're built with the same interface and run against the same data structures: the same rule can actually be used for any purpose. Rules can also be shared across multiple campaigns and referenced within other rules. This reuse substantially reduces the number of rules needed, and thus both the effort and opportunity for error.
The rules themselves are quite powerful, extending beyond the usual selections on field values to include advanced features such as if/then/else loops. One gap is missing support for a/b testing, which Conversen decided to omit because it added too much complexity. The system doesn’t maintain an audit trail of changes to each rule, but does provide reports listing everywhere each rule is used. This helps to avoid unintentional consequences when a rule is changed.
Rules connect with data gathered from source systems through batch processes or a real-time API. The resulting database is stored in Microsoft SQL Server and hosted by Conversen. This is important point, since it means that Conversen doesn’t simply attach to an existing marketing database. Although moving data into a separate database does add some cost, it also provides options to maintain persistent customer histories, combine data from multiple sources, and directly capture events such as campaign responses.
The system includes basic features to define data structures and map data from external sources into those structures. Load maps can include basic rules for whether to update or append matching records, but more advanced processes such as name/address matching have to be done externally.
Users who don’t need any of these functions could simply send Conversen the output files from a conventional campaign manager. This costs no more than loading files into any other message delivery system.
The heart of Conversen are the marketing messages. Conversen defines each message as an XML template. This holds any static elements plus the rules used to select content blocks.
The blocks themselves are created outside of Conversen and stored in a content library. This is another example of Conversen drawing the line between its core functionality and supporting functions to be handled elsewhere. It also probably reflects the reality that content will be created by external vendors, such as ad agencies, who will want to use their own tools in any event. Lack of an integrated content-builder does mean that personalization tokens such as [First Name] must be manually embedded within the content block. This can be done in the original content creation system, requiring a relatively inconvenient cut-and-paste from a list provided by Conversen, or be added after the content is loaded into Conversen.
Each Conversen content block currently supports a single medium. Thus, there would be separate content blocks for 10% discount in email, Web, direct mail, mobile and other types of messages. Conversen is working on multi-media content blocks that could be inserted into any medium. This would further simplify marketers’ lives.
One Conversen campaign can deliver multiple messages over time, based on dates such as a contract expiration or recent activity, or on events such as promotion responses. The system can react to qualifying events at regular intervals or in near-real-time as they are posted.
Clients can also build custom interfaces by direct access to the Conversen API. This lets them create branded systems and offer specialized portals with limited functionality. These might give designers access to the content-management features of the system, or make predefined campaigns to available to field offices.
Conversen supports email, mobile (SMS), RSS feeds such as blog posts, print, call center and Web. The system provides specialized services for each channel, such as rendering to preview emails and postal sorting for direct mail. Print output is integrated with Bitstream PageFlex, which supports direct output to high-speed printers. Conversen sends the digital messages itself and ships print and call center files to third parties for execution.
The system also provides operational reporting on campaign volume and responses. The reports are designed to provide activity information rather than detailed marketing analysis.
Conversen was introduced in 2007. The company now has about 25 marketing agencies as customers, serving more than 125 end clients. The system is offered only as a Conversen-hosted service. Pricing includes a $15,000 setup fee plus $1 to $20 per thousand messages based on volume and type.
One of the fundamental challenges in database marketing is that a seriously sophisticated campaign may send different messages to hundreds or even thousands of customer segments. The traditional approach has been to define these segments during the selection process, creating a tree with one end-point for each segment, and then to assign the appropriate message to each end-point. The problem is that this requires creating hundreds of versions of the messages and making sure that each is matched to the correct end-point. This is both labor-intensive and error-prone.
An alternative is to create "dynamic content" the messages that select the appropriate contents for each individual. In essence, this is moving some of the segmentation logic from the selection process to inside the message. Even though this ultimately produces the same number of variations, it lets marketers create fewer messages and segments, reducing manual effort.
Let’s take a concrete example. Suppose you’re sending offers for winter vacation travel. People in New York will be sent offers for Florida and people in Los Angeles will get offers for Mexico. In addition, people in high-income zip codes will be offered a deluxe package while those in middle-income zip codes get an economy offer. A segmentation-based approach would use three segmentation rules (New York or Los Angeles; if New York, high or middle income; if Los Angeles, high or middle income) to create four segments, each tied to a separate message. A dynamic content approach would require just two decisions (New York or Los Angeles, high or middle income) that are each tied to a specific content block.
It’s still possible to make a mistake: you could accidentally link the Mexico offer to New York. But each assignment is made only once so it’s easier to be sure it’s correct.
Note that the advantage of dynamic content increases as you add complexity: a three city-pair, three level program would require four segmentation rules (one for city, three for city/level combination) and nine unique messages, while dynamic content still needs only two rules (one for city, one for level) and six message blocks (three destination cities, three luxury levels).
So where’s the catch? Well, dynamic content requires the marketing automation vendor to work inside the message itself, using different technologies for each medium. This is significantly trickier than just pointing each segment to a message created elsewhere.
One way to avoid this complexity is to generate a file containing the customer records and segmentation variables and let channel-specific output systems generate the customized messages. But this adds its own costs and risks, since the external systems must be configured separately for each project. As a practical matter, most high-end marketing automation vendors have compromised by providing dynamic customization for email and Web pages, and letting external systems handle the other channels.
Conversen has taken a different approach, building a specialized system to support dynamic content across as many channels as possible. This puts it in a somewhat confusing business position, since it can sometimes replace a traditional campaign management system but more often receives output from one. Resolving this confusion is largely Conversen's own problem, however, since it sells to marketing service providers rather than end-users.
Conversen is organized primarily around campaigns. These include filters to select an audience, processing steps and content. The key here is consistency: the rules used in filters, steps and dynamic content are exactly the same. It's not just that they're built with the same interface and run against the same data structures: the same rule can actually be used for any purpose. Rules can also be shared across multiple campaigns and referenced within other rules. This reuse substantially reduces the number of rules needed, and thus both the effort and opportunity for error.
The rules themselves are quite powerful, extending beyond the usual selections on field values to include advanced features such as if/then/else loops. One gap is missing support for a/b testing, which Conversen decided to omit because it added too much complexity. The system doesn’t maintain an audit trail of changes to each rule, but does provide reports listing everywhere each rule is used. This helps to avoid unintentional consequences when a rule is changed.
Rules connect with data gathered from source systems through batch processes or a real-time API. The resulting database is stored in Microsoft SQL Server and hosted by Conversen. This is important point, since it means that Conversen doesn’t simply attach to an existing marketing database. Although moving data into a separate database does add some cost, it also provides options to maintain persistent customer histories, combine data from multiple sources, and directly capture events such as campaign responses.
The system includes basic features to define data structures and map data from external sources into those structures. Load maps can include basic rules for whether to update or append matching records, but more advanced processes such as name/address matching have to be done externally.
Users who don’t need any of these functions could simply send Conversen the output files from a conventional campaign manager. This costs no more than loading files into any other message delivery system.
The heart of Conversen are the marketing messages. Conversen defines each message as an XML template. This holds any static elements plus the rules used to select content blocks.
The blocks themselves are created outside of Conversen and stored in a content library. This is another example of Conversen drawing the line between its core functionality and supporting functions to be handled elsewhere. It also probably reflects the reality that content will be created by external vendors, such as ad agencies, who will want to use their own tools in any event. Lack of an integrated content-builder does mean that personalization tokens such as [First Name] must be manually embedded within the content block. This can be done in the original content creation system, requiring a relatively inconvenient cut-and-paste from a list provided by Conversen, or be added after the content is loaded into Conversen.
Each Conversen content block currently supports a single medium. Thus, there would be separate content blocks for 10% discount in email, Web, direct mail, mobile and other types of messages. Conversen is working on multi-media content blocks that could be inserted into any medium. This would further simplify marketers’ lives.
One Conversen campaign can deliver multiple messages over time, based on dates such as a contract expiration or recent activity, or on events such as promotion responses. The system can react to qualifying events at regular intervals or in near-real-time as they are posted.
Clients can also build custom interfaces by direct access to the Conversen API. This lets them create branded systems and offer specialized portals with limited functionality. These might give designers access to the content-management features of the system, or make predefined campaigns to available to field offices.
Conversen supports email, mobile (SMS), RSS feeds such as blog posts, print, call center and Web. The system provides specialized services for each channel, such as rendering to preview emails and postal sorting for direct mail. Print output is integrated with Bitstream PageFlex, which supports direct output to high-speed printers. Conversen sends the digital messages itself and ships print and call center files to third parties for execution.
The system also provides operational reporting on campaign volume and responses. The reports are designed to provide activity information rather than detailed marketing analysis.
Conversen was introduced in 2007. The company now has about 25 marketing agencies as customers, serving more than 125 end clients. The system is offered only as a Conversen-hosted service. Pricing includes a $15,000 setup fee plus $1 to $20 per thousand messages based on volume and type.
Monday, February 08, 2010
ExactTarget Survey: Lack of Skills Slows Growth of Digital Marketing
Summary: a new survey from ExactTarget shows that digital marketing is growing faster than database marketing or mass media, and that agencies have a harder time adding digital capabilities than their clients. It also suggests that marketers are moving into digital channels even when they can’t measure their value very well. No surprises in any of this, but good to see confirmation of previous research.
I really and truly was going to drop the topic of moving from database to digital marketing, but then I saw a survey last week from email vendor ExactTarget which reinforced several of my key points. (You can buy the complete survey from Econsultancy. A detailed slide show is available here for free, at least as I write this.) Key findings include:
- digital marketing budgets are growing faster than marketing in general (66% plan to increase their digital budget in 2010, vs 46% planning to increase their total marketing budget). Database marketing channels (email, direct mail and telephone) are growing at lower rates (54%, 27% and 26% plan to increase, respectively), while mass media (television, newspapers/magazines and radio) are lagging the most (20%, 17% and 15%).
Note that these are just the percentage of companies planning a budget increase; the actual average increase in digital budget was 17%. The average proportion of budget spent on digital was 24%, which is higher than other figures I’ve seen, suggesting the respondents were more digitally oriented than the industry as a whole.
- lack of skills is the key impediment to digital growth: lack of staff, company culture and lack of digital understanding were three of top four problems (after lack of budget, which was number 1). Inability to measure ROI and lack of business case ranked only ahead of “other”.
What is preventing your company from investing more money in digital marketing?
40% restricted budget for all types of marketing
35% lack of staff to make most of any digital investment
32% company culture
25% lack of understanding about digital
20% reliance on traditional marketing
16% inability to measure return on investment
9% lack of business case / case studies around digital
7% other
- agencies are more constrained than marketers by lack of skills. “Lack of understanding about digital” was cited by 45% of agency respondents, compared with about 13% of client-side marketers.* My interpretation is that clients can always go and hire a digital agency if they need to add the expertise, while the agencies themselves find it much harder to expand their offerings.
In fact, although 35% of both groups apparently cited “lack of staff” as a problem, they may mean different things. Agencies are probably referring to lack of staff with digital marketing skills. Client-side marketers probably mean lack of staff to oversee digital programs executed by an outside agency.
- The fastest-growing digital channels (social media and mobile) are the least measurable. In fact, there’s an almost inverted relationship between growth rates and measurability. This probably reflects that fact the fastest-growing channels are the newest, with least-established measurement methods, rather than a perverse hostility to measurability.
In this context, it’s also worth noting that agencies felt much more hobbled by lack of ROI and business cases than client-side marketers, and that a very-hard-to-believe 65% said their company measures marketing effectiveness based on ROI. These further reinforce the view that marketing measurement isn’t a top priority when moving into new digital channels.
__________________________________________________________________
* The published materials show total and agency figures. I've estimated values for client-side marketers based on the numbers of respondents reported for the two groups: 648 client-side, 385 agency/supplier-side. This won’t be precisely correct, since everybody didn’t answer every question. Hence that -3% response to "lack of business case" for client-side.
I really and truly was going to drop the topic of moving from database to digital marketing, but then I saw a survey last week from email vendor ExactTarget which reinforced several of my key points. (You can buy the complete survey from Econsultancy. A detailed slide show is available here for free, at least as I write this.) Key findings include:
- digital marketing budgets are growing faster than marketing in general (66% plan to increase their digital budget in 2010, vs 46% planning to increase their total marketing budget). Database marketing channels (email, direct mail and telephone) are growing at lower rates (54%, 27% and 26% plan to increase, respectively), while mass media (television, newspapers/magazines and radio) are lagging the most (20%, 17% and 15%).
Note that these are just the percentage of companies planning a budget increase; the actual average increase in digital budget was 17%. The average proportion of budget spent on digital was 24%, which is higher than other figures I’ve seen, suggesting the respondents were more digitally oriented than the industry as a whole.
- lack of skills is the key impediment to digital growth: lack of staff, company culture and lack of digital understanding were three of top four problems (after lack of budget, which was number 1). Inability to measure ROI and lack of business case ranked only ahead of “other”.
What is preventing your company from investing more money in digital marketing?
40% restricted budget for all types of marketing
35% lack of staff to make most of any digital investment
32% company culture
25% lack of understanding about digital
20% reliance on traditional marketing
16% inability to measure return on investment
9% lack of business case / case studies around digital
7% other
- agencies are more constrained than marketers by lack of skills. “Lack of understanding about digital” was cited by 45% of agency respondents, compared with about 13% of client-side marketers.* My interpretation is that clients can always go and hire a digital agency if they need to add the expertise, while the agencies themselves find it much harder to expand their offerings.
In fact, although 35% of both groups apparently cited “lack of staff” as a problem, they may mean different things. Agencies are probably referring to lack of staff with digital marketing skills. Client-side marketers probably mean lack of staff to oversee digital programs executed by an outside agency.
- The fastest-growing digital channels (social media and mobile) are the least measurable. In fact, there’s an almost inverted relationship between growth rates and measurability. This probably reflects that fact the fastest-growing channels are the newest, with least-established measurement methods, rather than a perverse hostility to measurability.
In this context, it’s also worth noting that agencies felt much more hobbled by lack of ROI and business cases than client-side marketers, and that a very-hard-to-believe 65% said their company measures marketing effectiveness based on ROI. These further reinforce the view that marketing measurement isn’t a top priority when moving into new digital channels.
__________________________________________________________________
* The published materials show total and agency figures. I've estimated values for client-side marketers based on the numbers of respondents reported for the two groups: 648 client-side, 385 agency/supplier-side. This won’t be precisely correct, since everybody didn’t answer every question. Hence that -3% response to "lack of business case" for client-side.
Thursday, February 04, 2010
Coremetrics Survey: Online Marketers Eager to Consolidate Data Across Channels
Summary: a survey sponsored by Coremetrics shows that online marketers are eager to merge data from multiple sources. This is the long-term solution to closing the gap between database and digital marketers.
I was debating yet another post on database vs digital marketing when I saw a Direct Newsline headline that said “Online Marketers Talk The Talk, But Don't Walk The Walk”. The accompanying article suggested the online marketers don’t give personalization a high priority, which supports the theme of my last few posts. Sweet.
But reality proves a bit more complex.
The article referred to a survey of online marketers sponsored by Web analytics vendor Coremetrics. As the headline suggests, about three-quarters of the marketers listed personalized email, display advertising and onsite pages as a high priority, but just under half are actually using them. So, yes, there’s more talking than walking.
But a closer look* shows that the “future priority” numbers are also related to current deployment: items like basic email marketing have low future priority scores because they’re already in widespread use. So the apparent discrepancy in the personalization rankings is less because online marketers don’t really care about it, than because they’ve had other, more fundamental things to do first.
If I were feeling particularly tendentious, I could argue other data in survey supports my claim that digital marketers are relatively disinterested in personalization. For example, “manual onsite cross-selling promotions and product recommendations” has a higher deployment rate (63%) than “manual onsite personalized content and recommendations” (49%). But a simpler explanation is that personalized recommendations are just technically harder. Indeed, the two “technology-driven” options, recommendations based on individual behavior and on “wisdom of the clouds”, have the lowest of all current deployment rates.
That said, it’s still interesting that the survey shows personalized email (52% deployed) as not significantly more common than personalized advertising (50%) or personalized site content (49%). This seems to contradict my position: if email is run by personalization-oriented database marketers, while Web advertising and (perhaps) site content are run by behavioral-targeting-oriented digital marketers, then email personalization should be more common.
But the actual question asks about email, display advertising and onsite content which are personalized "based on individual online behavior”. This adds the additional constraint of whether marketers have been able to tie (mostly anonymous) online behavior to other channels. That constraint applies across all the delivery channels, and is likely why the deployment rates are so similar. Surely the vast majority marketers are personalizing their email using information in their databases, particularly if you extend the definition of "personalization" to include segmentation that determines which messages are sent to whom.
A separate question asked marketers to rate the importance of automating different marketing tools.
What's interesting about those answers is that five of the top six didn't involve individual-level data: three are about campaign, channel and vendor performance, and the other two are about search keywords in aggregate. The only exception, "personalized content or product recommendations based on online behavior" is based on reusing data within a single channel, which means that individuals need not be personally identified. (The survey makes clear that its definition of "personalization" includes treatments based on anonymous behavior tracking.) Actually, the two applications that do rely on consolidating personal data across channels are the lowest ranked of all the options presented. I'd say this supports my fundamental contention that digital marketers are mostly concerned about non-personal, channel-specific applications.
On the other hand, respondents did rate “obtaining an integrated view of customers across online marketing touch points” as their highest challenge, or at least as a tie with measuring marketing impact. Since it was only listed by 45% of the respondents, I could speculate that those might have been the database (email) marketers in the group, while the digital (Web) marketers could have all ignored it.
But I’m not inclined to bother: I have no problem believing that digital marketers are perfectly willing, even eager, to consolidate data across channels when it’s possible. My main point is consolidation is generally not possible because most digital touchpoints do not collect identifiable, addressable information. (See yesterdays’ post for my definitions of those terms.) And, because consolidated data is often not available, the digital marketers have learned to work without it.
By contrast, Coremetrics is focused on a future (or, perhaps, imaginary) world where data-gathering techniques have improved. Coremetrics is arguing, and I fully agree, that consolidating data across channels does add value and that marketers should be willing to invest in making it happen.
In fact, if I hadn’t seen the survey this morning, my intent was to write about the convergence of database and digital marketing, precisely because digital marketers are increasingly aware of the value and possibilities of working from a consolidated database. So even though I’ve been arguing that database and digital marketing today are quite different, I do think they’ll become more similar over time as each group learns from the other. The marketers themselves are already leading in that direction, and vendors who want to survive will surely follow.
______________________________________________
* very close indeed. Sorry for the small print in the charts. It's the best I could do. The actual data is available in the surveys.
I was debating yet another post on database vs digital marketing when I saw a Direct Newsline headline that said “Online Marketers Talk The Talk, But Don't Walk The Walk”. The accompanying article suggested the online marketers don’t give personalization a high priority, which supports the theme of my last few posts. Sweet.
But reality proves a bit more complex.
The article referred to a survey of online marketers sponsored by Web analytics vendor Coremetrics. As the headline suggests, about three-quarters of the marketers listed personalized email, display advertising and onsite pages as a high priority, but just under half are actually using them. So, yes, there’s more talking than walking.
But a closer look* shows that the “future priority” numbers are also related to current deployment: items like basic email marketing have low future priority scores because they’re already in widespread use. So the apparent discrepancy in the personalization rankings is less because online marketers don’t really care about it, than because they’ve had other, more fundamental things to do first.
If I were feeling particularly tendentious, I could argue other data in survey supports my claim that digital marketers are relatively disinterested in personalization. For example, “manual onsite cross-selling promotions and product recommendations” has a higher deployment rate (63%) than “manual onsite personalized content and recommendations” (49%). But a simpler explanation is that personalized recommendations are just technically harder. Indeed, the two “technology-driven” options, recommendations based on individual behavior and on “wisdom of the clouds”, have the lowest of all current deployment rates.
That said, it’s still interesting that the survey shows personalized email (52% deployed) as not significantly more common than personalized advertising (50%) or personalized site content (49%). This seems to contradict my position: if email is run by personalization-oriented database marketers, while Web advertising and (perhaps) site content are run by behavioral-targeting-oriented digital marketers, then email personalization should be more common.
But the actual question asks about email, display advertising and onsite content which are personalized "based on individual online behavior”. This adds the additional constraint of whether marketers have been able to tie (mostly anonymous) online behavior to other channels. That constraint applies across all the delivery channels, and is likely why the deployment rates are so similar. Surely the vast majority marketers are personalizing their email using information in their databases, particularly if you extend the definition of "personalization" to include segmentation that determines which messages are sent to whom.
A separate question asked marketers to rate the importance of automating different marketing tools.
What's interesting about those answers is that five of the top six didn't involve individual-level data: three are about campaign, channel and vendor performance, and the other two are about search keywords in aggregate. The only exception, "personalized content or product recommendations based on online behavior" is based on reusing data within a single channel, which means that individuals need not be personally identified. (The survey makes clear that its definition of "personalization" includes treatments based on anonymous behavior tracking.) Actually, the two applications that do rely on consolidating personal data across channels are the lowest ranked of all the options presented. I'd say this supports my fundamental contention that digital marketers are mostly concerned about non-personal, channel-specific applications.
On the other hand, respondents did rate “obtaining an integrated view of customers across online marketing touch points” as their highest challenge, or at least as a tie with measuring marketing impact. Since it was only listed by 45% of the respondents, I could speculate that those might have been the database (email) marketers in the group, while the digital (Web) marketers could have all ignored it.
But I’m not inclined to bother: I have no problem believing that digital marketers are perfectly willing, even eager, to consolidate data across channels when it’s possible. My main point is consolidation is generally not possible because most digital touchpoints do not collect identifiable, addressable information. (See yesterdays’ post for my definitions of those terms.) And, because consolidated data is often not available, the digital marketers have learned to work without it.
By contrast, Coremetrics is focused on a future (or, perhaps, imaginary) world where data-gathering techniques have improved. Coremetrics is arguing, and I fully agree, that consolidating data across channels does add value and that marketers should be willing to invest in making it happen.
In fact, if I hadn’t seen the survey this morning, my intent was to write about the convergence of database and digital marketing, precisely because digital marketers are increasingly aware of the value and possibilities of working from a consolidated database. So even though I’ve been arguing that database and digital marketing today are quite different, I do think they’ll become more similar over time as each group learns from the other. The marketers themselves are already leading in that direction, and vendors who want to survive will surely follow.
______________________________________________
* very close indeed. Sorry for the small print in the charts. It's the best I could do. The actual data is available in the surveys.
Wednesday, February 03, 2010
Clarifying the Differences Between Database and Digital Marketing
Summary: Database and digital marketing are both data-driven. But they differ in plenty of other ways that make it hard for specialists in one to adapt smoothly to the other. Here's a detailed look at the differences.
Yesterday’s long (or merely long-winded?) post described the different mindsets of database and digital marketers but it was pretty short on differences between the two marketing methods themselves. Today I’ll try to be more concrete.
DB or Not DB
Database marketing is built around a marketing database that contains addressable, identifiable individuals. By “addressable”, I mean there is information such as a mailing address or phone number that lets the marketer contact the individual. By “identifiable”, I mean information is available to link data about the same individual from multiple sources. Addresses are the most common identifiable information, although there are also non-address identifiers such as Social Security Number. Addresses and identifiers are both required: a database without addresses couldn’t be used for most marketing, and a set of records that can’t be linked to other sources is just a list.
The consolidated database is the heart of the database marketing concept. Data from multiple sources lets database marketers make more effective predictions about the best treatments for each individual, and treatments across multiple channels are more effective when they are coordinated centrally. The marketing database contains attributes (age, income, location, etc.) and behaviors (promotion responses, purchases, customer service interactions, etc.). It can certainly include digital activities such as Web page views and social media comments, so long as these can be linked back to a known individual.
Digital marketing does not use a database of addressable, identifiable individuals. It may gather information from one source and even track it over time for the same entity. (Example: Web site behavior tied to a browser cookie.) But unless the entity can be linked to other sources through an identifier, the digital marketer can only make treatment decisions based on information captured in the source channel itself. This is far from useless – behavioral and contextual targeting can be quite powerful. But from a database marketing perspective, the data is frustratingly incomplete.
Addressable Media
Database marketing only works in addressable media: that is, where a message can sent to a specific individual. Addressable media include direct mail, email, outbound telemarketing, and customer service interactions. They can also include digital channels such as Web pages, mobile messages, kiosks and ATM machines, but ONLY where the recipient is known before a message is sent. Thus, a Web page that has identified me because I’ve registered and logged in (manually or via a cookie) is addressable; a Web page that I visit anonymously, even if it recognizes me as a previous visitor from a cookie, is not addressable.
Digital marketing includes many non-addressable media, including paid and organic search, Web banner advertising, social media, and anonymous forms of Web sites, kiosks, mobile (e.g., location-based messages), and the rest. These generate plenty of useful data, such as click through rates, search rankings, sentiment analysis, and page views. But this data and related analysis are quite different from what database marketers are used to.
Prediction vs Reaction
Database marketers have the rich information needed to accurately predict which offers are most appropriate for each customer. Combined with their access to customer addresses, this allows them to initiate effective outbound marketing campaigns and to define static rules for interactive dialogs. Note that in most addressable media (mail, email, outbound telemarketing), the offer must be selected before the customer is actually contacted, and making multiple offers often reduces response. So database marketers have strong reasons to work on making highly accurate predictions.
By definition, digital marketers cannot target outbound campaigns at individuals. They do have opportunities to manage interactions, but often know only what has happened during the current interaction itself. This greatly reduces their ability to make predictions. Instead, they present multiple options and react as people respond. Happily, most digital media are inherently interactive, so this is a practical approach. Since rule-based decision flows are less viable as the number of options increases, digital marketers lean more heavily on self-adjusting automated decision engines.
Message Control
Database marketers directly control the messages they send to each customer. This is yet another factor that helps to justify the costs of building a comprehensive database, running sophisticated predictive models and precisely customizing each message.
Digital marketers have vastly less control over who sees what. Much of their messaging is blind to the audience who will see it, or can only be targeted on limited information about behavior or context. Indeed, some of the most effective and intriguing digital marketing techniques, such as viral campaigns and shareable widgets, rely on distribution that's totally beyond the marketer's control. Social media provide even less control, since the messages themselves are composed outside the company. The net result of all this is to reduce the degree of individual targeting that digital marketers can execute.
Response Measurement
Database marketers can typically capture response to a promotion directly, with a coupon, telephone call or Web click. Even when they can’t, their database still ultimately tells them who bought what, so they can correlate the promotions they’ve addressed to an individual with that individual’s subsequent behavior. The ability to do precise response measurement is yet another factor that lets database marketers fine-tune their programs.
Digital marketers can also measure who clicks on a Web ad, and sometimes can track that person further into the buying cycle. But they don’t know what other promotions or social media that person saw, what else they purchased, who else saw the same promotion but didn’t respond, or who responded through some other channel. All these uncertainties leave digital marketers reliant on indirect measures, such as consumer panels and surveys, which are more typical of conventional mass media. These are approaches that most database marketers would find almost laughably imprecise.
What’s It All Mean?
Database marketers and digital marketers both have plenty of data and the good ones are highly analytical. Both can apply advanced statistical techniques and rigorous testing methods. Both can work to integrate their data and their customer strategies across channels. To some extent, they even work with the same media: in particular, a Web site can support both digital (anonymous) and database-driven (addressable) marketing programs.
Yet despite these similarities and interactions, the two groups work in largely different media, use different techniques and have different priorities. Database marketing is inherently more controlled and precise; digital marketing is more fluid. Good marketers will learn to apply both. But individuals who have specialized in any one area will find it hard to adjust to the other. At a minimum, they’ll need to be conscious that the old rules don’t apply.
Adjustment is even harder for organizations, who will have invested in specialized systems, processes and people to support one technique or the other. This, in my opinion, is why the leading database marketing vendors have not been the leading digital marketing vendors. Which, if you’ll recall, was where I started this discussion.
One final point: there's no reason the same organization or individual can't master both database and digital marketing. That is, although there are major differences between the two, there is no fundamental conflict. My point in these articles is simply that it will take conscious effort to address the differences and fill the gaps that they imply.
Yesterday’s long (or merely long-winded?) post described the different mindsets of database and digital marketers but it was pretty short on differences between the two marketing methods themselves. Today I’ll try to be more concrete.
DB or Not DB
Database marketing is built around a marketing database that contains addressable, identifiable individuals. By “addressable”, I mean there is information such as a mailing address or phone number that lets the marketer contact the individual. By “identifiable”, I mean information is available to link data about the same individual from multiple sources. Addresses are the most common identifiable information, although there are also non-address identifiers such as Social Security Number. Addresses and identifiers are both required: a database without addresses couldn’t be used for most marketing, and a set of records that can’t be linked to other sources is just a list.
The consolidated database is the heart of the database marketing concept. Data from multiple sources lets database marketers make more effective predictions about the best treatments for each individual, and treatments across multiple channels are more effective when they are coordinated centrally. The marketing database contains attributes (age, income, location, etc.) and behaviors (promotion responses, purchases, customer service interactions, etc.). It can certainly include digital activities such as Web page views and social media comments, so long as these can be linked back to a known individual.
Digital marketing does not use a database of addressable, identifiable individuals. It may gather information from one source and even track it over time for the same entity. (Example: Web site behavior tied to a browser cookie.) But unless the entity can be linked to other sources through an identifier, the digital marketer can only make treatment decisions based on information captured in the source channel itself. This is far from useless – behavioral and contextual targeting can be quite powerful. But from a database marketing perspective, the data is frustratingly incomplete.
Addressable Media
Database marketing only works in addressable media: that is, where a message can sent to a specific individual. Addressable media include direct mail, email, outbound telemarketing, and customer service interactions. They can also include digital channels such as Web pages, mobile messages, kiosks and ATM machines, but ONLY where the recipient is known before a message is sent. Thus, a Web page that has identified me because I’ve registered and logged in (manually or via a cookie) is addressable; a Web page that I visit anonymously, even if it recognizes me as a previous visitor from a cookie, is not addressable.
Digital marketing includes many non-addressable media, including paid and organic search, Web banner advertising, social media, and anonymous forms of Web sites, kiosks, mobile (e.g., location-based messages), and the rest. These generate plenty of useful data, such as click through rates, search rankings, sentiment analysis, and page views. But this data and related analysis are quite different from what database marketers are used to.
Prediction vs Reaction
Database marketers have the rich information needed to accurately predict which offers are most appropriate for each customer. Combined with their access to customer addresses, this allows them to initiate effective outbound marketing campaigns and to define static rules for interactive dialogs. Note that in most addressable media (mail, email, outbound telemarketing), the offer must be selected before the customer is actually contacted, and making multiple offers often reduces response. So database marketers have strong reasons to work on making highly accurate predictions.
By definition, digital marketers cannot target outbound campaigns at individuals. They do have opportunities to manage interactions, but often know only what has happened during the current interaction itself. This greatly reduces their ability to make predictions. Instead, they present multiple options and react as people respond. Happily, most digital media are inherently interactive, so this is a practical approach. Since rule-based decision flows are less viable as the number of options increases, digital marketers lean more heavily on self-adjusting automated decision engines.
Message Control
Database marketers directly control the messages they send to each customer. This is yet another factor that helps to justify the costs of building a comprehensive database, running sophisticated predictive models and precisely customizing each message.
Digital marketers have vastly less control over who sees what. Much of their messaging is blind to the audience who will see it, or can only be targeted on limited information about behavior or context. Indeed, some of the most effective and intriguing digital marketing techniques, such as viral campaigns and shareable widgets, rely on distribution that's totally beyond the marketer's control. Social media provide even less control, since the messages themselves are composed outside the company. The net result of all this is to reduce the degree of individual targeting that digital marketers can execute.
Response Measurement
Database marketers can typically capture response to a promotion directly, with a coupon, telephone call or Web click. Even when they can’t, their database still ultimately tells them who bought what, so they can correlate the promotions they’ve addressed to an individual with that individual’s subsequent behavior. The ability to do precise response measurement is yet another factor that lets database marketers fine-tune their programs.
Digital marketers can also measure who clicks on a Web ad, and sometimes can track that person further into the buying cycle. But they don’t know what other promotions or social media that person saw, what else they purchased, who else saw the same promotion but didn’t respond, or who responded through some other channel. All these uncertainties leave digital marketers reliant on indirect measures, such as consumer panels and surveys, which are more typical of conventional mass media. These are approaches that most database marketers would find almost laughably imprecise.
What’s It All Mean?
Database marketers and digital marketers both have plenty of data and the good ones are highly analytical. Both can apply advanced statistical techniques and rigorous testing methods. Both can work to integrate their data and their customer strategies across channels. To some extent, they even work with the same media: in particular, a Web site can support both digital (anonymous) and database-driven (addressable) marketing programs.
Yet despite these similarities and interactions, the two groups work in largely different media, use different techniques and have different priorities. Database marketing is inherently more controlled and precise; digital marketing is more fluid. Good marketers will learn to apply both. But individuals who have specialized in any one area will find it hard to adjust to the other. At a minimum, they’ll need to be conscious that the old rules don’t apply.
Adjustment is even harder for organizations, who will have invested in specialized systems, processes and people to support one technique or the other. This, in my opinion, is why the leading database marketing vendors have not been the leading digital marketing vendors. Which, if you’ll recall, was where I started this discussion.
One final point: there's no reason the same organization or individual can't master both database and digital marketing. That is, although there are major differences between the two, there is no fundamental conflict. My point in these articles is simply that it will take conscious effort to address the differences and fill the gaps that they imply.
Tuesday, February 02, 2010
Can Database Marketers Learn Digital Tricks?
Summary: Database marketing and digital marketing are more different than it seems. It's hard for experts in one to adjust to the other.
Yesterday’s post touched briefly on what I see as a fundamental transition between database marketing and digital marketing, and in particular on the changes that marketers and their supporting vendors must make to navigate the change successfully. This is an important topic, so I thought I’d return for a closer look.
It’s self-evident that digital marketing (mostly on the Internet, but also mobile, in-game, and eventually interactive TV) is a major change from both traditional mass media and more recent database marketing (mail, email, telemarketing, CRM). What’s less obvious is that the skills and attitudes that have served database marketers well for the past twenty or more years – an entire career for many – don’t transfer to the digital world. It’s true that database and digital marketing are both technology-enabled and thus seem as if they should draw on similar talents. But the similarities are superficial while the differences are profound.
Let’s cut to the core of the matter: the first rule of database marketing is that whoever has the biggest database, wins. Database marketers strive to gather ever-more information about their customers and (to a lesser extent, because less data is available) about their prospects. Their Holy Grail is the ever-receding “360 degree view of the customer,” a phrase I’ve always disliked because (a) it treats the customer as an object and (b) no one can possibly know everything about their customers. Today, at least to my mind, it also conjures up a full-body scan X-ray, an image I hope enough people find so offensive that it will finally put the phrase to rest.
Sorry for the rant. My point is that database marketers’ ideal is a perfectly detailed customer database, which would allow them to target precisely the “right offer to the right customer at the right time.” This attitude leads to highly structured, finely segmented campaigns and carefully-plotted, rules-driven interaction flows which make the best possible use of whatever data is actually available.
Digital marketers have no such illusions about the completeness of the data they could ever hope to assemble. I’m not saying many of them wouldn’t like to identify each person they interact with, just that this is obviously impossible in most situations. Thus, digital marketers start from a premise that they’ll be interacting with people cloaked by varying degrees of anonymity, and look for ways to make the best use of the limited information available. In one case this might a search term they used to reach a Web site; in another it might be a history of movies they and others have rented; in yet another it might be their current physical location. Most innovations in digital marketing involve improving the value extracted from such limited data, rather than attempting to link the data to an identity that can then be enhanced with large volumes of personal information from other sources.
(Caveat: yes, there are some major efforts aimed precisely at providing digital marketers with individual identities. But these run up against both the fundamental difficulty of identifying people in most digital media. Even more important, their value is limited because immediate past data about behavior and context is usually more powerful at predicting immediate future behavior than static personal information from external sources.)
A corollary to the limited and contextual nature of most digital customer data is that marketing programs don’t have enough information to make reliable predictions about the most appropriate treatments. Thus, multi-step marketing campaigns or highly structured interaction dialogs are less useful than simply giving people a variety of choices and letting them guide the process for themselves. Again, this is a matter of degree: deciding which choices to present itself requires predictions about which items the customers will prefer. But presenting multiple choices is quite different from trying to guess in advance which one is best.
In other words, we’re talking about a loss of control over the marketing process. This is still more obvious at the start of the marketing cycle, when companies are first attracting customers into a relationship. Database marketers spend lots of effort acquiring and enhancing prospect lists so they can decide whom to approach and which offers to send them. By contrast, most digital marketing contacts are initiated by the prospects themselves in response to an advertisement or social media message. Certainly digital marketers can select their advertising audiences, but this resembles traditional media buying more than an outbound direct marketing campaign. Even (or, perhaps, especially) with social media interactions, the marketer has very little control over what is communicated to whom.
Indeed, even though database marketers do plenty of acquisition, I think it’s fair to say that they find it relatively frustrating because the available data is generally so limited. Most would probably prefer to work on customer management – cross sell, upsell and retention – where richer data is available. By contrast, digital marketers have happily embraced the notion of “inbound marketing”, which is precisely the art of attracting new people to their products. To speculate still further, the reason that business marketers are adopting marketing automation much more enthusiastically than they ever adopted traditional database marketing may be that business marketing automation is largely being used in acquisition-friendly digital media, and business marketers are more acquisition-oriented (i.e., focused on lead generation) than their consumer marketing brethren.
Control is also a major differentiator when it comes to marketing measurement. Perhaps the proudest claim of database marketers is that all their efforts are highly and precisely measurable. Reality is a bit more messy, but it’s true that database marketing does support proper champion/challenger testing for companies willing to make the investment. Digital marketing also supports such testing. But many digital efforts involve display advertising where at least some of the value comes from exposures that do not prompt immediate, measurable activity. This is another area where digital marketing more closely resembles traditional mass media advertising than anything else. In fact, digital marketers increasingly base their measurements on consumer panels and surveys, almost precisely duplicating the conventional mass media approach. Again, the fundamental point is a difference in attitude: database marketers treat precise measurement as their ideal, even though they realize it isn’t fully attainable. Digital marketing doesn’t permit that illusion, so its practitioners can more easily accept less exact approaches.
By now I’ve probably annoyed many of my friends in both the database and digital marketing industries. Let me make clear that I’m not arguing that database marketing is obsolete or somehow inferior to digital marketing. They do different things and will coexist, just as mass media survived when database marketing appeared. In fact, good marketers will learn to integrate them effectively, letting each do what it does best. Actually, I’d argue that rule- and data-driven Website personalization has more in common with classic database marketing than with most digital marketing methods. In that case, integration between the two types of marketing happens within the Web site itself.
Nor am I arguing that database and digital marketing have nothing in common. Both are, obviously, dependent on technology and both are measurable in their own ways. Both work with customer databases – in fact, as digital marketers get better at capturing and integrating customer data, they will find themselves increasingly reliant on database marketing techniques. And, of course, both ultimately perform the basic marketing tasks of understanding their customers and using that knowledge effectively.
Rather, I’m trying to show that different skills and assumptions are needed for success in the two areas, and to suggest that this makes it difficult for people and organizations to transition from one to the other. This, in my opinion, is why the direct marketing agencies, marketing service providers and marketing software vendors who dominate the database marketing industry have not transferred their leadership to the digital marketing channels. The only new medium they easily adopted was email, but that was essentially database marketing to begin with.
This doesn’t mean that database marketing vendors are inevitably doomed or trapped in a shrinking specialty. But it does mean that those firms must recognize the fundamental differences between their old industry and the new one. They cannot make the easy but false assumption that digital marketing is a natural extension of database marketing techniques. Only the marketers and vendors who aggressively embrace digital marketing in its own terms will be able to lead the new industry.
Yesterday’s post touched briefly on what I see as a fundamental transition between database marketing and digital marketing, and in particular on the changes that marketers and their supporting vendors must make to navigate the change successfully. This is an important topic, so I thought I’d return for a closer look.
It’s self-evident that digital marketing (mostly on the Internet, but also mobile, in-game, and eventually interactive TV) is a major change from both traditional mass media and more recent database marketing (mail, email, telemarketing, CRM). What’s less obvious is that the skills and attitudes that have served database marketers well for the past twenty or more years – an entire career for many – don’t transfer to the digital world. It’s true that database and digital marketing are both technology-enabled and thus seem as if they should draw on similar talents. But the similarities are superficial while the differences are profound.
Let’s cut to the core of the matter: the first rule of database marketing is that whoever has the biggest database, wins. Database marketers strive to gather ever-more information about their customers and (to a lesser extent, because less data is available) about their prospects. Their Holy Grail is the ever-receding “360 degree view of the customer,” a phrase I’ve always disliked because (a) it treats the customer as an object and (b) no one can possibly know everything about their customers. Today, at least to my mind, it also conjures up a full-body scan X-ray, an image I hope enough people find so offensive that it will finally put the phrase to rest.
Sorry for the rant. My point is that database marketers’ ideal is a perfectly detailed customer database, which would allow them to target precisely the “right offer to the right customer at the right time.” This attitude leads to highly structured, finely segmented campaigns and carefully-plotted, rules-driven interaction flows which make the best possible use of whatever data is actually available.
Digital marketers have no such illusions about the completeness of the data they could ever hope to assemble. I’m not saying many of them wouldn’t like to identify each person they interact with, just that this is obviously impossible in most situations. Thus, digital marketers start from a premise that they’ll be interacting with people cloaked by varying degrees of anonymity, and look for ways to make the best use of the limited information available. In one case this might a search term they used to reach a Web site; in another it might be a history of movies they and others have rented; in yet another it might be their current physical location. Most innovations in digital marketing involve improving the value extracted from such limited data, rather than attempting to link the data to an identity that can then be enhanced with large volumes of personal information from other sources.
(Caveat: yes, there are some major efforts aimed precisely at providing digital marketers with individual identities. But these run up against both the fundamental difficulty of identifying people in most digital media. Even more important, their value is limited because immediate past data about behavior and context is usually more powerful at predicting immediate future behavior than static personal information from external sources.)
A corollary to the limited and contextual nature of most digital customer data is that marketing programs don’t have enough information to make reliable predictions about the most appropriate treatments. Thus, multi-step marketing campaigns or highly structured interaction dialogs are less useful than simply giving people a variety of choices and letting them guide the process for themselves. Again, this is a matter of degree: deciding which choices to present itself requires predictions about which items the customers will prefer. But presenting multiple choices is quite different from trying to guess in advance which one is best.
In other words, we’re talking about a loss of control over the marketing process. This is still more obvious at the start of the marketing cycle, when companies are first attracting customers into a relationship. Database marketers spend lots of effort acquiring and enhancing prospect lists so they can decide whom to approach and which offers to send them. By contrast, most digital marketing contacts are initiated by the prospects themselves in response to an advertisement or social media message. Certainly digital marketers can select their advertising audiences, but this resembles traditional media buying more than an outbound direct marketing campaign. Even (or, perhaps, especially) with social media interactions, the marketer has very little control over what is communicated to whom.
Indeed, even though database marketers do plenty of acquisition, I think it’s fair to say that they find it relatively frustrating because the available data is generally so limited. Most would probably prefer to work on customer management – cross sell, upsell and retention – where richer data is available. By contrast, digital marketers have happily embraced the notion of “inbound marketing”, which is precisely the art of attracting new people to their products. To speculate still further, the reason that business marketers are adopting marketing automation much more enthusiastically than they ever adopted traditional database marketing may be that business marketing automation is largely being used in acquisition-friendly digital media, and business marketers are more acquisition-oriented (i.e., focused on lead generation) than their consumer marketing brethren.
Control is also a major differentiator when it comes to marketing measurement. Perhaps the proudest claim of database marketers is that all their efforts are highly and precisely measurable. Reality is a bit more messy, but it’s true that database marketing does support proper champion/challenger testing for companies willing to make the investment. Digital marketing also supports such testing. But many digital efforts involve display advertising where at least some of the value comes from exposures that do not prompt immediate, measurable activity. This is another area where digital marketing more closely resembles traditional mass media advertising than anything else. In fact, digital marketers increasingly base their measurements on consumer panels and surveys, almost precisely duplicating the conventional mass media approach. Again, the fundamental point is a difference in attitude: database marketers treat precise measurement as their ideal, even though they realize it isn’t fully attainable. Digital marketing doesn’t permit that illusion, so its practitioners can more easily accept less exact approaches.
By now I’ve probably annoyed many of my friends in both the database and digital marketing industries. Let me make clear that I’m not arguing that database marketing is obsolete or somehow inferior to digital marketing. They do different things and will coexist, just as mass media survived when database marketing appeared. In fact, good marketers will learn to integrate them effectively, letting each do what it does best. Actually, I’d argue that rule- and data-driven Website personalization has more in common with classic database marketing than with most digital marketing methods. In that case, integration between the two types of marketing happens within the Web site itself.
Nor am I arguing that database and digital marketing have nothing in common. Both are, obviously, dependent on technology and both are measurable in their own ways. Both work with customer databases – in fact, as digital marketers get better at capturing and integrating customer data, they will find themselves increasingly reliant on database marketing techniques. And, of course, both ultimately perform the basic marketing tasks of understanding their customers and using that knowledge effectively.
Rather, I’m trying to show that different skills and assumptions are needed for success in the two areas, and to suggest that this makes it difficult for people and organizations to transition from one to the other. This, in my opinion, is why the direct marketing agencies, marketing service providers and marketing software vendors who dominate the database marketing industry have not transferred their leadership to the digital marketing channels. The only new medium they easily adopted was email, but that was essentially database marketing to begin with.
This doesn’t mean that database marketing vendors are inevitably doomed or trapped in a shrinking specialty. But it does mean that those firms must recognize the fundamental differences between their old industry and the new one. They cannot make the easy but false assumption that digital marketing is a natural extension of database marketing techniques. Only the marketers and vendors who aggressively embrace digital marketing in its own terms will be able to lead the new industry.
Monday, February 01, 2010
Unica and Alterian Lead Database Marketers to the Digital Promised Land
Here are some quick thoughts on two items: Unica’s acquisition of paid search bid management system MakeMeTop (now mercifully renamed Unica Search) and Alterian’s recently-released and excellent annual marketing survey.
The connection is that these both support my feeling that many members of the old-line database marketing community have failed to adapt to the new world of digital marketing. I’ve been talking about this a lot with consulting clients but don’t think I’ve written about it at length in this blog.
The gist of the argument is that traditional direct marketing agencies, marketing automation software vendors and marketing services providers have mostly remained focused on outbound campaigns. They did move from direct mail to email, but those are pretty much the same thing. The really cool digital marketing stuff, including Web site development, Web advertising and most recently social media, has been executed by a different set of digital marketing agencies, specialist software vendors, and, ironically, media buyers at traditional ad agencies.
The fundamental reason is that the main skill of database marketers is building a customer database, while the core of digital marketing is responding to the behaviors of anonymous individuals. Of course I’m oversimplifying – much digital marketing does deal with people who have identified themselves – but there’s still a fundamental shift from targeting outbound campaigns at known individuals to managing interactions with anyone willing to engage.
Both Unica and Alterian have been exceptionally forward-thinking among marketing automation vendors in preparing for this transition. Unica’s latest acquisition is particularly interesting because search bid management has almost nothing to do with reaching known individuals. (I say “almost” only because Unica seems to intend to link search click-throughs to a traditional marketing database.) It follows Unica’s acquisition last month of email deliverability expert Pivotal Veracity, which I found less impressive because email is part of the old database marketing world.
Alterian has already made big bets in social media and Web content management, which are also well beyond the scope of traditional database marketing. Its survey provides strong support for the notion that marketers are “moving from a campaign-centric direct marketing model towards multi-channel customer engagement”: in fact, 51% said they were expending a fair or significant amount of effort on exactly that. Related factoids include:
- 61% of marketers do not integrate Web analytics with other customer data.
- 66% of respondents (which included quite a few agencies and marketing services providers, in addition to marketers) plan to invest in social media marketing in 2010
- 36% of respondents plan to invest in social media monitoring in 2010 (a discrepancy that Alterian finds “worrying”, although I’ve previously seen similar data. My take is that many marketers see social media as a way to generate business directly, and look at monitoring as a secondary aim.)
- 38% said coordinating digital and direct marketing agencies was somewhat or very difficult. No surprise there, although I don't necessarily agree with Alterian's contention that this will lead to a unification between the two sets of agencies.
- 35% of marketers expect to move more than 20% of their direct marketing budget into digital channels next year.
In short, the Alterian survey shows that marketers are eagerly moving from classic direct marketing to digital, interactive and social marketing, but still lack the skills and resources to do it effectively. Industry vendors who support them will thrive. Those who don't will quickly be left behind.
The connection is that these both support my feeling that many members of the old-line database marketing community have failed to adapt to the new world of digital marketing. I’ve been talking about this a lot with consulting clients but don’t think I’ve written about it at length in this blog.
The gist of the argument is that traditional direct marketing agencies, marketing automation software vendors and marketing services providers have mostly remained focused on outbound campaigns. They did move from direct mail to email, but those are pretty much the same thing. The really cool digital marketing stuff, including Web site development, Web advertising and most recently social media, has been executed by a different set of digital marketing agencies, specialist software vendors, and, ironically, media buyers at traditional ad agencies.
The fundamental reason is that the main skill of database marketers is building a customer database, while the core of digital marketing is responding to the behaviors of anonymous individuals. Of course I’m oversimplifying – much digital marketing does deal with people who have identified themselves – but there’s still a fundamental shift from targeting outbound campaigns at known individuals to managing interactions with anyone willing to engage.
Both Unica and Alterian have been exceptionally forward-thinking among marketing automation vendors in preparing for this transition. Unica’s latest acquisition is particularly interesting because search bid management has almost nothing to do with reaching known individuals. (I say “almost” only because Unica seems to intend to link search click-throughs to a traditional marketing database.) It follows Unica’s acquisition last month of email deliverability expert Pivotal Veracity, which I found less impressive because email is part of the old database marketing world.
Alterian has already made big bets in social media and Web content management, which are also well beyond the scope of traditional database marketing. Its survey provides strong support for the notion that marketers are “moving from a campaign-centric direct marketing model towards multi-channel customer engagement”: in fact, 51% said they were expending a fair or significant amount of effort on exactly that. Related factoids include:
- 61% of marketers do not integrate Web analytics with other customer data.
- 66% of respondents (which included quite a few agencies and marketing services providers, in addition to marketers) plan to invest in social media marketing in 2010
- 36% of respondents plan to invest in social media monitoring in 2010 (a discrepancy that Alterian finds “worrying”, although I’ve previously seen similar data. My take is that many marketers see social media as a way to generate business directly, and look at monitoring as a secondary aim.)
- 38% said coordinating digital and direct marketing agencies was somewhat or very difficult. No surprise there, although I don't necessarily agree with Alterian's contention that this will lead to a unification between the two sets of agencies.
- 35% of marketers expect to move more than 20% of their direct marketing budget into digital channels next year.
In short, the Alterian survey shows that marketers are eagerly moving from classic direct marketing to digital, interactive and social marketing, but still lack the skills and resources to do it effectively. Industry vendors who support them will thrive. Those who don't will quickly be left behind.
Sunday, January 31, 2010
Aprimo Marketing Studio Supports Sophisticated Business Marketers
Summary: Aprimo Marketing Studio offers powerful features in an on-demand system for sophisticated business and consumer marketers. You know who you are.
When I wrote about Aprimo Marketing Studio in a post last August, I was impressed by the scope of the product but reserved judgment because it hadn’t yet been launched. I took a look at the actual product last week. Bottom line: Aprimo delivered what they promised.
Like Aprimo itself, Marketing Studio is a bit of an oddity because it serves both business and consumer marketers. The needs of these two groups don’t necessarily conflict, but they do diverge. This means that a system for both will include several features needed by only one group or the other. Placing them all in the same product adds cost and complexity, which are not a software developer’s friends.
Aprimo has not found a magical solution to this dilemma. Rather, it has conceded the lower tiers of business marketing to simpler systems and aimed Marketing Studio at marketers who need greater sophistication and will accept higher cost and complexity to get it. (For more on vendor classifications, see my list of demand generation vendors from last November.)
In other words, Marketing Studio competes with high-end demand generation systems like Eloqua, Market2Lead and Neolane. Neolane may be the most similar, since it also straddles the business and consumer marketing worlds.
(Small digression: most business marketing systems are designed around data from a sales automation system such as Salesforce.com. But consumer marketers also need inputs from transaction systems. Marketing Studio and Neolane don't have a problem because they can support any data structure. Eloqua and Market2Lead are based on sales automation data, but can incorporate external tables. Other business marketing systems generally cannot.)
As I mentioned earlier, what originally most impressed me about Aprimo Marketing Studio was its scope. This starts with the core functions of any business marketing system: outbound and multi-step email campaigns, landing pages, Web behavior tracking , lead scoring, Salesforce.com integration, reporting and content management.
The system then draws on Aprimo’s heritage in marketing management to add detailed cost tracking, project management, asset workflow including annotation and commenting on PDFs, and a flexible campaign calendar. These are handled crudely, or not at all, in many business marketing products. In Marketing Studio, they are well-implemented with advanced features and an attractive, intuitive interface.
Project management is especially powerful. Project plans include specific tasks assigned to individuals and linked with dependencies. Plans can automatically modify themselves in response to events: for example, if a piece of copy is rejected, the system can add a new set of review and revision steps. This is done by creating the project as a branching flow chart, with rules to determine what takes place at junction. These rules can insert a predefined subflow, such as the review and revision process, which itself is shared across multiple projects. Good stuff.
System scope also extends to inbound marketing. Marketing Studio offers a blog engine tailored to corporate needs: managers can review and approve posts; the system can automatically notify Twitter, LinkedIn and Facebook of new post; and each blog topic is assigned a different URL, which helps with search engine rank. Another module lets marketers create Adobe Flash-based Web ads, while an offer manager module tracks the user of offers across promotions. Paid search campaigns are supported through integration with Omniture SearchCenter.
Of course, the bells and whistles wouldn’t matter if the core features were poor. But Marketing Studio handles these quite nicely as well.
Email campaigns can execute as batch projects or trigger dialogs. The system treats these separately, although they are built with the same drag-and-drop flowchart interface. Batch campaigns include powerful segmentation supported by a sophisticated query builder, splits and merges. Batch flows can also update data attributes, calculate lead scores, create personalized URLs, add and remove names from groups, send email and generate output lists for other media.
Trigger dialogs have most of the same capabilities except for the advanced segmentation. In addition, they support wait periods and can send leads and alerts to the sales system. Unlike many demand generation products, Marketing Studio supports circular and merging flows, which can simplify design of complicated programs.
People enter a campaign by being added to a group. This can happen when a list is imported from an external file or the sales automation system, when people submit a Web form or click on an email or page link, or as a step within a campaign flow. External systems can also add names through the Marketing Studio API. Because either type of campaign flow can itself add a name to a group, the possibilities for controlling campaign entry and movement across campaigns are basically unlimited. Trigger campaigns execute immediately when a new lead is added to their group, allowing real-time interactions.
Other core features are similarly powerful. Users can build HTML emails, Web pages and multi-page microsites. Emails and Web pages can dynamically select content blocks based on rules that read the attributes of each recipient. Web forms and surveys are also content blocks, so the same rule-based selections can manage branching surveys and progressive profiling (i.e., asking different questions based on what is already known about an individual). The same rule-building interface is used for content selection rules, segmentation queries, and lead scoring. This reduces the amount of user training.
Lead scoring supports multiple scores per person, which is typical in high-end demand generation systems. More impressively, Marketing Studio can also apply multiple rule-sets to the same score calculation. For example, it could use different rules for leads from different geographic regions.
The system can capture Web visitor behavior directly or integrate with Omniture SiteCatalyst. One advantage of using Aprimo’s own Web tracking is that results are available in immediately, compared to nightly with Omniture. Marketing Studio can identify the company of anonymous visitors based on their IP address and retain the history of anonymous visitors when they identify themselves by filling out a form.
Salespeole working with Salesforce.com can see a list of their leads with priority ratings. They can then click on a name to see a digital activity profile (emails sent, links clicked, forms completed, Web site visits). This profile can include activity captured within Marketing Studio or imported to the Marketing Studio database from other systems. Users can drill further into each profile to see the underlying details of each activity. Still within the Salesforce.com interface, salespeople can send an email through Marketing Studio, add a lead to a Marketing Studio campaign, and edit, convert, clone, dedupe or remove the lead record. If the administrator chooses, Salesforce.com users can also open a Marketing Studio portal to see the marketing calendar, assets, lead lists, activity requests, content reviews, project tasks and reports.
Speaking of reports: the system includes 150 standard reports, which users can customize or supplement by creating their own with a basic report writer.
Pricing of Marketing Studio is competitive with other high-end business marketing systems. Fees are based on a combination of database size, email activity, number of users and modules deployed. The starting level is about $4,000 per month, which includes the core marketing features for ten users and up to 100,000 contacts or 250,000 emails. Fees including hosting and email execution. The marketing operations module adds $2,500 per month and other modules such as social media, banner ads, Web analytics and Web alerts add $1,500 each.
Aprimo was founded in 1998 and has more than 200 clients on its original marketing system, which offers modules for marketing automation and marketing resource management. Marketing Studio was launched in September 2009 and at this writing has 22 clients, including a mix of business and consumer marketers.
When I wrote about Aprimo Marketing Studio in a post last August, I was impressed by the scope of the product but reserved judgment because it hadn’t yet been launched. I took a look at the actual product last week. Bottom line: Aprimo delivered what they promised.
Like Aprimo itself, Marketing Studio is a bit of an oddity because it serves both business and consumer marketers. The needs of these two groups don’t necessarily conflict, but they do diverge. This means that a system for both will include several features needed by only one group or the other. Placing them all in the same product adds cost and complexity, which are not a software developer’s friends.
Aprimo has not found a magical solution to this dilemma. Rather, it has conceded the lower tiers of business marketing to simpler systems and aimed Marketing Studio at marketers who need greater sophistication and will accept higher cost and complexity to get it. (For more on vendor classifications, see my list of demand generation vendors from last November.)
In other words, Marketing Studio competes with high-end demand generation systems like Eloqua, Market2Lead and Neolane. Neolane may be the most similar, since it also straddles the business and consumer marketing worlds.
(Small digression: most business marketing systems are designed around data from a sales automation system such as Salesforce.com. But consumer marketers also need inputs from transaction systems. Marketing Studio and Neolane don't have a problem because they can support any data structure. Eloqua and Market2Lead are based on sales automation data, but can incorporate external tables. Other business marketing systems generally cannot.)
As I mentioned earlier, what originally most impressed me about Aprimo Marketing Studio was its scope. This starts with the core functions of any business marketing system: outbound and multi-step email campaigns, landing pages, Web behavior tracking , lead scoring, Salesforce.com integration, reporting and content management.
The system then draws on Aprimo’s heritage in marketing management to add detailed cost tracking, project management, asset workflow including annotation and commenting on PDFs, and a flexible campaign calendar. These are handled crudely, or not at all, in many business marketing products. In Marketing Studio, they are well-implemented with advanced features and an attractive, intuitive interface.
Project management is especially powerful. Project plans include specific tasks assigned to individuals and linked with dependencies. Plans can automatically modify themselves in response to events: for example, if a piece of copy is rejected, the system can add a new set of review and revision steps. This is done by creating the project as a branching flow chart, with rules to determine what takes place at junction. These rules can insert a predefined subflow, such as the review and revision process, which itself is shared across multiple projects. Good stuff.
System scope also extends to inbound marketing. Marketing Studio offers a blog engine tailored to corporate needs: managers can review and approve posts; the system can automatically notify Twitter, LinkedIn and Facebook of new post; and each blog topic is assigned a different URL, which helps with search engine rank. Another module lets marketers create Adobe Flash-based Web ads, while an offer manager module tracks the user of offers across promotions. Paid search campaigns are supported through integration with Omniture SearchCenter.
Of course, the bells and whistles wouldn’t matter if the core features were poor. But Marketing Studio handles these quite nicely as well.
Email campaigns can execute as batch projects or trigger dialogs. The system treats these separately, although they are built with the same drag-and-drop flowchart interface. Batch campaigns include powerful segmentation supported by a sophisticated query builder, splits and merges. Batch flows can also update data attributes, calculate lead scores, create personalized URLs, add and remove names from groups, send email and generate output lists for other media.
Trigger dialogs have most of the same capabilities except for the advanced segmentation. In addition, they support wait periods and can send leads and alerts to the sales system. Unlike many demand generation products, Marketing Studio supports circular and merging flows, which can simplify design of complicated programs.
People enter a campaign by being added to a group. This can happen when a list is imported from an external file or the sales automation system, when people submit a Web form or click on an email or page link, or as a step within a campaign flow. External systems can also add names through the Marketing Studio API. Because either type of campaign flow can itself add a name to a group, the possibilities for controlling campaign entry and movement across campaigns are basically unlimited. Trigger campaigns execute immediately when a new lead is added to their group, allowing real-time interactions.
Other core features are similarly powerful. Users can build HTML emails, Web pages and multi-page microsites. Emails and Web pages can dynamically select content blocks based on rules that read the attributes of each recipient. Web forms and surveys are also content blocks, so the same rule-based selections can manage branching surveys and progressive profiling (i.e., asking different questions based on what is already known about an individual). The same rule-building interface is used for content selection rules, segmentation queries, and lead scoring. This reduces the amount of user training.
Lead scoring supports multiple scores per person, which is typical in high-end demand generation systems. More impressively, Marketing Studio can also apply multiple rule-sets to the same score calculation. For example, it could use different rules for leads from different geographic regions.
The system can capture Web visitor behavior directly or integrate with Omniture SiteCatalyst. One advantage of using Aprimo’s own Web tracking is that results are available in immediately, compared to nightly with Omniture. Marketing Studio can identify the company of anonymous visitors based on their IP address and retain the history of anonymous visitors when they identify themselves by filling out a form.
Salespeole working with Salesforce.com can see a list of their leads with priority ratings. They can then click on a name to see a digital activity profile (emails sent, links clicked, forms completed, Web site visits). This profile can include activity captured within Marketing Studio or imported to the Marketing Studio database from other systems. Users can drill further into each profile to see the underlying details of each activity. Still within the Salesforce.com interface, salespeople can send an email through Marketing Studio, add a lead to a Marketing Studio campaign, and edit, convert, clone, dedupe or remove the lead record. If the administrator chooses, Salesforce.com users can also open a Marketing Studio portal to see the marketing calendar, assets, lead lists, activity requests, content reviews, project tasks and reports.
Speaking of reports: the system includes 150 standard reports, which users can customize or supplement by creating their own with a basic report writer.
Pricing of Marketing Studio is competitive with other high-end business marketing systems. Fees are based on a combination of database size, email activity, number of users and modules deployed. The starting level is about $4,000 per month, which includes the core marketing features for ten users and up to 100,000 contacts or 250,000 emails. Fees including hosting and email execution. The marketing operations module adds $2,500 per month and other modules such as social media, banner ads, Web analytics and Web alerts add $1,500 each.
Aprimo was founded in 1998 and has more than 200 clients on its original marketing system, which offers modules for marketing automation and marketing resource management. Marketing Studio was launched in September 2009 and at this writing has 22 clients, including a mix of business and consumer marketers.
Thursday, January 21, 2010
Kynetx Lets Marketers Customize User Experience Across Web Sites
Summary: Kynetx lets marketers enhance and coordinate user experience across multiple Web sites. It’s so different from site-based Web personalization that the possibilities can be hard to grasp. But I think they’re substantial.
The classic view of online anonymity is the 1993 New Yorker cartoon, “On the Internet, nobody knows you’re a dog.” Today, we realize that our online identities are not as private as they then seemed. But from a marketer’s viewpoint, it’s still maddeningly difficult to recognize online visitors and interact with them as individuals.
The challenge is usually focused on the marketer’s own Web site: when people visit, how can I identify them? But, ideally, marketers would track their customers across all Web sites and interject themselves when appropriate. Ad networks already do this to some extent, using third party cookies to coordinate the messages shown to each individual on different sites. But this doesn’t help marketers who want an active role in managing the user’s experience.
Kynetx offers a more powerful alternative. It installs a browser extension that can send data to an externally-hosted rules engine which returns JavaScript snippets that enhance the current Web page. The data describes the rules to execute and the current context, such as the Web page being viewed. It could potentially include personal information the user has chosen to share, although current Kynetx applications do not.
A concrete example would surely help. One Kynetx application is downloaded by members of the AAA automobile club. When users do a search on Google or other major sites, the application calls the Kynetx rules engine which checks a list of vendors who offer AAA discounts and flags them within the search results. No personal data is shared, yet AAA’s marketers deliver a customized experience that reminds members of their benefits and supports AAA’s partners.
Kynetx applications can also move data from one Web site to another, for example by capturing data and using it fill in a form or execute an API call.
The underlying technology for most Kynetx applications includes “Information Cards”, an open standard for digital identity management supported by Microsoft, Oracle, Google, PayPal and others. The general idea is that people can have different “cards” with different information for different purposes, allowing them to control (and, presumably, minimize) the amount of information they provide in each context. See the Information Card Foundation Web site for details.
In the case of Kynetx, Information Cards also minimize user effort, since the Kynetx browser extension must be installed only once, and then new applications can be added simply by loading a new Information Card. All the heavy lifting is done by the Kynetx rules engine, which resides on a central server accessed over the Internet. In addition to reducing the burden on the user’s computer, this makes updates easy since any changes are made on the server and go into effect without being deployed to user systems.
Development effort is further reduced because each Kynetx application runs on major browsers and operating systems without customization. Rules are written in a Kynetx-developed language with special features for context management. I was particularly pleased to see support for A/B tests, including facilities to randomly select different actions, capture success or failure, and report on results. Applications can run on personal computers, smartphones, or any other Web-enabled device.
Marketers who don’t want to use Information Cards can distribute applications through other “endpoints” including browser toolbars, cookies, wireless proxy servers (for example, in a coffee shop), or bookmarklets http://en.wikipedia.org/wiki/Bookmarklet . All that’s required is something that can identify a user, capture permissions, and call the Kynetx server.
Kynetx was founded in 2007 and currently is used in more than 700 applications from about 250 developers. Although the company does some application development, its primary business is selling execution on its platform, at rates from $.24 to $1.60 per thousand ruleset evaluations.
I’m frankly intrigued by the possibilities of Kynetx, which seems to open a direct channel onto users’ desktops, bypassing traditional Web advertising. It does require a preexisting relationship with the user, but gaining user permission is fast becoming a condition for most online interactions. Kynetx makes it easier to gain this permission by offering something of value in return. Even more important, it should help marketers to strengthen existing relationships by repeatedly demonstrating value after an application is installed.
The classic view of online anonymity is the 1993 New Yorker cartoon, “On the Internet, nobody knows you’re a dog.” Today, we realize that our online identities are not as private as they then seemed. But from a marketer’s viewpoint, it’s still maddeningly difficult to recognize online visitors and interact with them as individuals.The challenge is usually focused on the marketer’s own Web site: when people visit, how can I identify them? But, ideally, marketers would track their customers across all Web sites and interject themselves when appropriate. Ad networks already do this to some extent, using third party cookies to coordinate the messages shown to each individual on different sites. But this doesn’t help marketers who want an active role in managing the user’s experience.
Kynetx offers a more powerful alternative. It installs a browser extension that can send data to an externally-hosted rules engine which returns JavaScript snippets that enhance the current Web page. The data describes the rules to execute and the current context, such as the Web page being viewed. It could potentially include personal information the user has chosen to share, although current Kynetx applications do not.
A concrete example would surely help. One Kynetx application is downloaded by members of the AAA automobile club. When users do a search on Google or other major sites, the application calls the Kynetx rules engine which checks a list of vendors who offer AAA discounts and flags them within the search results. No personal data is shared, yet AAA’s marketers deliver a customized experience that reminds members of their benefits and supports AAA’s partners.
Kynetx applications can also move data from one Web site to another, for example by capturing data and using it fill in a form or execute an API call.
The underlying technology for most Kynetx applications includes “Information Cards”, an open standard for digital identity management supported by Microsoft, Oracle, Google, PayPal and others. The general idea is that people can have different “cards” with different information for different purposes, allowing them to control (and, presumably, minimize) the amount of information they provide in each context. See the Information Card Foundation Web site for details.
In the case of Kynetx, Information Cards also minimize user effort, since the Kynetx browser extension must be installed only once, and then new applications can be added simply by loading a new Information Card. All the heavy lifting is done by the Kynetx rules engine, which resides on a central server accessed over the Internet. In addition to reducing the burden on the user’s computer, this makes updates easy since any changes are made on the server and go into effect without being deployed to user systems.
Development effort is further reduced because each Kynetx application runs on major browsers and operating systems without customization. Rules are written in a Kynetx-developed language with special features for context management. I was particularly pleased to see support for A/B tests, including facilities to randomly select different actions, capture success or failure, and report on results. Applications can run on personal computers, smartphones, or any other Web-enabled device.
Marketers who don’t want to use Information Cards can distribute applications through other “endpoints” including browser toolbars, cookies, wireless proxy servers (for example, in a coffee shop), or bookmarklets http://en.wikipedia.org/wiki/Bookmarklet . All that’s required is something that can identify a user, capture permissions, and call the Kynetx server.
Kynetx was founded in 2007 and currently is used in more than 700 applications from about 250 developers. Although the company does some application development, its primary business is selling execution on its platform, at rates from $.24 to $1.60 per thousand ruleset evaluations.
I’m frankly intrigued by the possibilities of Kynetx, which seems to open a direct channel onto users’ desktops, bypassing traditional Web advertising. It does require a preexisting relationship with the user, but gaining user permission is fast becoming a condition for most online interactions. Kynetx makes it easier to gain this permission by offering something of value in return. Even more important, it should help marketers to strengthen existing relationships by repeatedly demonstrating value after an application is installed.
Friday, January 15, 2010
Autonomy Promises to Automate Delivery of Tailored Marketing Messages
Summary: Autonomy is a leader in enterprise search and content management (it owns Interwoven). Its concept of "Meaning Based Marketing" comes quite close to my idea of "content grazing" as a way to reduce marketing complexity while delivering the right content to each customer or prospect.
In my last post, I proposed the (somewhat tongue-in-cheek) term of “content grazing” to describe automatically extracting small bits of information from company documents and feeding them to prospects and customers. The notion had been on my mind for some time, prompted by a sense that traditional approaches to content creation and distribution are fundamentally too expensive to deploy in full. That is, tailoring large content streams for buyer segments and funnel stages is just too much work for both marketers (who can't afford to create the content and campaigns) and buyers (who don’t have time to read the results).
The good folks at Autonomy apparently had similar thoughts. Back in July 2009 they published a paper Meaning Based Marketing that describes using a collection of Autonomy technologies “to truly understand your customers—drawing on everything from transaction history to cross-channel interactions, user generated content, customer and community behavior, as well as third party content—and act on that knowledge to deliver the best performing, most accurate, and relevant content to each individual visitor. Automatically.” That pretty much says it all.
The Autonomy brief has a slightly different scope from my own concept, perhaps because it’s tailored to fit the Autonomy product portfolio. For example, it includes Web content archiving, which I wouldn’t have considered, and excludes creating content from relevant pieces within a larger document. I do consider the latter quite important, because it’s a key to reducing the content creation cost and in making the information more digestible for customers. But the core components of meaning extraction and self-adjusting content selection are certainly present in Autonomy's description.
Specifically, the paper outlines a fully automated process of:
- delivering a tailored customer experience (that is, content recommendations) based on its understanding of both the customer and the contents
- optimizing interactions through real-time multivariate testing
The list also includes market analysis, based on sentiments and trends, as well as the previously-mentioned content archiving. Both are useful additions to the vision.
The paper doesn’t go into much technical detail beyong mentioning that Autonomy unifies the data through its “Intelligent Data Operating Layer” (IDOL). But I suspect you could find much more information elsewhere on their site: Autonomy itself doesn’t seem to be conserving its content-creation budget.
Nor, come to think of it, did I notice any particular personalization or intelligent targeting on my own return visits to their Web site. Either they’re very good at this stuff – and know I’m not a real sales prospect – or they haven’t quite gotten around to deploying these services for themselves. Either way, the concept remains valid and it’s good to see that someone is working to make it happen.
In my last post, I proposed the (somewhat tongue-in-cheek) term of “content grazing” to describe automatically extracting small bits of information from company documents and feeding them to prospects and customers. The notion had been on my mind for some time, prompted by a sense that traditional approaches to content creation and distribution are fundamentally too expensive to deploy in full. That is, tailoring large content streams for buyer segments and funnel stages is just too much work for both marketers (who can't afford to create the content and campaigns) and buyers (who don’t have time to read the results).
The good folks at Autonomy apparently had similar thoughts. Back in July 2009 they published a paper Meaning Based Marketing that describes using a collection of Autonomy technologies “to truly understand your customers—drawing on everything from transaction history to cross-channel interactions, user generated content, customer and community behavior, as well as third party content—and act on that knowledge to deliver the best performing, most accurate, and relevant content to each individual visitor. Automatically.” That pretty much says it all.
The Autonomy brief has a slightly different scope from my own concept, perhaps because it’s tailored to fit the Autonomy product portfolio. For example, it includes Web content archiving, which I wouldn’t have considered, and excludes creating content from relevant pieces within a larger document. I do consider the latter quite important, because it’s a key to reducing the content creation cost and in making the information more digestible for customers. But the core components of meaning extraction and self-adjusting content selection are certainly present in Autonomy's description.
Specifically, the paper outlines a fully automated process of:
- analyzing unstructured content to infer the views, needs and preferences of customers who create or read it
- generating customer profiles based on the contents and associated behaviors
- uncovering customer segments within the data- delivering a tailored customer experience (that is, content recommendations) based on its understanding of both the customer and the contents
- optimizing interactions through real-time multivariate testing
The list also includes market analysis, based on sentiments and trends, as well as the previously-mentioned content archiving. Both are useful additions to the vision.
The paper doesn’t go into much technical detail beyong mentioning that Autonomy unifies the data through its “Intelligent Data Operating Layer” (IDOL). But I suspect you could find much more information elsewhere on their site: Autonomy itself doesn’t seem to be conserving its content-creation budget.
Nor, come to think of it, did I notice any particular personalization or intelligent targeting on my own return visits to their Web site. Either they’re very good at this stuff – and know I’m not a real sales prospect – or they haven’t quite gotten around to deploying these services for themselves. Either way, the concept remains valid and it’s good to see that someone is working to make it happen.
Thursday, January 07, 2010
2010 Will Bring New Features to Demand Generation Systems
Summary: the demand generation market will continue to grow in 2010, and it may attract some new, big competitors from outside the industry. But the real excitement will be features that expand the scope of demand generation products to support inbound marketing, better measurement, and more efficient content creation.
2009 was a year of tremendous growth for demand generation systems (a.k.a. business-to-business marketing automation. By some measures, it's looking more mature: buyers are appearing outside the initial niche of software and technology companies; core functionality is well understood and largely consistent across products; vendors are expanding scope to include new users at existing accounts (in particular, sales departments); pricing is under pressure; and companies are starting to specialize in different customer segments.
On the other hand, there are still plenty of new entrants; few pioneering vendors have failed or consolidated; and related software vendors (in this case, CRM, email and Web site management systems) haven’t yet introduced me-too products. Perhaps most important, many potential buyers still don’t understand the value provided by these systems—although vendors are working very hard to educate them. So, on balance, I'd say the industry is still in a fairly early stage: late adolescence, if you will.
What will 2010 bring? Continued sales growth, for sure: that’s easy enough when you’re starting with a small base. We can also be confident that the feature trends I described in my review of 2009 will continue: better support for social media, greater access for sales departments, and more flexible reporting. I do expect vendors to converge on more standard social media features. These will probably combine the content-sharing and activity-tracking capabilities that different vendors now deliver separately.
There’s also a reasonable chance – although this prediction is less certain – that sales access features will blossom into deeper cooperation between marketing and sales in managing prospect relationships. There's no question in my mind that such cooperation will appear: it's inevitable as marketing’s role expands beyond lead generation to long-term relationship management. What I don’t know is how quickly this will happen or whether the sales access tools will be the connection point. One reason they might not is that sales access tools are used by individual sales people, while broad marketing and sales integration is likely to be controlled by senior sales management.
So much for the rear view mirror. Here are some predictions that are larger departures from the immediate past.
- me-too products. It's just a matter of time before CRM vendors (yes, I mean Salesforce.com) and Web content management vendors decide to compete seriously for marketing automation business. Frankly, this is so obvious that I'm almost embarrassed to mention it. But I wouldn't want anyone to say I failed to see it coming.
- inbound marketing. The work of generating Web traffic through search engine optimization, paid Web ads and expanded Web content has so far been performed outside of most demand generation systems. These are important marketing activities and they are a natural extension of demand generation systems, even though they require closer integration with (or replacement of ) Web content management and Web analytics. Note that Webinars and social media, which are also inbound marketing devices, are already being added to marketing automation products.
This type of extension—supporting new tasks for current users—is typical of maturing products once the core functions widely available. It also implies that vendors specializing in these areas will add their own marketing automation features to compete. HubSpot particularly comes to mind, which is a testament to their own marketing skills.
- external data. Many demand generation systems already make it easy to look up data about prospects from sources like Hoovers or JigSaw and to infer the location and company of anonymous visitors from their IP address. Certainly those features will continue to grow. But there’s another trend that's very pronounced in the consumer marketing space, which is using consumer panels and surveys to measure responses that aren’t captured within the company’s own systems. I haven’t seen much analogous activity among business marketers, but think that will change as the technique becomes more common and as business marketers accept that internal data will never provide all the answers they really need for effective marketing measurement. The task for the marketing automation vendors is making it easier to integrate such data and, in cases such as ad-embedded surveys, to generate it.
- content grazing. I'll explain that label in a moment. The idea is to squeeze the most value from existing marketing content, rather than creating new content for each project and situation. This implies two complementary tasks: being able to extract and classify nuggets of information from existing marketing documents, and being able to deliver exactly the right nugget in each situation.
The underlying insight is that there’s so much information available today that people don’t have time to digest large blocks of it. Rather, they want be fed bite-sized chunks that meet their immediate needs. Hence, the term "content grazing": it's like eating appetizers instead of a full meal.
Today’s marketing best practice is the opposite of content grazing: it’s to develop many different campaigns that deliver large volumes of content for different situations. This is expensive and it's exactly what prospects don't want. The alternative is automated systems that extract and classify content from existing materials, including many such as blog posts that would be created for other purposes. Other automated systems would can select and deliver the correct content during each interaction.
Basically this is the challenge of simulating a human conversation. It’s possible that some solutions will be based on automated customer service agents already used for other interactions. I haven’t seen this applied in a marketing automation context, but suspect it’s a path that marketers will be forced to explore as they recognize the full cost of conventional content-heavy approaches, and that buyers don't want them anyway.
2009 was a year of tremendous growth for demand generation systems (a.k.a. business-to-business marketing automation. By some measures, it's looking more mature: buyers are appearing outside the initial niche of software and technology companies; core functionality is well understood and largely consistent across products; vendors are expanding scope to include new users at existing accounts (in particular, sales departments); pricing is under pressure; and companies are starting to specialize in different customer segments.
On the other hand, there are still plenty of new entrants; few pioneering vendors have failed or consolidated; and related software vendors (in this case, CRM, email and Web site management systems) haven’t yet introduced me-too products. Perhaps most important, many potential buyers still don’t understand the value provided by these systems—although vendors are working very hard to educate them. So, on balance, I'd say the industry is still in a fairly early stage: late adolescence, if you will.
What will 2010 bring? Continued sales growth, for sure: that’s easy enough when you’re starting with a small base. We can also be confident that the feature trends I described in my review of 2009 will continue: better support for social media, greater access for sales departments, and more flexible reporting. I do expect vendors to converge on more standard social media features. These will probably combine the content-sharing and activity-tracking capabilities that different vendors now deliver separately.
There’s also a reasonable chance – although this prediction is less certain – that sales access features will blossom into deeper cooperation between marketing and sales in managing prospect relationships. There's no question in my mind that such cooperation will appear: it's inevitable as marketing’s role expands beyond lead generation to long-term relationship management. What I don’t know is how quickly this will happen or whether the sales access tools will be the connection point. One reason they might not is that sales access tools are used by individual sales people, while broad marketing and sales integration is likely to be controlled by senior sales management.
So much for the rear view mirror. Here are some predictions that are larger departures from the immediate past.
- me-too products. It's just a matter of time before CRM vendors (yes, I mean Salesforce.com) and Web content management vendors decide to compete seriously for marketing automation business. Frankly, this is so obvious that I'm almost embarrassed to mention it. But I wouldn't want anyone to say I failed to see it coming.
- inbound marketing. The work of generating Web traffic through search engine optimization, paid Web ads and expanded Web content has so far been performed outside of most demand generation systems. These are important marketing activities and they are a natural extension of demand generation systems, even though they require closer integration with (or replacement of ) Web content management and Web analytics. Note that Webinars and social media, which are also inbound marketing devices, are already being added to marketing automation products.
This type of extension—supporting new tasks for current users—is typical of maturing products once the core functions widely available. It also implies that vendors specializing in these areas will add their own marketing automation features to compete. HubSpot particularly comes to mind, which is a testament to their own marketing skills.
- external data. Many demand generation systems already make it easy to look up data about prospects from sources like Hoovers or JigSaw and to infer the location and company of anonymous visitors from their IP address. Certainly those features will continue to grow. But there’s another trend that's very pronounced in the consumer marketing space, which is using consumer panels and surveys to measure responses that aren’t captured within the company’s own systems. I haven’t seen much analogous activity among business marketers, but think that will change as the technique becomes more common and as business marketers accept that internal data will never provide all the answers they really need for effective marketing measurement. The task for the marketing automation vendors is making it easier to integrate such data and, in cases such as ad-embedded surveys, to generate it.
- content grazing. I'll explain that label in a moment. The idea is to squeeze the most value from existing marketing content, rather than creating new content for each project and situation. This implies two complementary tasks: being able to extract and classify nuggets of information from existing marketing documents, and being able to deliver exactly the right nugget in each situation.
The underlying insight is that there’s so much information available today that people don’t have time to digest large blocks of it. Rather, they want be fed bite-sized chunks that meet their immediate needs. Hence, the term "content grazing": it's like eating appetizers instead of a full meal.
Today’s marketing best practice is the opposite of content grazing: it’s to develop many different campaigns that deliver large volumes of content for different situations. This is expensive and it's exactly what prospects don't want. The alternative is automated systems that extract and classify content from existing materials, including many such as blog posts that would be created for other purposes. Other automated systems would can select and deliver the correct content during each interaction.
Basically this is the challenge of simulating a human conversation. It’s possible that some solutions will be based on automated customer service agents already used for other interactions. I haven’t seen this applied in a marketing automation context, but suspect it’s a path that marketers will be forced to explore as they recognize the full cost of conventional content-heavy approaches, and that buyers don't want them anyway.
Tuesday, January 05, 2010
Marketing Automation System Trends: What We Found in the Raab Guide
Summary: Social media and access for sales people were the two big trends among demand generation vendors last year. But enhanced reporting was the most common improvement of all. Could marketers finally be ready to spend on measurement?
I’m pleased to report that the 2010 edition of the Raab Guide to Demand Generation Systems is officially available today, with updated entries on all vendors (alphabetically: Eloqua, Manticore Technology, Market2Lead, Marketbright, Marketo, Neolane and Silverpop Engage B2B).
Preparing the updates gave me a good review of where developers focused their efforts last year. Even though this is limited to the vendors in the Guide, it's a pretty representative sample of the industry as a whole. Here’s a quick look at what I found.
- Social media. At least three vendors (Eloqua, Marketo and Silverpop) introduced new features aimed at improving marketers’ ability to use social media. What’s most interesting is that no standard approach has yet emerged. Eloqua focused on making it easier to embed sharable links within conventional marketing assets. Marketo added features to capture Twitter posts and Helpstream customer support interactions within a lead’s activity history. Silverpop made it easier to add social media handles to lead records so these could be used to send messages.
- Sales access. The same three vendors also added new tools to give salespeople better access to information the marketing automation system has captured about their leads. But in contrast to social media applications, the sales access modules were remarkably similar. All aimed at showing the activities of selected leads, typically by showing overviews and trends, and then letting users drill into details. The vendors also charged additional per-user fees for these modules. This contrasts with traditional demand generation pricing on database size and/or activity volume, but is the way sales automation systems like Salesforce.com are usually sold. These modules open up a major new revenue stream for the demand generation systems while simultaneously giving sales departments a greater reason to support marketing's purchase of the systems. Even though the modules clearly trespasses on the CRM vendors turf – inviting a potentially devastating counter-invasion – the opportunity seems irresistible.
- Upgraded reporting. You already knew that vendors were adding features for social media and sales access, but did you realize that nearly everyone (five of my seven vendors: Eloqua, Market2Lead, Marketo, Manticore Technology and Marketbright) also made substantial improvements in their business intelligence and reporting capabilities? Popular new features included user-customizable dashboards, better user-defined reports and more extensive standard reports. I take this as evidence that marketers are demanding more sophisticated reporting from their vendors, and suspect further improvements are on the way.
- New user interfaces. Market2Lead, Manticore Technology and Silverpop all introduced major interface upgrades. The focus was less on adding new capabilities than on making existing functions more accessible. I don’t need to remind you that usability is a critical point of competition among industry vendors. But as older vendors revamp their interfaces, it will become harder for buyers to differentiate along those lines. This might lead vendors to highlight the structural differences in their campaign engines, which are ultimately more important for usability than the visual interface. But, the structural issues are much harder for buyers to grasp, so this might not be an effective marketing approach. Could this lead vendors to compete on other grounds entirely?
- Anonymous user look-up and data enhancement. At least three vendors added or enhanced features to use IP address to identify the company of anonymous Web visitors, and/or to look up prospect names and other data about those companies in directories such as Jigsaw and Hoovers. I won’t name those three because the other vendors may have similar capabilities. In fact, anonymous visitor identification and enhancement have become pretty much standard features: today, it would be an exceptional vendor who did NOT make them available. These features also tie into both social media and sales access modules. They illustrate how the role of marketing has changed from simply gathering leads and handing them to sales, to building and managing prospect relationships.
So much for 2009. Many of these trends will surely continue in 2010, but I think we can expect some new directions as well. I'll talk about those in my next post.
I’m pleased to report that the 2010 edition of the Raab Guide to Demand Generation Systems is officially available today, with updated entries on all vendors (alphabetically: Eloqua, Manticore Technology, Market2Lead, Marketbright, Marketo, Neolane and Silverpop Engage B2B).
Preparing the updates gave me a good review of where developers focused their efforts last year. Even though this is limited to the vendors in the Guide, it's a pretty representative sample of the industry as a whole. Here’s a quick look at what I found.
- Social media. At least three vendors (Eloqua, Marketo and Silverpop) introduced new features aimed at improving marketers’ ability to use social media. What’s most interesting is that no standard approach has yet emerged. Eloqua focused on making it easier to embed sharable links within conventional marketing assets. Marketo added features to capture Twitter posts and Helpstream customer support interactions within a lead’s activity history. Silverpop made it easier to add social media handles to lead records so these could be used to send messages.
- Sales access. The same three vendors also added new tools to give salespeople better access to information the marketing automation system has captured about their leads. But in contrast to social media applications, the sales access modules were remarkably similar. All aimed at showing the activities of selected leads, typically by showing overviews and trends, and then letting users drill into details. The vendors also charged additional per-user fees for these modules. This contrasts with traditional demand generation pricing on database size and/or activity volume, but is the way sales automation systems like Salesforce.com are usually sold. These modules open up a major new revenue stream for the demand generation systems while simultaneously giving sales departments a greater reason to support marketing's purchase of the systems. Even though the modules clearly trespasses on the CRM vendors turf – inviting a potentially devastating counter-invasion – the opportunity seems irresistible.
- Upgraded reporting. You already knew that vendors were adding features for social media and sales access, but did you realize that nearly everyone (five of my seven vendors: Eloqua, Market2Lead, Marketo, Manticore Technology and Marketbright) also made substantial improvements in their business intelligence and reporting capabilities? Popular new features included user-customizable dashboards, better user-defined reports and more extensive standard reports. I take this as evidence that marketers are demanding more sophisticated reporting from their vendors, and suspect further improvements are on the way.
- New user interfaces. Market2Lead, Manticore Technology and Silverpop all introduced major interface upgrades. The focus was less on adding new capabilities than on making existing functions more accessible. I don’t need to remind you that usability is a critical point of competition among industry vendors. But as older vendors revamp their interfaces, it will become harder for buyers to differentiate along those lines. This might lead vendors to highlight the structural differences in their campaign engines, which are ultimately more important for usability than the visual interface. But, the structural issues are much harder for buyers to grasp, so this might not be an effective marketing approach. Could this lead vendors to compete on other grounds entirely?
- Anonymous user look-up and data enhancement. At least three vendors added or enhanced features to use IP address to identify the company of anonymous Web visitors, and/or to look up prospect names and other data about those companies in directories such as Jigsaw and Hoovers. I won’t name those three because the other vendors may have similar capabilities. In fact, anonymous visitor identification and enhancement have become pretty much standard features: today, it would be an exceptional vendor who did NOT make them available. These features also tie into both social media and sales access modules. They illustrate how the role of marketing has changed from simply gathering leads and handing them to sales, to building and managing prospect relationships.
So much for 2009. Many of these trends will surely continue in 2010, but I think we can expect some new directions as well. I'll talk about those in my next post.
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