You probably saw ExactTarget’s June 13 announcement of its strategic partnership with Marketo and Eloqua’s June 21 announcement of its new AppCloud marketplace for connectors with other systems. So did I. But it took a little while to connect with the vendors to get the details, so I’m only now ready to write about them.
Both announcements shared a theme of integration between core marketing platforms and other marketing systems. That Eloqua sees itself as the center of a marketing infrastructure isn’t surprising, although it does show how far we've traveled from the once-common view of marketing automation as an auxiliary to the sales automation “system of record”. ExactTarget’s aspiration to a central role was less expected, since its original and still primary business is email delivery. But ExactTarget has added mobile, Web pages, and social in recent years. They've been pulling these together with an “Interactive Marketing Hub” in beta since last September, which is now used by 500 of their 4,000 clients. The IMH, as we cognoscenti call it, combines ExactTarget's email, mobile, Web pages, Web visitor tracking, and social media with external touchpoints as well as Salesforce.com and Microsoft CRM.
The IMH sports a slick user interface with a very nice dashboard showing real-time updates of summary statistics for each channel. It also provides a central marketing calendar of campaigns across the channels. The underlying database can be simple lists, as in traditional email system, or a proper multi-table structure acting as the primary marketing database. As Captain Planet used to say, The Power Is Yours.
It’s perfectly sensible for ExactTarget to move in this direction, since it otherwise risks being pushed to the unprofitable edges of the marketing world as a commodity email engine. In fact, the real head-scratcher was why ExactTarget would deal with Marketo if it had ambitions to occupy the same central turf. (Marketo’s motivation is obvious: to gain broader distribution.)
ExactTarget’s answer was refreshingly honest: IMH lacks key B2B marketing automation features including lead scoring, advanced segmentation, and multi-step campaigns. The campaign engine will be improved before IMH's official launch this September, but other specialized B2B features probably won’t be added. ExactTarget also sees Marketo as the first of many partner applications for IMH, further clarifying that they see it in the central position.
Eloqua’s AppCloud is obviously modeled on Salesforce.com’s AppExchange and other application stores. The goal is for third parties to extend the value of a core platform by building tools that enhance it. In Eloqua’s case, most of the initial applications are connectors with other systems for Webinars, social communities, messaging and data acquisition. These will be joined over time by apps that add functionality within Eloqua itself. The AppCloud is an extension of Eloqua’s earlier Cloud Connector initiative, which provides APIs for external systems to access Eloqua data and functions. Basically, AppCloud makes it easier to find and deploy those connectors.
I did ask Eloqua how AppCloud relates to its Revenue Performance Management positioning. This felt like a pretty clever question until I later saw it was addressed in the AppCloud press release. Oh well. The answer came smoothly enough: AppCloud makes it easier to gather the activity data needed for Revenue Performance Management analysis. That makes sense, although AppCloud implies a more active integration with external systems than simply reporting against them.
Both the ExactTarget and Eloqua announcements reflect a strategy of positioning their products as a company’s primary customer management system. If you recall my post last week on Adobe and Oracle announcements, those firms also wanted to place themselves at the center of the customer management universe. So does pretty much everyone else.
Obviously they all can’t win this game. At the end of the day, I’d still put my money on the big CRM systems as the logical central repository for customer data. But I do believe that many auxiliary systems will continue to feed data to the central system and somehow coordinate treatment decisions with it. Connectors created to service ExactTarget, Eloqua, and others will make it easier to integrate the peripheral systems with whichever product ends up in the middle. So it’s all good.
Mittwoch, Juni 29, 2011
Mittwoch, Juni 22, 2011
Dueling Strategies: Adobe and Oracle Take Opposite Paths to Customer Experience Management
Adobe on Monday announced a new “Digital Enterprise Platform for Customer Experience Management”. The platform fills the center of Adobe’s three-part corporate mission to “make, manage, and measure” digital content and experiences. The other two pieces were already in place: “make” is Adobe’s original content creation business, while “measure” is Omniture Web analytics.
The strategic significance of the announcement seems more important than the actual product enhancements. These include improved integration of the company’s Web content management system (formerly Day C5) with Scene 7 dynamic content and Omniture Survey and Test & Target; features for salespeople and customer service agents to customize standard documents in a controlled fashion; integrated content reviews and workflows; and a platform to build and share content in multiple formats. The announcement also included beta versions of tools for social engagement, online enrollment, and agent workspaces. Good stuff but nothing earth-shaking.
Adobe's strategy itself is a curious mixture of broad ambition and narrow execution. Adobe describes its scope as nothing less than optimizing customer experience and marketing spend across the entire customer journey, from first learning about a company through validation, purchase decision, product use, and commitment. But Adobe also explicitly limits its scope to digital channels, and implicitly limits its concern to content creation, delivery, and evaluation. In fact, the only customer-facing technology Adobe offers is Web site management. Otherwise, Adobe expects even digital content such as emails to be delivered by third party products. Offline interactions, such as telephone and retail, are definitely out of the picture. Nor does Adobe manage the underlying customer database, marketing campaigns, or deep analytics. The only exceptions are customer profiles, segmentation, and content to support Web personalization.
The company argues the tools it does provide, combined with the cross-channel content sharing, are enough to build a unified digital customer experience. I’m not so sure that’s correct, and even if it is, I question whether customers will be happy to have only their digital experiences be unified. Either way, marketers will certainly need other vendors' products to manage their full customer relationships.
On the other hand, I do agree with Adobe’s argument that its approach lets clients create a unified digital experience without replacing their entire enterprise infrastructure. This is certainly an advantage.
Adobe’s announcement was released on Monday, but I didn’t get around to writing about it until today. The delay is unfortunate, since the attention of the enterprise marketing automation world has already shifted to yesterday’s announcement that Oracle is acquiring Web “experience” management vendor FatWire Software. I’m not sure I accept “Web experience management” as a legitimate software category, but FatWire does combine conventional Web content management with unusually strong targeting, personalization, content analytics, digital asset management, mobile, and social features. Perhaps that justifies calling it more than plain old Web content management.
The strategic purpose of the FatWire acquisition is self-evident: to fill a gap in Oracle’s customer-facing technologies, which already had ATG ecommerce and general Enterprise Content Management for Web sites, as well as Oracle CRM and Oracle Loyalty. (Oracle isn’t very creative with product names.) FatWire will allow much richer, more personalized and targeted Web site interactions. It also provides some Web analytics, although I still think Oracle has a gap to fill there.
The Oracle and Adobe announcements do highlight a clear strategic contrast. Adobe has largely limited itself to digital interactions, and has largely avoided customer-facing systems except for Web sites. Oracle has embraced the full range of online and offline interactions, including customer-facing systems in every channel. Oracle has also hedged its bets a bit with Real Time Decisions, which can coordinate customer treatments delivered by non-Oracle systems and powered by non-Oracle data sources. Of the other enterprise-level marketing automation vendors, IBM, SAS and Teradata share Adobe's focus on digital channels and its avoidance of customer-facing systems, although they resemble Oracle in offering deep analytics and customer database management.
Based on my fundamental rule that “suites win”, I think Oracle’s strategy is more likely to succeed. But only time will tell.
The strategic significance of the announcement seems more important than the actual product enhancements. These include improved integration of the company’s Web content management system (formerly Day C5) with Scene 7 dynamic content and Omniture Survey and Test & Target; features for salespeople and customer service agents to customize standard documents in a controlled fashion; integrated content reviews and workflows; and a platform to build and share content in multiple formats. The announcement also included beta versions of tools for social engagement, online enrollment, and agent workspaces. Good stuff but nothing earth-shaking.
Adobe's strategy itself is a curious mixture of broad ambition and narrow execution. Adobe describes its scope as nothing less than optimizing customer experience and marketing spend across the entire customer journey, from first learning about a company through validation, purchase decision, product use, and commitment. But Adobe also explicitly limits its scope to digital channels, and implicitly limits its concern to content creation, delivery, and evaluation. In fact, the only customer-facing technology Adobe offers is Web site management. Otherwise, Adobe expects even digital content such as emails to be delivered by third party products. Offline interactions, such as telephone and retail, are definitely out of the picture. Nor does Adobe manage the underlying customer database, marketing campaigns, or deep analytics. The only exceptions are customer profiles, segmentation, and content to support Web personalization.
The company argues the tools it does provide, combined with the cross-channel content sharing, are enough to build a unified digital customer experience. I’m not so sure that’s correct, and even if it is, I question whether customers will be happy to have only their digital experiences be unified. Either way, marketers will certainly need other vendors' products to manage their full customer relationships.
On the other hand, I do agree with Adobe’s argument that its approach lets clients create a unified digital experience without replacing their entire enterprise infrastructure. This is certainly an advantage.
Adobe’s announcement was released on Monday, but I didn’t get around to writing about it until today. The delay is unfortunate, since the attention of the enterprise marketing automation world has already shifted to yesterday’s announcement that Oracle is acquiring Web “experience” management vendor FatWire Software. I’m not sure I accept “Web experience management” as a legitimate software category, but FatWire does combine conventional Web content management with unusually strong targeting, personalization, content analytics, digital asset management, mobile, and social features. Perhaps that justifies calling it more than plain old Web content management.
The strategic purpose of the FatWire acquisition is self-evident: to fill a gap in Oracle’s customer-facing technologies, which already had ATG ecommerce and general Enterprise Content Management for Web sites, as well as Oracle CRM and Oracle Loyalty. (Oracle isn’t very creative with product names.) FatWire will allow much richer, more personalized and targeted Web site interactions. It also provides some Web analytics, although I still think Oracle has a gap to fill there.
The Oracle and Adobe announcements do highlight a clear strategic contrast. Adobe has largely limited itself to digital interactions, and has largely avoided customer-facing systems except for Web sites. Oracle has embraced the full range of online and offline interactions, including customer-facing systems in every channel. Oracle has also hedged its bets a bit with Real Time Decisions, which can coordinate customer treatments delivered by non-Oracle systems and powered by non-Oracle data sources. Of the other enterprise-level marketing automation vendors, IBM, SAS and Teradata share Adobe's focus on digital channels and its avoidance of customer-facing systems, although they resemble Oracle in offering deep analytics and customer database management.
Based on my fundamental rule that “suites win”, I think Oracle’s strategy is more likely to succeed. But only time will tell.
Montag, Juni 20, 2011
How Do You Measure the Influence of Marketing Messages?
My review of Coremetrics Lifestyle raised the issue of measuring the impact of marketing materials on customer behavior. Of course, this is just one piece of the marketing attribution puzzle. But it’s worth a separate discussion because it’s such a common question – and, unlike so many measurement problems, this one actually has an answer.
Let’s start with the original impetus. This was an “influence” report that showed the percentage of people reaching a marketing stage who had received specific marketing treatments (or had other attributes such as source, product history, demographic, etc.). The idea was that treatments received by a higher percentage of customers were more influential. In other words, if 100% of new buyers saw a white paper offer and just 50% saw a Webinar invitation, then the white paper has more influence than the Webinar.
Plausible, yes. But wrong.
Let’s think through the example. What if the white paper is offered to everyone? Yes, 100% of new buyers saw it, but so did 100% of non-buyers. We know exactly nothing about whether it made its recipients more or less likely to purchase.
Now, let’s say just 10% of prospects see the Webinar invitation, compared with 50% of buyers. Can we say it has a positive influence? Still no: maybe the Webinar attracts hot prospects who would have purchased anyway. It’s even possible that the Webinar offer annoys people and actually reduces purchase rates. You can’t tell from these figures.
In other words, it’s not enough to know what was seen by customers who became buyers (or, more generally, by people who took any particular action). You also need to know what was seen by non-buyers and, ideally, to compare results for groups that are similar except for that particular treatment.
So, what measures do make sense for assessing influence?
- the simplest measure compares the result rate of treated customers with results for non-treated customers. You might find that 20% of people who receive a white paper became buyers, compared with 10% of people who don’t receive the white paper. These two figures can be combined in a single ratio: 20% of treated / 10% of non-treated = 2.0. The higher the ratio, the more it seems that receiving the white paper increased the likelihood that someone would purchase. But it’s no more than a suggestion: maybe the white paper was sent to people who were stronger prospects to begin with.
- a more advanced measure adjusts for the audience by attempting to limit the non-treated group (e.g., non-buyers) to customers similar to the target group. This could be done by building a statistical model that uses all other attributes to predict behavior. Or, you could apply lead scores or funnel stage definitions. Whatever the technique, the result is to divide the audience into groups that are expected to behave similarly. The calculation would then compare results of treated vs. non-treated customers in each same group. So, a report might find that 40% of “stage 3 leads” (whatever they are) made a purchase after attending a Webinar, while just 15% of “stage 3 leads” made a purchase if they didn't attend a Webinar. Again, the treated and non-treated figures could be combined in a ratio (40% / 15% = 2.7)
- of course, the only true measure is a structured test. This ensures that the only difference between the treated and non-treated groups is the treatment itself. Without such tests, there's a good chance that the customers selected for treatment would have performed differently in any event.
A proper reporting system would present the ratios along with actual result rates, trends over time, the number of customers receiving each treatment, and comparisons with ratios for other treatments. These figures help marketers focus their energies on the most valuable opportunities. Still, the starting point is always a comparison of treated vs. non-treated performance: without that, the numbers could mean anything.
Let’s start with the original impetus. This was an “influence” report that showed the percentage of people reaching a marketing stage who had received specific marketing treatments (or had other attributes such as source, product history, demographic, etc.). The idea was that treatments received by a higher percentage of customers were more influential. In other words, if 100% of new buyers saw a white paper offer and just 50% saw a Webinar invitation, then the white paper has more influence than the Webinar.
Plausible, yes. But wrong.
Let’s think through the example. What if the white paper is offered to everyone? Yes, 100% of new buyers saw it, but so did 100% of non-buyers. We know exactly nothing about whether it made its recipients more or less likely to purchase.
Now, let’s say just 10% of prospects see the Webinar invitation, compared with 50% of buyers. Can we say it has a positive influence? Still no: maybe the Webinar attracts hot prospects who would have purchased anyway. It’s even possible that the Webinar offer annoys people and actually reduces purchase rates. You can’t tell from these figures.
In other words, it’s not enough to know what was seen by customers who became buyers (or, more generally, by people who took any particular action). You also need to know what was seen by non-buyers and, ideally, to compare results for groups that are similar except for that particular treatment.
So, what measures do make sense for assessing influence?
- the simplest measure compares the result rate of treated customers with results for non-treated customers. You might find that 20% of people who receive a white paper became buyers, compared with 10% of people who don’t receive the white paper. These two figures can be combined in a single ratio: 20% of treated / 10% of non-treated = 2.0. The higher the ratio, the more it seems that receiving the white paper increased the likelihood that someone would purchase. But it’s no more than a suggestion: maybe the white paper was sent to people who were stronger prospects to begin with.
- a more advanced measure adjusts for the audience by attempting to limit the non-treated group (e.g., non-buyers) to customers similar to the target group. This could be done by building a statistical model that uses all other attributes to predict behavior. Or, you could apply lead scores or funnel stage definitions. Whatever the technique, the result is to divide the audience into groups that are expected to behave similarly. The calculation would then compare results of treated vs. non-treated customers in each same group. So, a report might find that 40% of “stage 3 leads” (whatever they are) made a purchase after attending a Webinar, while just 15% of “stage 3 leads” made a purchase if they didn't attend a Webinar. Again, the treated and non-treated figures could be combined in a ratio (40% / 15% = 2.7)
- of course, the only true measure is a structured test. This ensures that the only difference between the treated and non-treated groups is the treatment itself. Without such tests, there's a good chance that the customers selected for treatment would have performed differently in any event.
A proper reporting system would present the ratios along with actual result rates, trends over time, the number of customers receiving each treatment, and comparisons with ratios for other treatments. These figures help marketers focus their energies on the most valuable opportunities. Still, the starting point is always a comparison of treated vs. non-treated performance: without that, the numbers could mean anything.
Donnerstag, Juni 09, 2011
Swyft Offers Low-Cost Interaction Management Software as a Service
Summary: Swyft offers a Software-as-a-Service real-time interaction manager. It costs less than traditional versions of those products but has similar features.
Last month’s post on Oracle Real Time Decisions offered a brief overview of real-time interaction management products. I won’t repeat that here, except to summarize that these systems use data from multiple source systems to feed centrally-managed, real-time decisions to multiple touchpoints. The most common application has probably been product recommendations in customer service call centers, where there’s a substantial opportunity to sell something to a customer once you’ve solved their problem. Another frequent use has been selecting offers on Web sites, such as the familiar book recommendations on Amazon.com.
You’ll note that both of these are single-channel examples. That may seem odd, since coordinating treatments across channels is a key selling point. I believe the explanation is that most buyers purchase interaction management systems to get more powerful decision engines than those provided with their call center and Web site products.
Indeed, effective interaction management requires a sophisticated mix of predictive modeling, business rules, flow management, response capture, data integration, real-time processing, simulation, and analytics. The simple scripting and personalization engines built into call center and Web products don't provide all this. Equally important, the results of an interaction management deployment are immediately and precisely measureable – so it’s clear when one product works better than another. This means specialist vendors with superior products have a good chance to survive.
But you’ll also notice that these products don’t have many customers. I haven’t done a proper census but doubt there are five hundred implementations among all vendors combined. One reason is the sophistication itself: only a highly knowledgeable set of users can deploy the required rules and models effectively. Another is cost: you’re looking at the price of a 50 foot yacht (about a quarter million dollars if you haven’t bought one lately), plus a sister ship or two for implementation. Few firms with the resources and business volume needed to justify this expense.
(Alternate interpretation: the tools built into standard call center and Web applications are pretty good, so dedicated interaction managers offer only a small percentage gain. A company must be quite large for this to cover the interaction manager's cost.)
Swyft provides a low-cost alternative – more like a 30 footer (around $100,000).
The comparison is inexact because traditional interaction management systems are sold as licensed on-premise software, while Swyft is a Software-as-a-Service product, billed monthly. Pricing for agent-based applications (call centers, field sales, etc.) runs about one dinghy per user ($50 to $80 per month). But even small clients buy a fleet of 100 or more. Web site applications are priced on number of customers but come to roughly the same total.
Implementation is around $15,000 to $25,000, with data connections handled through standard Web Services. The company says a typical deployment takes 30 to 90 days, usually closer to 30.
Functionally, Swyft offers a pretty full set of interaction management capabilities. Decision rules can take into account capacity constraints such as call center workload; customer propensities; current and previous interactions; channel distinctions; offer eligibility; and event-based triggers. Interactions can kick off complex back-end workflows for follow-up treatments.
Call center integrations monitor agent activities and flash an alert if the system has an offer to make. The system then guides the agent through transition statements, probing questions, objections, offers, closing statements, and disposition capture. It can present different messages depending on the agent’s skill level. Web site implementations can present offers, collect data, and run champion/challenger and multivariate tests. The system will automatically adjust offer frequencies based on test results.
One feature that Swyft lacks is built-in predictive modeling. The company says it has found that most clients already have models in place. Rules can use model scores as inputs.
Like other interaction managers, Swyft relies primarily on data stored in external systems. Again like other products, it creates its own database of offers made and responses received for each customer. Less typically, it also stores marketing contents internally and provides a content builder to create these. The system can import and store additioinal information if real-time access is not appropriate.
The current version of Swyft lacks an interface that lets business users create their own rules. The company addresses this largely by doing the work for its clients, providing a “concierge” service that includes content and rule management as part of the base price. Clients do have the option to do this work for themselves; the company says it can be done after a couple weeks of training. A simpler end-user interface is planned for future development.
Swyft was founded in 2004 and launched its product in 2006. It has about ten clients spread among financial services, insurance, communications and media. The largest are mid-sized firms, with a several million customers. Intriguingly, the company offers its product on the Salesforce.com App Exchange, specifically offering a smartphone-enabled version that can use geolocation to identify a salesperson’s current location and recommend the most efficient prospects to visit. It has not yet deployed this at an actual client.
Last month’s post on Oracle Real Time Decisions offered a brief overview of real-time interaction management products. I won’t repeat that here, except to summarize that these systems use data from multiple source systems to feed centrally-managed, real-time decisions to multiple touchpoints. The most common application has probably been product recommendations in customer service call centers, where there’s a substantial opportunity to sell something to a customer once you’ve solved their problem. Another frequent use has been selecting offers on Web sites, such as the familiar book recommendations on Amazon.com.
You’ll note that both of these are single-channel examples. That may seem odd, since coordinating treatments across channels is a key selling point. I believe the explanation is that most buyers purchase interaction management systems to get more powerful decision engines than those provided with their call center and Web site products.
Indeed, effective interaction management requires a sophisticated mix of predictive modeling, business rules, flow management, response capture, data integration, real-time processing, simulation, and analytics. The simple scripting and personalization engines built into call center and Web products don't provide all this. Equally important, the results of an interaction management deployment are immediately and precisely measureable – so it’s clear when one product works better than another. This means specialist vendors with superior products have a good chance to survive.
But you’ll also notice that these products don’t have many customers. I haven’t done a proper census but doubt there are five hundred implementations among all vendors combined. One reason is the sophistication itself: only a highly knowledgeable set of users can deploy the required rules and models effectively. Another is cost: you’re looking at the price of a 50 foot yacht (about a quarter million dollars if you haven’t bought one lately), plus a sister ship or two for implementation. Few firms with the resources and business volume needed to justify this expense.
(Alternate interpretation: the tools built into standard call center and Web applications are pretty good, so dedicated interaction managers offer only a small percentage gain. A company must be quite large for this to cover the interaction manager's cost.)
Swyft provides a low-cost alternative – more like a 30 footer (around $100,000).
The comparison is inexact because traditional interaction management systems are sold as licensed on-premise software, while Swyft is a Software-as-a-Service product, billed monthly. Pricing for agent-based applications (call centers, field sales, etc.) runs about one dinghy per user ($50 to $80 per month). But even small clients buy a fleet of 100 or more. Web site applications are priced on number of customers but come to roughly the same total.
Implementation is around $15,000 to $25,000, with data connections handled through standard Web Services. The company says a typical deployment takes 30 to 90 days, usually closer to 30.
Functionally, Swyft offers a pretty full set of interaction management capabilities. Decision rules can take into account capacity constraints such as call center workload; customer propensities; current and previous interactions; channel distinctions; offer eligibility; and event-based triggers. Interactions can kick off complex back-end workflows for follow-up treatments.
Call center integrations monitor agent activities and flash an alert if the system has an offer to make. The system then guides the agent through transition statements, probing questions, objections, offers, closing statements, and disposition capture. It can present different messages depending on the agent’s skill level. Web site implementations can present offers, collect data, and run champion/challenger and multivariate tests. The system will automatically adjust offer frequencies based on test results.
One feature that Swyft lacks is built-in predictive modeling. The company says it has found that most clients already have models in place. Rules can use model scores as inputs.
Like other interaction managers, Swyft relies primarily on data stored in external systems. Again like other products, it creates its own database of offers made and responses received for each customer. Less typically, it also stores marketing contents internally and provides a content builder to create these. The system can import and store additioinal information if real-time access is not appropriate.
The current version of Swyft lacks an interface that lets business users create their own rules. The company addresses this largely by doing the work for its clients, providing a “concierge” service that includes content and rule management as part of the base price. Clients do have the option to do this work for themselves; the company says it can be done after a couple weeks of training. A simpler end-user interface is planned for future development.
Swyft was founded in 2004 and launched its product in 2006. It has about ten clients spread among financial services, insurance, communications and media. The largest are mid-sized firms, with a several million customers. Intriguingly, the company offers its product on the Salesforce.com App Exchange, specifically offering a smartphone-enabled version that can use geolocation to identify a salesperson’s current location and recommend the most efficient prospects to visit. It has not yet deployed this at an actual client.
Mittwoch, Juni 08, 2011
Coremetrics Offers a Foggy View of Lifecycle Analysis
I stumbled over an Adexchanger interview yesterday with John Squire, the Chief Strategy Officer of IBM Coremetrics. It first caught my eye because the headline read “IBM’s Vision for the Marketer”, which is always a topic of interest. Then I noticed it was touting new reporting feature called Coremetrics Lifecycle, which the company describes as “the industry’s first application geared to enable online marketers to track and understand how customers progress through long-term conversion lifecycles.”
This was intriguing. On one hand, I’ve seen plenty of systems that track customers through the buying process, including Eloqua, Marketo, Leadformix, Clear Saleing, C3 Metrics, and Encore Media Metrics. So the claim to be first is questionable. But, on the other hand, seeing another vendor offer this sort of analysis reinforces the importance of the concept.
But a closer look at Lifecycle itself was disappointing. The product does allow tracking of individual Web site visitors over time, which is the foundation of lifecycle analysis. But, in my opinion, a lifecycle tracking system reports on movement of customers across stages within the lifecycle. That is, it shows conversions from one stage to the next. This implies reports that show the previous stages of customers who enter a new stage (“where they came from”), and show the destinations of customers who leave a stage (“where they went”). These are typically represented as a matrix showing all combinations of previous and current stages, or a flow chart that highlights the most common before-and-after pairs.
Lifecycle does none of this. Rather, it lets users define any number of segmentation schemes and count the number of customers in each segment. It does report how many customers entered each segment during a specified time period, but not where they came from. In fact, there is no requirement for a logical progression from one segment to the next, which to me is what a lifecycle implies.
Lifecycle has some other useful features. It can report on the most common marketing treatments received by people who moved into a segment, giving some insight into treatment effectiveness. It calculates the average number of days and Web sessions that customers spend in a segment, which is a limited velocity measure. It also lets users select segment members and send them messages through Coremetrics’ products for email, display ad retargeting, and Web site personalization, although it's not clear the process can be automated.
But a proper lifecycle analysis tool would go much further. It would calculate the end-to-end completion rates, show the drop-off from one stage to the next, estimate the incremental impact of specific treatments, project future segment counts, and show changes in these measures over time. So while I’m pleased that Coremetrics is promoting the concept of lifecycle analysis, I’m disappointed that its product doesn’t deliver a real lifecycle measurement solution.
Addendum - June 19, 2011
After the original post and IBM's comment on it, I reviewed the Lifecycle product with the Coremetrics team. This uncovered no substantive errors in the original post, although a couple of points could have been stated more clearly.
- the system supports two types of lifecycles, one requiring that customers progress through the stages in sequence and one that does not. Users specify the type when they set up a new lifecycle. In both cases, the stages are defined by selection rules created by the user.
- there is a limit of six stages per lifeycle.
- for sequential lifecycles, the system will warn the user if the selection rules are not inherently sequential. (An inherently sequential rule might be based on the number of purchases made; you can't make three purchases without having previously made two. Other stage definitions, such as downloading a white paper or leaving a comment, might come in any order and, therefore, are not inherently sequential.)
- in a sequential lifecycle, the system will not allow customers to advance outside of sequence even if the definitions would allow it. Nor does it report on customers who would qualify for a later stage but cannot reach it because they didn't qualify for a previous one.
- the system's primary report shows the number of customers within each stage during a specified date range. Think of this as an inventory. A "Migrator" report shows how many customers entered their current stage during the report period: for example, there were 500 customers in stage 3, of whom 200 first entered stage 3 during this period. This gives some sense of movement, but it's not the classic funnel analysis showing the percentage of customers in each stage who eventually move to the next stage.
- users can run the standard reports against "segments", which could be defined as anything including a cohort of customers who entered the system during a specified time period. A Lifecycle inventory report for such a cohort would show how many customers reached each stage and got no further. This is the information needed to build a classic funnel analysis, although users would have to extract the data and manipulate it to produce an actual funnel report. This would be done outside of Coremetrics, because there is no end-user report writer.
- reports show the average number of days and Web sessions it takes customers to reach each stage (i.e., since they first entered the system), not the number of days and sessions spent in each stage, as I wrote originally.
- users do have the option to create a recurring process that automatically selects customers in a particular stage and sends them an email or other message. The system could apply a few rules to this process, such as eliminating people who had been selected previously. But more sophisticated controls would be handled outside of Coremetrics, in the message delivery system.
- the system can profile customers in each stage against many attributes (products purchased, geography, social network membership, etc.) in addition to marketing contents received. But, as I wrote originally, the reporting only shows the percentage of customers in each stage who match a particular attribute: this is far from measuring influence, for reasons I'll explain in a future post.
- we confirmed that the system doesn't do projections of future inventory counts, report on out-of-sequence customer movements, or allow customers to migrate backwards into lower-ranked stages (as might happen if stages were based on recency or ratios).
I'm happy to have clarified these matters but none of this changes my original assessment: Lifecycle is a useful product that falls far short of serious life stage analysis.
This was intriguing. On one hand, I’ve seen plenty of systems that track customers through the buying process, including Eloqua, Marketo, Leadformix, Clear Saleing, C3 Metrics, and Encore Media Metrics. So the claim to be first is questionable. But, on the other hand, seeing another vendor offer this sort of analysis reinforces the importance of the concept.
But a closer look at Lifecycle itself was disappointing. The product does allow tracking of individual Web site visitors over time, which is the foundation of lifecycle analysis. But, in my opinion, a lifecycle tracking system reports on movement of customers across stages within the lifecycle. That is, it shows conversions from one stage to the next. This implies reports that show the previous stages of customers who enter a new stage (“where they came from”), and show the destinations of customers who leave a stage (“where they went”). These are typically represented as a matrix showing all combinations of previous and current stages, or a flow chart that highlights the most common before-and-after pairs.
Lifecycle does none of this. Rather, it lets users define any number of segmentation schemes and count the number of customers in each segment. It does report how many customers entered each segment during a specified time period, but not where they came from. In fact, there is no requirement for a logical progression from one segment to the next, which to me is what a lifecycle implies.
Lifecycle has some other useful features. It can report on the most common marketing treatments received by people who moved into a segment, giving some insight into treatment effectiveness. It calculates the average number of days and Web sessions that customers spend in a segment, which is a limited velocity measure. It also lets users select segment members and send them messages through Coremetrics’ products for email, display ad retargeting, and Web site personalization, although it's not clear the process can be automated.
But a proper lifecycle analysis tool would go much further. It would calculate the end-to-end completion rates, show the drop-off from one stage to the next, estimate the incremental impact of specific treatments, project future segment counts, and show changes in these measures over time. So while I’m pleased that Coremetrics is promoting the concept of lifecycle analysis, I’m disappointed that its product doesn’t deliver a real lifecycle measurement solution.
Addendum - June 19, 2011
After the original post and IBM's comment on it, I reviewed the Lifecycle product with the Coremetrics team. This uncovered no substantive errors in the original post, although a couple of points could have been stated more clearly.
- the system supports two types of lifecycles, one requiring that customers progress through the stages in sequence and one that does not. Users specify the type when they set up a new lifecycle. In both cases, the stages are defined by selection rules created by the user.
- there is a limit of six stages per lifeycle.
- for sequential lifecycles, the system will warn the user if the selection rules are not inherently sequential. (An inherently sequential rule might be based on the number of purchases made; you can't make three purchases without having previously made two. Other stage definitions, such as downloading a white paper or leaving a comment, might come in any order and, therefore, are not inherently sequential.)
- in a sequential lifecycle, the system will not allow customers to advance outside of sequence even if the definitions would allow it. Nor does it report on customers who would qualify for a later stage but cannot reach it because they didn't qualify for a previous one.
- the system's primary report shows the number of customers within each stage during a specified date range. Think of this as an inventory. A "Migrator" report shows how many customers entered their current stage during the report period: for example, there were 500 customers in stage 3, of whom 200 first entered stage 3 during this period. This gives some sense of movement, but it's not the classic funnel analysis showing the percentage of customers in each stage who eventually move to the next stage.
- users can run the standard reports against "segments", which could be defined as anything including a cohort of customers who entered the system during a specified time period. A Lifecycle inventory report for such a cohort would show how many customers reached each stage and got no further. This is the information needed to build a classic funnel analysis, although users would have to extract the data and manipulate it to produce an actual funnel report. This would be done outside of Coremetrics, because there is no end-user report writer.
- reports show the average number of days and Web sessions it takes customers to reach each stage (i.e., since they first entered the system), not the number of days and sessions spent in each stage, as I wrote originally.
- users do have the option to create a recurring process that automatically selects customers in a particular stage and sends them an email or other message. The system could apply a few rules to this process, such as eliminating people who had been selected previously. But more sophisticated controls would be handled outside of Coremetrics, in the message delivery system.
- the system can profile customers in each stage against many attributes (products purchased, geography, social network membership, etc.) in addition to marketing contents received. But, as I wrote originally, the reporting only shows the percentage of customers in each stage who match a particular attribute: this is far from measuring influence, for reasons I'll explain in a future post.
- we confirmed that the system doesn't do projections of future inventory counts, report on out-of-sequence customer movements, or allow customers to migrate backwards into lower-ranked stages (as might happen if stages were based on recency or ratios).
I'm happy to have clarified these matters but none of this changes my original assessment: Lifecycle is a useful product that falls far short of serious life stage analysis.
Donnerstag, Juni 02, 2011
Oracle Integrates On Demand Marketing with On Demand CRM
Summary: Oracle has integrated marketing automation with its on-demand CRM product. Will competitors do the same?
If I were more on the ball, I would have noticed that May 25 marked a full year since Oracle bought the intellectual property* of high-end B2B marketing automation vendor Market2Lead. I was actually briefed on May 17 by the Oracle team handling the resulting product but hadn’t noticed that the anniversary was approaching. I wonder if they had cake?
I hope so, since they’ve clearly been working hard. In February they released the first “Oraclized” version of the product, now Oracle CRM On Demand Marketing. This included a redesigned user interface that matches the look, feel, and terminology of Oracle’s on-demand CRM product, is available in the same 20 languages, and allows unified user IDs and log-ins.
The new system uses the same data structures as the rest of Oracle CRM On Demand. It shares many physical tables as well, but keeps the major contact tables separate yet synchronized. This is largely because Marketing systems typically contain many more leads than Sales wants in CRM. Marketing systems also run large, complex queries that would interfere with CRM performance if both systems used the same physical files.
The unified data structure allows unified reporting across the customer buying process. Although Oracle doesn’t use the term, this is very consistent with the revenue management concepts described by other B2B marketing automation vendors. Oracle’s new Marketing system supports this with a separate analytical database, which is essential for advanced revenue reporting such as time-series analysis.
Except for improved reporting, the features of the new Oracle product are pretty much the same as the old Market2Lead, which I last reviewed two years ago. This was, and remains, one of the most powerful in the industry. Important capabilities include “adaptive” program flows, which vary depending on customer behavior; advanced Web pages and forms; automated content recommendations; and several types of asset templates. These are mostly relevant to large companies, which fits nicely with Oracle’s customer base.
In fact, most On Demand Marketing sales are part of an Oracle CRM On Demand installation, either at current Oracle CRM users or at clients buying both CRM and marketing automation simultaneously. It doesn’t hurt that On Demand Marketing is the only choice for companies who want a Software-as-a-Service marketing system from Oracle. The company’s other big marketing automation product, Siebel Marketing, is on-premise software.
All this makes Oracle a poster child of sorts for the proposition that CRM and marketing automation should be part of a single system. I’ve argued this for a long time but it’s still a minority view, especially (and for obvious reasons) among the vendors of stand-alone marketing automation products. Oracle itself has announced an initiative for “cross channel customer experience management” which incorporates its products for CRM, marketing, loyalty, real-time decisions, and ecommerce.
It will be interesting to see whether Oracle’s integrated marketing-plus-sales product leads its not-so-friendly competitors at Salesforce.com to respond with an integrated solution of their own. Or, more broadly, whether IBM sticks to its position that it doesn’t need a CRM product to dominate the integrated marketing world. The B2B marketing automation vendors are definitely mice at an elephant dance. It’s a dangerous but exciting position.
____________________________________________________
* It wasn’t an outright acquisition because Salesforce.com wouldn’t permit integration with an Oracle-owned product. So existing Market2Lead clients remained with the old company until it could migrate them to other marketing platforms. Once this is done, Market2Lead will complete its shutdown.
If I were more on the ball, I would have noticed that May 25 marked a full year since Oracle bought the intellectual property* of high-end B2B marketing automation vendor Market2Lead. I was actually briefed on May 17 by the Oracle team handling the resulting product but hadn’t noticed that the anniversary was approaching. I wonder if they had cake?
I hope so, since they’ve clearly been working hard. In February they released the first “Oraclized” version of the product, now Oracle CRM On Demand Marketing. This included a redesigned user interface that matches the look, feel, and terminology of Oracle’s on-demand CRM product, is available in the same 20 languages, and allows unified user IDs and log-ins.
The new system uses the same data structures as the rest of Oracle CRM On Demand. It shares many physical tables as well, but keeps the major contact tables separate yet synchronized. This is largely because Marketing systems typically contain many more leads than Sales wants in CRM. Marketing systems also run large, complex queries that would interfere with CRM performance if both systems used the same physical files.
The unified data structure allows unified reporting across the customer buying process. Although Oracle doesn’t use the term, this is very consistent with the revenue management concepts described by other B2B marketing automation vendors. Oracle’s new Marketing system supports this with a separate analytical database, which is essential for advanced revenue reporting such as time-series analysis.
Except for improved reporting, the features of the new Oracle product are pretty much the same as the old Market2Lead, which I last reviewed two years ago. This was, and remains, one of the most powerful in the industry. Important capabilities include “adaptive” program flows, which vary depending on customer behavior; advanced Web pages and forms; automated content recommendations; and several types of asset templates. These are mostly relevant to large companies, which fits nicely with Oracle’s customer base.
In fact, most On Demand Marketing sales are part of an Oracle CRM On Demand installation, either at current Oracle CRM users or at clients buying both CRM and marketing automation simultaneously. It doesn’t hurt that On Demand Marketing is the only choice for companies who want a Software-as-a-Service marketing system from Oracle. The company’s other big marketing automation product, Siebel Marketing, is on-premise software.
All this makes Oracle a poster child of sorts for the proposition that CRM and marketing automation should be part of a single system. I’ve argued this for a long time but it’s still a minority view, especially (and for obvious reasons) among the vendors of stand-alone marketing automation products. Oracle itself has announced an initiative for “cross channel customer experience management” which incorporates its products for CRM, marketing, loyalty, real-time decisions, and ecommerce.
It will be interesting to see whether Oracle’s integrated marketing-plus-sales product leads its not-so-friendly competitors at Salesforce.com to respond with an integrated solution of their own. Or, more broadly, whether IBM sticks to its position that it doesn’t need a CRM product to dominate the integrated marketing world. The B2B marketing automation vendors are definitely mice at an elephant dance. It’s a dangerous but exciting position.
____________________________________________________
* It wasn’t an outright acquisition because Salesforce.com wouldn’t permit integration with an Oracle-owned product. So existing Market2Lead clients remained with the old company until it could migrate them to other marketing platforms. Once this is done, Market2Lead will complete its shutdown.
Donnerstag, Mai 26, 2011
Oracle Real-Time Decisions Empowers Business Users
One of the few dependable rules in the software industry is that Suites Win. When a market first develops, it is filled with “point solutions” that do one function – say, send emails or analyze Web traffic. Over time, products emerge that combine these functions and displace the individual point solutions. Even though the point solutions may be better at their particular task than the corresponding suite components, the time, cost, and risk savings of preintegrated products are irresistible to most buyers.* This is especially true when IT departments, rather than end-users, control the purchase process.
The only reason that companies haven’t already ended up with a single mega-system is that new applications appear constantly. It takes time before the existing suites can expand to assimilate the new features. This is especially true in customer management, where new touchpoints – Web, mobile, social, etc. – appear at a dizzying pace. In the real world, nearly all companies run multiple customer contact systems and probably always will.
What this means in practical terms is that companies wishing to coordinate customer treatments across channels need to knit together their separate touchpoints. A class of systems to do this has long existed, loosely labeled as “interaction managers” or “decision engines”. These systems manage outbound campaigns and real-time interactions using a combination of business rules and predictive models. Examples include Infor Interaction Advisor, IBM Unica Interact, Pegasystems Recommendation Advisor, SAS Real-Time Decision Manager, eponymous thinkAnalytics, and Oracle Real-Time Decisions.
These systems are all broadly similar in that they connect to external systems for customer data, marketing content, and message delivery. This contrasts with standard marketing automation and customer relationship management systems, which maintain their own customer databases, store content internally, and deliver messages themselves. Interaction managers and other types of customer management systems do share decision management capabilities including multi-step process flows, logical rules, and predictive models.
Interaction management vendors compete on the power of their rules, automated model generation, user interface, scalability, and analytics. To some degree they also compete their ability to connect with data sources and touchpoint systems. But every vendor I've spoken with says this integration is easy, so it doesn’t seem to be a major point of differentiation.
I caught up last week with the Oracle Real-Time Decisions (RTD) team, who released their latest version earlier this month. RTD is based on the SigmaDynamics product, originally built in 2002 and purchased by Oracle in 2006. Oracle now sells it as a general purchase decision platform, positioned as one of its business intelligence and middleware products. But although some clients do use it for customer service, sales, and operations management, 90% of implementations are still for marketing decisions, primarily to select offers for Web sites and call centers.
RTD’s particular strengths are automated learning and sophisticated decision rules. Users set up process flows, define decision points within each flow, and connect to touchpoint systems to capture events at those decision points. The system then automatically correlates event outcomes with creative, channels, offers, customer attributes and other factors. This happens without users specifying which factors to track -- a significant labor saving. The scope of data lets the system predict behaviors based on the full context of a situation, not just the customer’s identity. The data also provides the foundation for in-depth reports on the factors driving results, in addition to standard campaign reporting.
Decision rules can incorporate multiple goals, each assigned a relative weight, and multiple choices, each assigned a value towards reaching each goal. The system scores each choice by adding up the value it contributes to each goal, adjusted for the probability that the customer will accept that choice if offered. Users can also weigh goals differently for different customer segments: for example, retention might be more important for high-value customers, while cost reduction could be a priority for customers who are less profitable. The same goal definitions can apply to multiple decisions, reducing work and ensuring consistency.
Although RTD has always been powerful, its user interface was designed for technical users. The latest release changes this, introducing role-based security that allows different business users throughout an organization to control different functions. This means offers could be controlled by one person, campaigns designed by someone else, and touchpoint placements by a third party. Different users can also be presented with different views of the underlying objects, so they can see information organized in ways that make the most sense for their own purposes.
The new version of RTD is still aimed at large enterprises. Pricing depends on the type of deployment but it's a safe bet you won't get started for less than a couple hundred thousand dollars.
__________________________________________________________________________________
*True believers might argue that Software as a Service upends this rule by making integration very simple. I’ll grant that SaaS makes it easier to add new components on top of a standard platform such as Salesforce.com’s Force.com. But I'd argue that the platform itself is the functional equivalent of the suite, so the rule still stands.
The only reason that companies haven’t already ended up with a single mega-system is that new applications appear constantly. It takes time before the existing suites can expand to assimilate the new features. This is especially true in customer management, where new touchpoints – Web, mobile, social, etc. – appear at a dizzying pace. In the real world, nearly all companies run multiple customer contact systems and probably always will.
What this means in practical terms is that companies wishing to coordinate customer treatments across channels need to knit together their separate touchpoints. A class of systems to do this has long existed, loosely labeled as “interaction managers” or “decision engines”. These systems manage outbound campaigns and real-time interactions using a combination of business rules and predictive models. Examples include Infor Interaction Advisor, IBM Unica Interact, Pegasystems Recommendation Advisor, SAS Real-Time Decision Manager, eponymous thinkAnalytics, and Oracle Real-Time Decisions.
These systems are all broadly similar in that they connect to external systems for customer data, marketing content, and message delivery. This contrasts with standard marketing automation and customer relationship management systems, which maintain their own customer databases, store content internally, and deliver messages themselves. Interaction managers and other types of customer management systems do share decision management capabilities including multi-step process flows, logical rules, and predictive models.
Interaction management vendors compete on the power of their rules, automated model generation, user interface, scalability, and analytics. To some degree they also compete their ability to connect with data sources and touchpoint systems. But every vendor I've spoken with says this integration is easy, so it doesn’t seem to be a major point of differentiation.
I caught up last week with the Oracle Real-Time Decisions (RTD) team, who released their latest version earlier this month. RTD is based on the SigmaDynamics product, originally built in 2002 and purchased by Oracle in 2006. Oracle now sells it as a general purchase decision platform, positioned as one of its business intelligence and middleware products. But although some clients do use it for customer service, sales, and operations management, 90% of implementations are still for marketing decisions, primarily to select offers for Web sites and call centers.
RTD’s particular strengths are automated learning and sophisticated decision rules. Users set up process flows, define decision points within each flow, and connect to touchpoint systems to capture events at those decision points. The system then automatically correlates event outcomes with creative, channels, offers, customer attributes and other factors. This happens without users specifying which factors to track -- a significant labor saving. The scope of data lets the system predict behaviors based on the full context of a situation, not just the customer’s identity. The data also provides the foundation for in-depth reports on the factors driving results, in addition to standard campaign reporting.
Decision rules can incorporate multiple goals, each assigned a relative weight, and multiple choices, each assigned a value towards reaching each goal. The system scores each choice by adding up the value it contributes to each goal, adjusted for the probability that the customer will accept that choice if offered. Users can also weigh goals differently for different customer segments: for example, retention might be more important for high-value customers, while cost reduction could be a priority for customers who are less profitable. The same goal definitions can apply to multiple decisions, reducing work and ensuring consistency.
Although RTD has always been powerful, its user interface was designed for technical users. The latest release changes this, introducing role-based security that allows different business users throughout an organization to control different functions. This means offers could be controlled by one person, campaigns designed by someone else, and touchpoint placements by a third party. Different users can also be presented with different views of the underlying objects, so they can see information organized in ways that make the most sense for their own purposes.
The new version of RTD is still aimed at large enterprises. Pricing depends on the type of deployment but it's a safe bet you won't get started for less than a couple hundred thousand dollars.
__________________________________________________________________________________
*True believers might argue that Software as a Service upends this rule by making integration very simple. I’ll grant that SaaS makes it easier to add new components on top of a standard platform such as Salesforce.com’s Force.com. But I'd argue that the platform itself is the functional equivalent of the suite, so the rule still stands.
Freitag, Mai 20, 2011
Pirates, Train Wrecks, and Marketing Automation
Summary: Selecting a marketing automation system is an adventure. Here's the screenplay. Ready when you are, CB.
I spent most of this week at the inaugural DemandCon conference in San Francisco. My presentation, How to Avoid a Marketing Automation Train Wreck, was based largely on the Marketing Automation Vendor Selection Workbook I released last month (available for free on the RaabGuide Web site). But the heart of the Workbook is a series of checklists like the one below, whereas DemandCon asked presenters to avoid long lists of bullet points. So I had to rethink the format.
After some pondering, I decided it would be more memorable to structure the presentation as a story. This made sense: deploying a marketing automation system is literally a quest, and one that can end in either triumph or the train wreck of my title. Although my actual delivery was marred by a few technical hiccups, I liked the result enough to offer a version of it here.
Prologue
A good adventure begins with a map. This one starts with our hero, a young prince, accidentally uncovering a box containing a map of the marketing technology landscape, showing where B2B marketing automation fits among other types of customer management systems. Since any story is better if you add pirates, this is a treasure map, where X marks the spot. (Sadly, one of the technical hiccups meant the DemandCon audience never saw this image, but I personally find it hilarious. Note the pirate-style headline.):
The box also holds a chart that lists the features of different types of marketing automation systems. I didn't have time to reformat it, but in the story these are presented as clues to identifying the treasure.
He also finds a set of puzzle pieces that, when assembled, present a flow chart of standard B2B marketing tasks: program setup, lead generation, nurturing, scoring, transfer to sales, and reporting. This teaches him that marketing automation is a process, not a technology.
Our Story Begins...
The young prince is intrigued by his discovery, but reluctant to take on the quest. He is moved to action by a village of marketers and salespeople crying out for more leads and better nurturing. Specific benefits include replacing point solutions with an integrated system; running larger numbers and more types of marketing programs; less reliance on non-marketing resources to manage Web content and process data; and closer integration with sales. Who could resist?
After the hero announces his decision, he is warned about the perils ahead by a wise old consultant. These include:
- buying without concrete objectives
- choosing systems based on who has the most, best, or coolest features
- only considering industry leaders
- not using scenarios to test systems against your needs
- ignoring the information you can gather from references
- not investing in training, planning, program design, content, and other resources for successful deployment
Thus forewarned, our hero starts his quest. He starts by making a plan, which means he identifies the business benefits expected from this project. These should be quantified and linked to marketing programs that will deliver them. Then he defines the requirements implied by these programs, by listing the tasks to be completed for each project and the system features needed to execute these tasks. I represented requirements as a kitten who “requires” a bowl of milk – except that now it’s a pirate kitten (my second-favorite slide in the deck. Yes, I am easily amused.)
Planning complete, the hero sets out on his search. Along the way, he meets several companions with different traits. Recognizing that he can't succeed alone, he knows he must choose one of them to help him find the treasure. His task at this stage is choosing the right one. (We somehow seem to have lost the pirates. Pity.)
These companions represent the different marketing automation systems. To choose wisely, the hero must understand the type of product he needs. I divide the B2B marketing automation world into three segments: systems serving “micro-businesses” (very small firms where marketing is a part-time job, often for the owner); small to mid-size business (a separate marketing department but typically in one location and serving one product line); and enterprises (huge companies with dozens of marketers serving multiple markets and products). Each type of business has different requirements and is served by different vendors: I won’t list the details here but they’re in the Workbook.
The Journey
Our band of travelers now faces a series of challenges, escaping from traps, crossing rivers, and beating off attacks by wild animals. At each stage a different member demonstrates his special skills. In concrete terms, this means defining scenarios based on the goals you have set for your marketing automation system. What matters is seeing how well the systems perform the tasks you need, not the ones the vendor likes to demonstrate. This means the real challenge is understanding your requirements – our hero must learn about himself before he can complete his quest. It’s a cliché but how else can I sell this to Disney?
Now the scene switches: it’s the tavern after a day of adventures, and our little group are warily eating together, trying to decide who they can trust. In other words, they’re checking references. You’ll remember that skipping references is one of the dangers I warned against. It’s true that the company will hand-pick happy customers, but you can still learn a lot if you ask the right questions:
- why did they pick the system (maybe the cared about something that’s not important to you);
- what do they see as strengths and weaknesses;
- are they using the system the same way you expect to;
- are their skills and resources similar to yours.
If a vendor can’t connect you with a reference whose situation matches your own, be very cautious.
And while we’re on the subject – don’t think social media queries replace reference checking. What comes back is typically a “yes, we love it” from highly motivated fans. Apart from dedicated grudge-holders, few businesspeople will volunteer negative feedback in social media: they can only get in trouble and there’s nothing in it for them. If you do rely on the social media, contact the people who respond and have an in-depth conversation asking the same questions you would ask the vendor’s own references.
Back to our story. The hero still hasn’t chosen on a single companion, and now the group faces the final test: it must cross the desert, storm the castle, and find the treasure. Who will stay and who will run away? Who will is a good long-term partner? The only way to find out is to move ahead.
In marketing automation terms, this means setting up a trial so you can understand the day-to-day details of working with a system. Most vendors will give you a trial license if they know you’re seriously considering their product. The trick to an effective trial is to test the system thoroughly: this means setting up programs are as demanding as those you’ll actually run once you own it and then running them from start to finish.
Here’s where all that early planning and goal-setting comes in handy, since you’ll have defined those programs already. If that sounds like too much work, bear in mind that you’ll need those programs after deployment anyway. So you might as well do the work a bit sooner and have the programs available to help make the right selection.
Triumph and Return
The group now wins the final battle and finds the treasure, only to meet a new crisis: there’s only enough water for two people to recross the desert. The hero must finally choose. In our story, this is easy because everyone else has failed or died nobly – oh, and it turns out that the remaining companion is really a disguised princess, with whom the hero has fallen in love. Didn’t see that coming, did you? Even better, she’s a pirate princess. Disney’s gonna love it.
But the real world isn’t a fairy tale. You may actually find several qualified vendors. Do what you can to make a rational choice – the Workbook provides a list of criteria to consider. But even if there is no clear winner, make a choice and get on with it. Remember your real goal is to get value from using the system, not to run the world’s finest selection project.
Epilogue
The story doesn’t end with the hero’s triumphant return. Treasure is only valuable if you spend it wisely; relationships don’t end with the wedding. It’s hard work to live happily ever after. So we have an epilogue showing how the happy couple used their riches to improve the lives of the villagers for years to come.
In marketing automation terms, this means avoiding the final mistake of underinvesting in deployment. Be prepared to spend money training your staff, developing content, cleansing data, and measuring results. Expect to spend time on organizational changes and coordinating with sales, finance, and IT departments. Hire consultants and agencies if you don’t have the necessary skills in-house – which few firms do when they start. And don’t get stuck in a rut: make a long-term plan to steadily expand use of your system after your initial deployment.
The End
I have to admit this isn’t exactly what I presented at DemandCon, although I wish it had been. The one thing I’d still want to change is to give more emphasis to the section on deployment. It’s problems with process, content, data quality and staffing that cause most marketing automation train wrecks, not the technology.
Do I smell a sequel?
I spent most of this week at the inaugural DemandCon conference in San Francisco. My presentation, How to Avoid a Marketing Automation Train Wreck, was based largely on the Marketing Automation Vendor Selection Workbook I released last month (available for free on the RaabGuide Web site). But the heart of the Workbook is a series of checklists like the one below, whereas DemandCon asked presenters to avoid long lists of bullet points. So I had to rethink the format.
After some pondering, I decided it would be more memorable to structure the presentation as a story. This made sense: deploying a marketing automation system is literally a quest, and one that can end in either triumph or the train wreck of my title. Although my actual delivery was marred by a few technical hiccups, I liked the result enough to offer a version of it here.
Prologue
A good adventure begins with a map. This one starts with our hero, a young prince, accidentally uncovering a box containing a map of the marketing technology landscape, showing where B2B marketing automation fits among other types of customer management systems. Since any story is better if you add pirates, this is a treasure map, where X marks the spot. (Sadly, one of the technical hiccups meant the DemandCon audience never saw this image, but I personally find it hilarious. Note the pirate-style headline.):
The box also holds a chart that lists the features of different types of marketing automation systems. I didn't have time to reformat it, but in the story these are presented as clues to identifying the treasure.
He also finds a set of puzzle pieces that, when assembled, present a flow chart of standard B2B marketing tasks: program setup, lead generation, nurturing, scoring, transfer to sales, and reporting. This teaches him that marketing automation is a process, not a technology.
Our Story Begins...
The young prince is intrigued by his discovery, but reluctant to take on the quest. He is moved to action by a village of marketers and salespeople crying out for more leads and better nurturing. Specific benefits include replacing point solutions with an integrated system; running larger numbers and more types of marketing programs; less reliance on non-marketing resources to manage Web content and process data; and closer integration with sales. Who could resist?
After the hero announces his decision, he is warned about the perils ahead by a wise old consultant. These include:
- buying without concrete objectives
- choosing systems based on who has the most, best, or coolest features
- only considering industry leaders
- not using scenarios to test systems against your needs
- ignoring the information you can gather from references
- not investing in training, planning, program design, content, and other resources for successful deployment
Thus forewarned, our hero starts his quest. He starts by making a plan, which means he identifies the business benefits expected from this project. These should be quantified and linked to marketing programs that will deliver them. Then he defines the requirements implied by these programs, by listing the tasks to be completed for each project and the system features needed to execute these tasks. I represented requirements as a kitten who “requires” a bowl of milk – except that now it’s a pirate kitten (my second-favorite slide in the deck. Yes, I am easily amused.)
Planning complete, the hero sets out on his search. Along the way, he meets several companions with different traits. Recognizing that he can't succeed alone, he knows he must choose one of them to help him find the treasure. His task at this stage is choosing the right one. (We somehow seem to have lost the pirates. Pity.)
These companions represent the different marketing automation systems. To choose wisely, the hero must understand the type of product he needs. I divide the B2B marketing automation world into three segments: systems serving “micro-businesses” (very small firms where marketing is a part-time job, often for the owner); small to mid-size business (a separate marketing department but typically in one location and serving one product line); and enterprises (huge companies with dozens of marketers serving multiple markets and products). Each type of business has different requirements and is served by different vendors: I won’t list the details here but they’re in the Workbook.
The Journey
Our band of travelers now faces a series of challenges, escaping from traps, crossing rivers, and beating off attacks by wild animals. At each stage a different member demonstrates his special skills. In concrete terms, this means defining scenarios based on the goals you have set for your marketing automation system. What matters is seeing how well the systems perform the tasks you need, not the ones the vendor likes to demonstrate. This means the real challenge is understanding your requirements – our hero must learn about himself before he can complete his quest. It’s a cliché but how else can I sell this to Disney?
Now the scene switches: it’s the tavern after a day of adventures, and our little group are warily eating together, trying to decide who they can trust. In other words, they’re checking references. You’ll remember that skipping references is one of the dangers I warned against. It’s true that the company will hand-pick happy customers, but you can still learn a lot if you ask the right questions:
- why did they pick the system (maybe the cared about something that’s not important to you);
- what do they see as strengths and weaknesses;
- are they using the system the same way you expect to;
- are their skills and resources similar to yours.
If a vendor can’t connect you with a reference whose situation matches your own, be very cautious.
And while we’re on the subject – don’t think social media queries replace reference checking. What comes back is typically a “yes, we love it” from highly motivated fans. Apart from dedicated grudge-holders, few businesspeople will volunteer negative feedback in social media: they can only get in trouble and there’s nothing in it for them. If you do rely on the social media, contact the people who respond and have an in-depth conversation asking the same questions you would ask the vendor’s own references.
Back to our story. The hero still hasn’t chosen on a single companion, and now the group faces the final test: it must cross the desert, storm the castle, and find the treasure. Who will stay and who will run away? Who will is a good long-term partner? The only way to find out is to move ahead.
In marketing automation terms, this means setting up a trial so you can understand the day-to-day details of working with a system. Most vendors will give you a trial license if they know you’re seriously considering their product. The trick to an effective trial is to test the system thoroughly: this means setting up programs are as demanding as those you’ll actually run once you own it and then running them from start to finish.
Here’s where all that early planning and goal-setting comes in handy, since you’ll have defined those programs already. If that sounds like too much work, bear in mind that you’ll need those programs after deployment anyway. So you might as well do the work a bit sooner and have the programs available to help make the right selection.
Triumph and Return
The group now wins the final battle and finds the treasure, only to meet a new crisis: there’s only enough water for two people to recross the desert. The hero must finally choose. In our story, this is easy because everyone else has failed or died nobly – oh, and it turns out that the remaining companion is really a disguised princess, with whom the hero has fallen in love. Didn’t see that coming, did you? Even better, she’s a pirate princess. Disney’s gonna love it.
But the real world isn’t a fairy tale. You may actually find several qualified vendors. Do what you can to make a rational choice – the Workbook provides a list of criteria to consider. But even if there is no clear winner, make a choice and get on with it. Remember your real goal is to get value from using the system, not to run the world’s finest selection project.
Epilogue
The story doesn’t end with the hero’s triumphant return. Treasure is only valuable if you spend it wisely; relationships don’t end with the wedding. It’s hard work to live happily ever after. So we have an epilogue showing how the happy couple used their riches to improve the lives of the villagers for years to come.
In marketing automation terms, this means avoiding the final mistake of underinvesting in deployment. Be prepared to spend money training your staff, developing content, cleansing data, and measuring results. Expect to spend time on organizational changes and coordinating with sales, finance, and IT departments. Hire consultants and agencies if you don’t have the necessary skills in-house – which few firms do when they start. And don’t get stuck in a rut: make a long-term plan to steadily expand use of your system after your initial deployment.
The End
I have to admit this isn’t exactly what I presented at DemandCon, although I wish it had been. The one thing I’d still want to change is to give more emphasis to the section on deployment. It’s problems with process, content, data quality and staffing that cause most marketing automation train wrecks, not the technology.
Do I smell a sequel?
Sonntag, Mai 15, 2011
DIGIDAY:TARGET, or, Yogi Berra Meets Data in the Online World.
I was scheduled to attend the DIGIDAY:TARGET conference on May 4 but wasn't able to be there. (Download the conference agenda and presentations.) Happily, my colleague and big-data guru Matt Doering was able to take my place. Here are Matt's thoughts:
Yogi Berra meets data in the online world.
At the recent Digiday:Target conference (Park Central Hotel, NYC, May 4 2011) a moderator posed the question “Which is better: More Data, Consistent Data or Data Expertise”. Not surprisingly there was a wide variety of opinions both from the panel as well as from many attendees I talked to later in the day. Many I listened to were really intrigued and conflicted by this question. To understand the real answer let us first review the pros and cons of the three possible answers.
Background
More Data – Large volumes of data from varied sources.
Pros:
• Richer data content from any given data source.
• Data sources tend to enrich each other, if properly managed.
• More likely to find the outliers that many times can be the real profit makers.
Cons:
• Many companies don’t have the resources to handle very large volumes of data.
• Lack of Metadata about data sources.
• No real experience with merging multiple data sources with different element codes and timeframes.
• Data hygiene can be an issue if you are working with a data set that is new to your organization.
Consistent Data – All data conforms to some industry standard. Any data not conforming to the model is discarded or reduced.
Pros:
• All data is easily understood and documented in a Metadata stack.
• Data hygiene is easy to define and enforce.
• Data processing performance profiles are well understood. This makes it very easy to scope a system or project.
Cons:
• Let’s admit it; all homogenized milk tastes the same. Where is the differentiation potential?
• In the process of conforming to a standard more detailed data is lost. For example if the industry standard requires that age elements be bucketed into 10 year breaks what happens if for your product offering you need 6.5 year breaks?
Data Expertise – Deep experience with very large data sets.
Pros:
• Small data, large data, inconsistent data are not a problem. Expertise can handle all these issues.
• These resources understand the role that standardized data plays in data analysis (like a good coat of primer on a wall) but also know that the real value is in what is different.
• Most data experts love to teach so the entire data IQ of you organization increases.
• Able to distinguish between dirty data and gold nuggets.
Cons:
• These resources can be hard to find. It’s not a matter of having the right degree its more of who they are. Just as simply having a degree in fine arts doesn’t make you an artist a degree in stats doesn’t make you a good data scientist. In fact one of the best data scientists I know never took a stats course.
“Its déjà vu all over again”
Yogi had it right. If, as I strongly believe, data expertise is of critical importance for the media world it’s not the first industry where this is true. A number of industries over the past 25 years have had to deal with the “big data” problem. Early examples of this are the classic CPG scanner data, pharmaceutical detailing data and financial services direct marketing data sets. All these industries faced large and diverse data issues and they all succeeded in overcoming the problem with technique not CPU.
Now it might be tempting to claim that our space generates significantly higher volumes of data or more diverse data, but is that really true? At first this appears to be true, but when you factor in the computing power available at the times it is not that far fetched to say the adjusted data volumes are actually very similar. Keep in mind that the data scientists of those days were working with computers with less horse power and memory then the average iPad used by the majority of attendees at Digiday:Target.
So where do you find this expertise? Look to the industries named above. Membership of the Direct Marketing Association and those who attended the NCDM (National Center for Database Marketing) is a good place to start. Look for people from the telecommunications industry who helped build systems to analyze Call Detail Records (CDRs). Experience in genome sequencing and pairing should grab your attention. Do these people know clicks from conversions? Probably not, but on the other hand for them more data is the breath of life. We need to recruit the talent that is out there into the industry and avoid having to reinvent it “all over again”.
Yogi Berra meets data in the online world.
At the recent Digiday:Target conference (Park Central Hotel, NYC, May 4 2011) a moderator posed the question “Which is better: More Data, Consistent Data or Data Expertise”. Not surprisingly there was a wide variety of opinions both from the panel as well as from many attendees I talked to later in the day. Many I listened to were really intrigued and conflicted by this question. To understand the real answer let us first review the pros and cons of the three possible answers.
BackgroundMore Data – Large volumes of data from varied sources.
Pros:
• Richer data content from any given data source.
• Data sources tend to enrich each other, if properly managed.
• More likely to find the outliers that many times can be the real profit makers.
Cons:
• Many companies don’t have the resources to handle very large volumes of data.
• Lack of Metadata about data sources.
• No real experience with merging multiple data sources with different element codes and timeframes.
• Data hygiene can be an issue if you are working with a data set that is new to your organization.
Consistent Data – All data conforms to some industry standard. Any data not conforming to the model is discarded or reduced.
Pros:
• All data is easily understood and documented in a Metadata stack.
• Data hygiene is easy to define and enforce.
• Data processing performance profiles are well understood. This makes it very easy to scope a system or project.
Cons:
• Let’s admit it; all homogenized milk tastes the same. Where is the differentiation potential?
• In the process of conforming to a standard more detailed data is lost. For example if the industry standard requires that age elements be bucketed into 10 year breaks what happens if for your product offering you need 6.5 year breaks?
Data Expertise – Deep experience with very large data sets.
Pros:
• Small data, large data, inconsistent data are not a problem. Expertise can handle all these issues.
• These resources understand the role that standardized data plays in data analysis (like a good coat of primer on a wall) but also know that the real value is in what is different.
• Most data experts love to teach so the entire data IQ of you organization increases.
• Able to distinguish between dirty data and gold nuggets.
Cons:
• These resources can be hard to find. It’s not a matter of having the right degree its more of who they are. Just as simply having a degree in fine arts doesn’t make you an artist a degree in stats doesn’t make you a good data scientist. In fact one of the best data scientists I know never took a stats course.
“Its déjà vu all over again”
Yogi had it right. If, as I strongly believe, data expertise is of critical importance for the media world it’s not the first industry where this is true. A number of industries over the past 25 years have had to deal with the “big data” problem. Early examples of this are the classic CPG scanner data, pharmaceutical detailing data and financial services direct marketing data sets. All these industries faced large and diverse data issues and they all succeeded in overcoming the problem with technique not CPU.
Now it might be tempting to claim that our space generates significantly higher volumes of data or more diverse data, but is that really true? At first this appears to be true, but when you factor in the computing power available at the times it is not that far fetched to say the adjusted data volumes are actually very similar. Keep in mind that the data scientists of those days were working with computers with less horse power and memory then the average iPad used by the majority of attendees at Digiday:Target.
So where do you find this expertise? Look to the industries named above. Membership of the Direct Marketing Association and those who attended the NCDM (National Center for Database Marketing) is a good place to start. Look for people from the telecommunications industry who helped build systems to analyze Call Detail Records (CDRs). Experience in genome sequencing and pairing should grab your attention. Do these people know clicks from conversions? Probably not, but on the other hand for them more data is the breath of life. We need to recruit the talent that is out there into the industry and avoid having to reinvent it “all over again”.
Mittwoch, Mai 11, 2011
Silverpop's Latest Release Targets Sophisticated Marketing Automation Buyers
Summary: Silverpop has continued to extend the marketing automation capabilities of its Engage platform. The latest release adds features that are most important to enterprise marketers.
More than a year has passed since Silverpop merged its email and marketing automation systems into a single product, Engage 8. The combined product offered advanced email but was missing some capabilities available in the previous marketing automation product. These included revenue reporting, anonymous visitor lookups, marketing calendars, and advanced scoring features such as caps on points from one event type. Clients who needed those features had to remain on the previous system (Engage B2B). Prospects who wanted them had to look elsewhere.
Silverpop has been steadily enhancing its new product since that time. The latest version, Engage 8.3, was released last month. It still doesn’t offer all the features of the oldl B2B product because Silverpop decided that some were not worth duplicating. But it does offer other capabilities that are improvements. Here are some highlights from the latest set of additions:
- multiple scores per lead. This is important in large companies that need to score leads against multiple products. It also allows different scoring rules for different customer segments. Scoring models can now include data values, such as a score that was calculated externally and imported.
- progressive profiling. Online forms can automatically remove questions a visitor has already answered and replace them with new questions in a user-specified sequence. Silverpop's form builder handles this quite elegantly, without requiring the user to embed rules or a scripting language.
- social sharing. The system can publish directly to Twitter, Facebook, and LinkedIn accounts. Content can include sharing buttons for a wide range of other systems. The system can track the number of shares and reshares for each message and identify traffic from those shares. It also captures the identity of the original sharer although this is not currently exposed.
- revenue tracking. Engage still relies on Salesforce.com to produce revenue reports. But it now feeds Salesforce all campaigns that touched the lead and flags both the original source and the campaign that generated contact information. This will allow advanced attribution analysis.
- Salesforce.com integration. Users can now embed campaign codes within a URL link, making them easier to capture. They can have the system create Salesforce.com tasks when a new lead is created, use Salesforce.com opportunity stages within campaign rules, and add leads to a Salesforce.com campaign at any step in a marketing automation program.
- enhanced security. Silverpop suffered a widely-publicized security breach in December 2010. The new release tightens access in several ways, including user-specific IP restrictions, challenges to log-ins from new IP addresses, two-factor authentication, and narrower restrictions on administrative rights. Given subsequent breaches at other firms, most recently Epsilon and Sony, it's possible that vendors and marketers will start paying more attention to security issues.
- email controls. Merging the email and marketing automation systems does have the advantage of giving B2B marketers access to features developed for Silverpop’s advanced email business. These include send-time optimization, which automatically sends campaign emails at the most effective time of day, and a “snooze” option that lets recipients halt email messages for a specified time period instead of opting out completely.
These are all valuable additions to Silverpop’s B2B capabilities. But Silverpop faces an uphill battle in regaining lost momentum and competing with the advanced analytics now touted by several competitors. Silverpop may be positioning itself to serve the upper end of the market, where companies with multiple products and world-wide organizations need advanced features like multiple scores, dynamic content, enhanced security, and high scalability. That’s a plausible strategy, although it means competing against both high-end B2B marketing automation vendors and B2C products like Neolane and Teradata/Aprimo. Given the costs of product development, it would be tough to remain a first-tier system by selling to large enterprises alone.
More than a year has passed since Silverpop merged its email and marketing automation systems into a single product, Engage 8. The combined product offered advanced email but was missing some capabilities available in the previous marketing automation product. These included revenue reporting, anonymous visitor lookups, marketing calendars, and advanced scoring features such as caps on points from one event type. Clients who needed those features had to remain on the previous system (Engage B2B). Prospects who wanted them had to look elsewhere.
Silverpop has been steadily enhancing its new product since that time. The latest version, Engage 8.3, was released last month. It still doesn’t offer all the features of the oldl B2B product because Silverpop decided that some were not worth duplicating. But it does offer other capabilities that are improvements. Here are some highlights from the latest set of additions:
- multiple scores per lead. This is important in large companies that need to score leads against multiple products. It also allows different scoring rules for different customer segments. Scoring models can now include data values, such as a score that was calculated externally and imported.
- progressive profiling. Online forms can automatically remove questions a visitor has already answered and replace them with new questions in a user-specified sequence. Silverpop's form builder handles this quite elegantly, without requiring the user to embed rules or a scripting language.
- social sharing. The system can publish directly to Twitter, Facebook, and LinkedIn accounts. Content can include sharing buttons for a wide range of other systems. The system can track the number of shares and reshares for each message and identify traffic from those shares. It also captures the identity of the original sharer although this is not currently exposed.
- revenue tracking. Engage still relies on Salesforce.com to produce revenue reports. But it now feeds Salesforce all campaigns that touched the lead and flags both the original source and the campaign that generated contact information. This will allow advanced attribution analysis.
- Salesforce.com integration. Users can now embed campaign codes within a URL link, making them easier to capture. They can have the system create Salesforce.com tasks when a new lead is created, use Salesforce.com opportunity stages within campaign rules, and add leads to a Salesforce.com campaign at any step in a marketing automation program.
- enhanced security. Silverpop suffered a widely-publicized security breach in December 2010. The new release tightens access in several ways, including user-specific IP restrictions, challenges to log-ins from new IP addresses, two-factor authentication, and narrower restrictions on administrative rights. Given subsequent breaches at other firms, most recently Epsilon and Sony, it's possible that vendors and marketers will start paying more attention to security issues.
- email controls. Merging the email and marketing automation systems does have the advantage of giving B2B marketers access to features developed for Silverpop’s advanced email business. These include send-time optimization, which automatically sends campaign emails at the most effective time of day, and a “snooze” option that lets recipients halt email messages for a specified time period instead of opting out completely.
These are all valuable additions to Silverpop’s B2B capabilities. But Silverpop faces an uphill battle in regaining lost momentum and competing with the advanced analytics now touted by several competitors. Silverpop may be positioning itself to serve the upper end of the market, where companies with multiple products and world-wide organizations need advanced features like multiple scores, dynamic content, enhanced security, and high scalability. That’s a plausible strategy, although it means competing against both high-end B2B marketing automation vendors and B2C products like Neolane and Teradata/Aprimo. Given the costs of product development, it would be tough to remain a first-tier system by selling to large enterprises alone.
Mittwoch, Mai 04, 2011
Intuit / Salesforce.com Alliance Is No April Fool's Joke
Am I the only one who missed the April 1 announcement of a strategic alliance between Salesforce.com and Intuit? Given our industry's endless nattering about whether Salesforce.com will move into marketing automation, this should have attracted more attention (or, at least, enough attention that I would hear about it sooner than I did).
In case you too missed the news, it comes down to this: Salesforce.com will be available on Intuit’s App Center and be deployed so that the Intuit and Salesforce.com databases are synchronized. For those of us used to thinking of Salesforce.com as the 900 pound gorilla, it’s disorienting to see Salesforce on the Intuit App Center, rather than the other way around.
But it does make sense. Intuit has more than 4 million customers, compared with 90,000 for Salesforce.com. The revenue differential isn’t as large ($3.5 billion for Intuit vs. $1.7 billion for Salesforce) and Salesforce.com actually has a slightly higher market cap ($17.5 billion for Salesforce.com vs. $16.5 billion for Intuit). But Intuit represents a gateway to the small business market for Salesforce.com, so it’s clear who needs whom.
What has this to do with marketing automation? Pretty much everything, I’d argue, at least for companies like Infusionsoft, OfficeAutoPilot, and Genoo, who target “micro-businesses” at the lowest end of the market. Those vendors base much of their appeal on the convenience of using one system for marketing, Web pages, CRM, and even order processing. The one thing they don’t offer is accounting, in good part because Intuit’s QuickBooks has such a dominant position.
The lack of accounting data is an important gap, because the accounting system is the ultimate source for information on customer identities and transactions. That data is important for effective marketing. Having it automatically available to Salesforce.com makes Salesforce a much more attractive marketing option for small businesses.
I suppose I should backtrack a bit here and acknowledge that I’m talking about marketing to customers – that is, people who have already made a purchase – rather than marketing to prospects or leads. Business-to-consumer marketing automation systems manage relationships with both groups, while B2B marketing automation is concerned primarily with just prospects and leads. The “micro-business” marketing automation vendors are more like B2C systemsbecause they do deal with customers as well as leads and prospects.
In other words, the Intuit / Salesforce.com alliance poses a very large threat to the “micro-business” marketing automation vendors but doesn’t have much impact on the rest of the B2B marketing automation industry, which sells to larger companies. Indeed, those larger firms are typically not QuickBooks clients at all.
But here’s the thing: let’s say that Salesforce.com does succeed in selling to a lot of Intuit clients, and in the process adds marketing automation features to serve them better. Those marketing automation features will be available to all sizes of Salesforce.com clients, including the larger ones who currently purchase marketing automation systems. Even if those firms continue to use marketing automation just to target leads and prospects, they’ll suddenly have a stronger reason to adopt Salesforce.com as their marketing platform. So marketing automation vendors who thought the Salesforce.com / Intuit deal didn’t apply to them, might want to think again.
In case you too missed the news, it comes down to this: Salesforce.com will be available on Intuit’s App Center and be deployed so that the Intuit and Salesforce.com databases are synchronized. For those of us used to thinking of Salesforce.com as the 900 pound gorilla, it’s disorienting to see Salesforce on the Intuit App Center, rather than the other way around.
But it does make sense. Intuit has more than 4 million customers, compared with 90,000 for Salesforce.com. The revenue differential isn’t as large ($3.5 billion for Intuit vs. $1.7 billion for Salesforce) and Salesforce.com actually has a slightly higher market cap ($17.5 billion for Salesforce.com vs. $16.5 billion for Intuit). But Intuit represents a gateway to the small business market for Salesforce.com, so it’s clear who needs whom.
What has this to do with marketing automation? Pretty much everything, I’d argue, at least for companies like Infusionsoft, OfficeAutoPilot, and Genoo, who target “micro-businesses” at the lowest end of the market. Those vendors base much of their appeal on the convenience of using one system for marketing, Web pages, CRM, and even order processing. The one thing they don’t offer is accounting, in good part because Intuit’s QuickBooks has such a dominant position.
The lack of accounting data is an important gap, because the accounting system is the ultimate source for information on customer identities and transactions. That data is important for effective marketing. Having it automatically available to Salesforce.com makes Salesforce a much more attractive marketing option for small businesses.
I suppose I should backtrack a bit here and acknowledge that I’m talking about marketing to customers – that is, people who have already made a purchase – rather than marketing to prospects or leads. Business-to-consumer marketing automation systems manage relationships with both groups, while B2B marketing automation is concerned primarily with just prospects and leads. The “micro-business” marketing automation vendors are more like B2C systemsbecause they do deal with customers as well as leads and prospects.
In other words, the Intuit / Salesforce.com alliance poses a very large threat to the “micro-business” marketing automation vendors but doesn’t have much impact on the rest of the B2B marketing automation industry, which sells to larger companies. Indeed, those larger firms are typically not QuickBooks clients at all.
But here’s the thing: let’s say that Salesforce.com does succeed in selling to a lot of Intuit clients, and in the process adds marketing automation features to serve them better. Those marketing automation features will be available to all sizes of Salesforce.com clients, including the larger ones who currently purchase marketing automation systems. Even if those firms continue to use marketing automation just to target leads and prospects, they’ll suddenly have a stronger reason to adopt Salesforce.com as their marketing platform. So marketing automation vendors who thought the Salesforce.com / Intuit deal didn’t apply to them, might want to think again.
Dienstag, April 26, 2011
MakesBridge Offers Powerful Features to Small Business Marketers
Summary: MakesBridge offers a full set of marketing automation features with some special strengths that will appeal especially to small companies.
I’ve written quite a bit recently about marketing systems for very small businesses – a category I’ve tentatively labeled “micro-business” and pegged at under $5 million revenue. This group of marketers has different needs from even slightly larger companies. In particular, they want a highly-integrated combination of standard marketing automation (email, landing pages and individual-level Website behavior tracking) with customer relationship management (tracking personal and telephone contacts with individuals). Leaders in the space are Infusionsoft and OfficeAutoPilot, which both also provide integrated shopping carts for e-commerce. HubSpot also has many micro-business clients but is not focused on them exclusively and – probably as a result – has a slightly different feature set: more Web traffic generation and no built-in contact management or shopping cart.
There are plenty of other vendors serving micro-businesses. I’ve previously reviewed Genoo, which supplements the standard marketing automation features with Web hosting and built-in CRM but no shopping cart. Canterris , NurtureHQ , and mKubed all provide email, Web visitor tracking, nurture campaigns, lead scoring, and CRM integration ((Salesforce.com for Canterris and NurtureHQ; its own CRM for mKubed) for under $500 per month. Canterris and mKubed also host Web forms and landing pages but NurtureHQ apparently does not. See my List of Demand Generation Vendors for other options.
MakesBridge is another contender. The company started in 2001 as an email service provider and still offers a $29.95 per month email product. It greatly expanded its features in 2010 and now offers a marketing automation system starting at $500 per month. This includes the full rig: outbound email, multi-step nurture campaigns, landing pages and forms, lead scoring, Web visitor tracking (licensed from VisiStat and quite impressive), and a sales automation module that can work as a stand-alone CRM system or integrate with Salesforce.com, NetSuite, Google Apps, or Capsule CRM, a $12 per month per user system also aimed at small business. There’s no shopping cart or Web site hosting but I don’t yet consider those standard features, even for micro-business systems.
MakesBridge does a particularly good job of taming the mass of Web pages that are critical to reacting to lead behaviors. It does this by letting users write rules that reference sets of Web pages rather than individual pages. This can be done by either assigning a shared label to several pages or by assigning page attributes and selecting on those. This is a helpful middle ground between rules that treat all pages the same (e.g. “visited any Web page”) and those that require users to list a specific page or several individual pages. These rules can be used in segmentation, lead scoring, and sales alerts.
The system also has a solid campaign engine, which breaks campaigns into steps and allows multiple options within each step. Each option has a filter that determines which leads are eligible, in addition to actions and an execution schedule that apply to those leads. Users can view reports on performance for each step and for each option within the step. A “circuit breaker” enforces limits on the total number of emails sent during any time period, alerting the user and limiting the damage from what MakesBridge calls "automation run wild".
MakesBridge also supports automated direct mail production, another feature favored by micro-business marketers. For this, the company has integrated with Cloud2You, a Salesforce.com App Exchange partner that loads selected records directly into templates to produce personalized mailing pieces. Cloud2You handles the actual printing and mailing without any additional effort by the user. Mailings can be triggered by steps within a MakesBridge campaign,
The sales automation module gives salespeople access to detailed information about their leads, including their current campaigns. Salespeople can remove a lead from a campaign, suspend the campaign, or skip a particular message. Although MakesBridge is designed to integrate with external CRM products, some clients use its sales automation module as their primary CRM system.
Pricing of MakesBridge is based on the modules used, number of users, email volume, and number of leads in the database. The system currently has more than 150 clients. Most are small businesses but some are large corporations.
I’ve written quite a bit recently about marketing systems for very small businesses – a category I’ve tentatively labeled “micro-business” and pegged at under $5 million revenue. This group of marketers has different needs from even slightly larger companies. In particular, they want a highly-integrated combination of standard marketing automation (email, landing pages and individual-level Website behavior tracking) with customer relationship management (tracking personal and telephone contacts with individuals). Leaders in the space are Infusionsoft and OfficeAutoPilot, which both also provide integrated shopping carts for e-commerce. HubSpot also has many micro-business clients but is not focused on them exclusively and – probably as a result – has a slightly different feature set: more Web traffic generation and no built-in contact management or shopping cart.
There are plenty of other vendors serving micro-businesses. I’ve previously reviewed Genoo, which supplements the standard marketing automation features with Web hosting and built-in CRM but no shopping cart. Canterris , NurtureHQ , and mKubed all provide email, Web visitor tracking, nurture campaigns, lead scoring, and CRM integration ((Salesforce.com for Canterris and NurtureHQ; its own CRM for mKubed) for under $500 per month. Canterris and mKubed also host Web forms and landing pages but NurtureHQ apparently does not. See my List of Demand Generation Vendors for other options.
MakesBridge is another contender. The company started in 2001 as an email service provider and still offers a $29.95 per month email product. It greatly expanded its features in 2010 and now offers a marketing automation system starting at $500 per month. This includes the full rig: outbound email, multi-step nurture campaigns, landing pages and forms, lead scoring, Web visitor tracking (licensed from VisiStat and quite impressive), and a sales automation module that can work as a stand-alone CRM system or integrate with Salesforce.com, NetSuite, Google Apps, or Capsule CRM, a $12 per month per user system also aimed at small business. There’s no shopping cart or Web site hosting but I don’t yet consider those standard features, even for micro-business systems.
MakesBridge does a particularly good job of taming the mass of Web pages that are critical to reacting to lead behaviors. It does this by letting users write rules that reference sets of Web pages rather than individual pages. This can be done by either assigning a shared label to several pages or by assigning page attributes and selecting on those. This is a helpful middle ground between rules that treat all pages the same (e.g. “visited any Web page”) and those that require users to list a specific page or several individual pages. These rules can be used in segmentation, lead scoring, and sales alerts.
The system also has a solid campaign engine, which breaks campaigns into steps and allows multiple options within each step. Each option has a filter that determines which leads are eligible, in addition to actions and an execution schedule that apply to those leads. Users can view reports on performance for each step and for each option within the step. A “circuit breaker” enforces limits on the total number of emails sent during any time period, alerting the user and limiting the damage from what MakesBridge calls "automation run wild".
MakesBridge also supports automated direct mail production, another feature favored by micro-business marketers. For this, the company has integrated with Cloud2You, a Salesforce.com App Exchange partner that loads selected records directly into templates to produce personalized mailing pieces. Cloud2You handles the actual printing and mailing without any additional effort by the user. Mailings can be triggered by steps within a MakesBridge campaign,
The sales automation module gives salespeople access to detailed information about their leads, including their current campaigns. Salespeople can remove a lead from a campaign, suspend the campaign, or skip a particular message. Although MakesBridge is designed to integrate with external CRM products, some clients use its sales automation module as their primary CRM system.
Pricing of MakesBridge is based on the modules used, number of users, email volume, and number of leads in the database. The system currently has more than 150 clients. Most are small businesses but some are large corporations.
Mittwoch, April 20, 2011
Argyle Social Helps to Track Social Media Results
Summary: Argyle Social offers social media marketing with above-average features for tracking results.
I’ve had a couple of conversations in recent months with Argyle Social, one of the zillions* of companies offering social media marketing tools. Argyle’s particular focus is making social media measurable. It does this in two ways:
- embedding trackable URLs in social messages. The system provides a social media publishing tool that automatically creates links with embedded Google-Analytics-compatible identifiers for campaign, content, and source. This overcomes the fact that social media traffic often can’t be tied to a referring Web site. The identifiers can also include custom parameters for other Web analytics packages. The URLs are sent to an Argyle-controlled destination which logs the traffic before redirecting the Web visitor to the original target page.
- adding cookies to visitors’ computers when they view Argyle-generated social media content, and checking for those cookies when visitors reach a “conversion” page (i.e., make a purchase or take some other targeted action). The conversion pages can be created outside of Argyle but must contain Argyle tags. Results are used to identify visitors who are "influenced" by social media.
Argyle uses its tracking features to generate reports on direct responses to social media campaigns (i.e., clicks on Argyle-generated messages) and on influenced responses (i.e., conversions of visitors whose cookie shows they previously saw social content). Although this is far from the ideal of measuring the true incremental impact of a campaign, it's a step in the right direction. It also provides data that could be the foundation of a more sophisticated analysis.
These features are not technically difficult, so it's quite possible they're available in some other social media systems. But that matters less than knowing they're available in Argyle if you need them.
Argyle's tracking features are combined with a publishing interface that lets users set up accounts, create posts, and deliver them immediately or on schedule. It can currently post to Facebook, Twitter and Linked In. It can also scan for social messages containing specified keywords and store these messages for future reference. The publishing features don’t yet include enterprise-level capabilities such as response templates, approval work flows, case management, or relationship tracking, although these are on the horizon. A rules-based inbox filtering feature will launch tomorrow.
Argyle launched its product at the end of last year and is nearing 100 customers. A basic edition (three users, ten social properties, one conversion goal, one inbox filtering rule) is priced at $149 per month and the advanced edition (five users, unlimited social properties, five goals, ten advanced rules) costs $499 per month.
__________________________________________________________________________________
*at last count. Here are the first three lists I found via a Google search, plus others whose authors were SEO-savvy enough to find a nice, round 100, and one with a cool infographic:
[INFOGRAPHIC] What Are The Best Social Media Monitoring Tools?
22 Social Media Marketing Management Tools (Lee Odden)
42+ Social Media Marketing Tools (Joe Pulizzi)
List of Social Media Management Systems (SMMS) (Jeremiah Owyang)
100+ Social Media Monitoring Tools (Pam Dyer)
Top 100 social media monitoring tools (juanmarketing)
I’ve had a couple of conversations in recent months with Argyle Social, one of the zillions* of companies offering social media marketing tools. Argyle’s particular focus is making social media measurable. It does this in two ways:
- embedding trackable URLs in social messages. The system provides a social media publishing tool that automatically creates links with embedded Google-Analytics-compatible identifiers for campaign, content, and source. This overcomes the fact that social media traffic often can’t be tied to a referring Web site. The identifiers can also include custom parameters for other Web analytics packages. The URLs are sent to an Argyle-controlled destination which logs the traffic before redirecting the Web visitor to the original target page.
- adding cookies to visitors’ computers when they view Argyle-generated social media content, and checking for those cookies when visitors reach a “conversion” page (i.e., make a purchase or take some other targeted action). The conversion pages can be created outside of Argyle but must contain Argyle tags. Results are used to identify visitors who are "influenced" by social media.
Argyle uses its tracking features to generate reports on direct responses to social media campaigns (i.e., clicks on Argyle-generated messages) and on influenced responses (i.e., conversions of visitors whose cookie shows they previously saw social content). Although this is far from the ideal of measuring the true incremental impact of a campaign, it's a step in the right direction. It also provides data that could be the foundation of a more sophisticated analysis.
These features are not technically difficult, so it's quite possible they're available in some other social media systems. But that matters less than knowing they're available in Argyle if you need them.
Argyle's tracking features are combined with a publishing interface that lets users set up accounts, create posts, and deliver them immediately or on schedule. It can currently post to Facebook, Twitter and Linked In. It can also scan for social messages containing specified keywords and store these messages for future reference. The publishing features don’t yet include enterprise-level capabilities such as response templates, approval work flows, case management, or relationship tracking, although these are on the horizon. A rules-based inbox filtering feature will launch tomorrow.
Argyle launched its product at the end of last year and is nearing 100 customers. A basic edition (three users, ten social properties, one conversion goal, one inbox filtering rule) is priced at $149 per month and the advanced edition (five users, unlimited social properties, five goals, ten advanced rules) costs $499 per month.
__________________________________________________________________________________
*at last count. Here are the first three lists I found via a Google search, plus others whose authors were SEO-savvy enough to find a nice, round 100, and one with a cool infographic:
[INFOGRAPHIC] What Are The Best Social Media Monitoring Tools?
22 Social Media Marketing Management Tools (Lee Odden)
42+ Social Media Marketing Tools (Joe Pulizzi)
List of Social Media Management Systems (SMMS) (Jeremiah Owyang)
100+ Social Media Monitoring Tools (Pam Dyer)
Top 100 social media monitoring tools (juanmarketing)
Mittwoch, April 13, 2011
Step-by-Step Guide to Selecting the Right Marketing Automation System - Part 2
Yesterday' post described the first three steps in Raab Associates' vendor selection process: defining requirements, researching options, and testing vendors against scenarios. This post lists the four steps needed to complete the task. As before, there's a worksheet for each step that can be a model for your own, more detailed version. And remember, the complete set is available for free in our Vendor Selection Workbook in the Resource Library at the Raab Guide Web site.
4. Talk To References
This is an often-overlooked source of insight. The question isn’t whether the references are happy, but whether your situations are similar enough that you’re likely to be happy as well. Find out whether the reference is using the system functions you care about, how long they took to get started, the amount of training and process change required, what problems they had, and how the vendor responded.
5. Consider A Trial
Nearly all marketing automation vendors will let you try their system for a limited period. Trials are a great way to learn what it’s really like to use a system, but only if they are managed effectively. This means you need to invest in training and then set up and execute actual projects. As with scenario demonstrations, you may still rely on the vendor to handle some of the more demanding aspects of the project, but, again, make sure you see how hard it will eventually be to do them for yourself.
6. Make A Decision
Don’t let the selection process drag on. Selection is a means to an end, not a goal in itself. Unless you have very specialized needs, there are probably several marketing automation systems that will meet your requirements. Look at your key criteria and assess how well each vendor matches them – bearing in mind that a system can be too powerful as well as too simple. Once you’ve found one that you are confident will be sufficient, go ahead and buy it. Then you can start on what’s really important: better marketing results.
7. Invest In Deployment
Marketing automation systems allow major improvements in marketing results. But those improvements require more than just a new system. If you don’t already have a formal description of the stages that prospects move through to become buyers, build one and instrument your systems to measure it. Use the stages as a framework to plan, design and develop a balanced set of marketing programs. Invest in the staff training and content to execute those programs successfully. Document and improve internal marketing processes. Work closely with sales to define lead scoring rules, hand-off mechanisms and service levels, and ways to capture results. Build measurement systems and use them to hold marketers at every level of the department responsible for results they control. Bring in outside resources, such as agencies and consultants, when you lack the internal expertise or time to do the work in-house.
4. Talk To References
This is an often-overlooked source of insight. The question isn’t whether the references are happy, but whether your situations are similar enough that you’re likely to be happy as well. Find out whether the reference is using the system functions you care about, how long they took to get started, the amount of training and process change required, what problems they had, and how the vendor responded.
| Issue | Questions to ask |
| System fit vs. my needs | What kinds of programs do you run with the system? |
| How many programs do you run each month? | |
| How many people at your company use the system? | |
| System reliability | How often has the system been unavailable? |
| What kinds of bugs have you run into? | |
| Ease of use | How much training did you need to use the system? |
| What kinds of tasks need outside help to accomplish? | |
| How long does it take to set up different kinds of programs? | |
| Vendor support | How well does the vendor respond when you ask for help? |
| How quickly do problems get solved? | |
| Does the vendor ever offer assistance before you ask? | |
| What help does the vendor provide with email deliverability? | |
| Cost | Did you negotiate any special pricing? |
| Did you pay extra for implementation and on-going support? | |
| Were there any unexpected costs after you started? |
5. Consider A Trial
Nearly all marketing automation vendors will let you try their system for a limited period. Trials are a great way to learn what it’s really like to use a system, but only if they are managed effectively. This means you need to invest in training and then set up and execute actual projects. As with scenario demonstrations, you may still rely on the vendor to handle some of the more demanding aspects of the project, but, again, make sure you see how hard it will eventually be to do them for yourself.
| What you can learn from a trial | How hard it is to install the system |
| How hard it is to set up a campaign | |
| How hard it is to make changes and reuse materials | |
| What features are available or missing (if you test them) | |
| Quality of training classes and materials (if you try them) | |
| What you can’t learn from a trial | How the system handles large volumes of data, users, etc. |
| Results from complex or long-running campaigns | |
| Accuracy of scoring and reports | |
| Quality of customer service and support | |
| Quality of vendor partners (agencies, integrators, etc.) |
6. Make A Decision
Don’t let the selection process drag on. Selection is a means to an end, not a goal in itself. Unless you have very specialized needs, there are probably several marketing automation systems that will meet your requirements. Look at your key criteria and assess how well each vendor matches them – bearing in mind that a system can be too powerful as well as too simple. Once you’ve found one that you are confident will be sufficient, go ahead and buy it. Then you can start on what’s really important: better marketing results.
| Selection criteria | Key factors | Vendor Fit | ||
| Too Little | Appropriate | Too Much | ||
| Functions | Outbound email | |||
| Landing page and forms | ||||
| Web behavior tracking | ||||
| Lead scoring | ||||
| Multi-step campaigns | ||||
| Sales integration | ||||
| Reporting and analysis | ||||
| Usability | Easy to learn | |||
| Efficient to use | ||||
| Technology | Easy installation | |||
| Flexibility | ||||
| Cost | Direct (software and support) | |||
| Indirect (staff, training, services) | ||||
| Predictable | ||||
| Expansion costs | ||||
| Vendor | Staff resources | |||
| Product plans | ||||
| Financial stability | ||||
7. Invest In Deployment
Marketing automation systems allow major improvements in marketing results. But those improvements require more than just a new system. If you don’t already have a formal description of the stages that prospects move through to become buyers, build one and instrument your systems to measure it. Use the stages as a framework to plan, design and develop a balanced set of marketing programs. Invest in the staff training and content to execute those programs successfully. Document and improve internal marketing processes. Work closely with sales to define lead scoring rules, hand-off mechanisms and service levels, and ways to capture results. Build measurement systems and use them to hold marketers at every level of the department responsible for results they control. Bring in outside resources, such as agencies and consultants, when you lack the internal expertise or time to do the work in-house.
| Goal | Tasks |
| Balanced set of marketing programs | Define lead lifecycle (buying process and buyer roles) |
| Map existing programs to process stages and identify gaps | |
| Prioritize new programs to close gaps | |
| Execute programs and measure results | |
| Refine programs with versions for different segments | |
| Measurement | Track leads through stages in the buying process |
| Import revenue from sales systems | |
| Link revenue to lead source (acquisition programs) | |
| Measure incremental impact (nurture programs) | |
| Project future revenue from current lead inventory | |
| Process management | Define processes to execute marketing programs |
| Identify tasks and responsibilities within each process | |
| Define measures to capture task performance | |
| Assess existing processes and possible improvements | |
| Monitor execution, test improvements, check results, repeat | |
| Sales alignment | Identify key contacts between sales and marketing |
| Agree on process for lead qualification, transfer to sales | |
| Agree on measures for lead quality, revenue attribution | |
| Deploy agreed processes, monitor results, review regularly | |
| Staff training | Define skills needed to deploy new system |
| Assess existing staff skills and identify gaps | |
| Plan initial training to close gaps | |
| Plan on-going training to maintain and expand skills |
Dienstag, April 12, 2011
Step-by-Step Guide to Selecting the Right Marketing Automation System - Part 1
Choosing a marketing automation system is a major decision. A disciplined selection process is essential to make a sound selection. This series of posts presents the seven-step methodology we use at Raab Associates, along with related worksheets. The first three are below.
For a complete list of the steps, worksheets, and background materials, visit the Raab Guide Website and download the Vendor Selection Workbook from the Resource Library (registration required).
1. Define Requirements
Create a list of your goals in buying the system. Relate these to financial values when possible. Then define how you’ll use the system to meet these goals, being as specific as you can about the actual processes involved. Be sure to include processes beyond what you do already: one of the reasons you’re looking at marketing automation is to expand what your department can accomplish. Your requirements are based on the tasks you must perform to meet your goals.
2. Research Your Options
Raab Associates’ B2B Marketing Automation Vendor Selection Tool (VEST) provides a good starting point for matching possible vendors to your requirements. In particular, match the scale and sophistication of your marketing operations to the different buyer segments used in the report. Bear in mind that company size alone doesn’t necessary predict the depth of your requirements: small businesses can run complex marketing programs, and large business programs may be simple.
3. Test Vendors Against Scenarios
Develop scenarios that describe actual marketing projects you expect to run through the system, and have the most promising vendors demonstrate how they would execute them. Scenarios based on your own needs are critical for understanding how well each system would function in your own environment. Be sure that some scenarios describe your more complicated processes, since these are most likely to highlight differences among systems. If vendor staff executes the scenarios for you, be sure to understand how much the vendor built in advance. This ensures that you get an accurate sense of the total work effort involved.
The next post in this series will present additional steps in our process.
For a complete list of the steps, worksheets, and background materials, visit the Raab Guide Website and download the Vendor Selection Workbook from the Resource Library (registration required).
1. Define Requirements
Create a list of your goals in buying the system. Relate these to financial values when possible. Then define how you’ll use the system to meet these goals, being as specific as you can about the actual processes involved. Be sure to include processes beyond what you do already: one of the reasons you’re looking at marketing automation is to expand what your department can accomplish. Your requirements are based on the tasks you must perform to meet your goals.
| Goals | Related Requirements |
| Generate more leads | Manage online and offline advertising campaigns |
| Import email address lists and send personalized emails | |
| Monitor and publish to social media | |
| Build and deploy landing pages to capture responses | |
| Use IP address to identify the company of Web site visitors | |
| More effective nurturing | Capture the source and Web site activities of each visitor |
| Create Web forms to gather information about visitors | |
| Score visitors based on form responses and Web behaviors | |
| Execute multi-step campaigns tailored to different groups | |
| Use visitor behavior to trigger campaigns and other actions | |
| Better sales integration | Synchronize data between sales and marketing systems |
| Send leads to sales based on lead score and actions | |
| Send alerts to sales based on Web site behaviors | |
| Report on revenue generated by leads from marketing | |
| More efficient marketing operations | Store marketing materials and share across programs |
| Track planned and actual costs of marketing programs | |
| Manage tasks and approvals during program development |
2. Research Your Options
Raab Associates’ B2B Marketing Automation Vendor Selection Tool (VEST) provides a good starting point for matching possible vendors to your requirements. In particular, match the scale and sophistication of your marketing operations to the different buyer segments used in the report. Bear in mind that company size alone doesn’t necessary predict the depth of your requirements: small businesses can run complex marketing programs, and large business programs may be simple.
| Company Type | Key System Features |
| Micro-business | Outbound email and multi-step nurture campaigns |
| Landing pages and forms | |
| Built-in sales and service features | |
| Built-in or integrate with third party ecommerce and shopping cart | |
| Small to mid-size business | Outbound email and multi-step nurture campaigns |
| Landing pages and forms | |
| Web site visitor tracking | |
| Lead scoring (one score per lead) | |
| Integrate with external sales automation system | |
| Large business | Outbound email and multi-step nurture campaigns |
| Landing pages and forms | |
| Web site visitor tracking | |
| Lead scoring (multiple scores per lead) | |
| Integrate with external sales automation system | |
| Manage marketing budgets, program tasks and approvals | |
| Add custom tables with data from many sources | |
| Limit different users to different tasks and programs |
3. Test Vendors Against Scenarios
Develop scenarios that describe actual marketing projects you expect to run through the system, and have the most promising vendors demonstrate how they would execute them. Scenarios based on your own needs are critical for understanding how well each system would function in your own environment. Be sure that some scenarios describe your more complicated processes, since these are most likely to highlight differences among systems. If vendor staff executes the scenarios for you, be sure to understand how much the vendor built in advance. This ensures that you get an accurate sense of the total work effort involved.
| Scenario | Steps |
| Outbound email campaign | Import list from CSV file, from Excel |
| Compose personalized emails with embedded graphics | |
| Create landing page with data entry form | |
| Set automated email response to form submissions | |
| Set rules to score leads and send qualified leads to sales | |
| Report on results: sent, opened, clicked, completed form | |
| Nurture campaign | Set start and end date for campaign |
| Set rules to select leads, based on attributes and behaviors | |
| Set priority of campaign vs. other campaigns | |
| Define multi-step flow with wait periods between steps | |
| Set rules for different treatments for segments within steps | |
| Set rules to score leads and send qualified leads to sales | |
| Create emails, landing pages, and forms | |
| Report on results including leads to sales and revenue | |
| Revenue reporting | Define stages in lead lifecycle |
| Define rules to assign leads to lifecycle stages | |
| Report on movement of leads through lifecycle stages | |
| Set up process to import revenue from sales system | |
| Define rules to link revenue to campaigns | |
| Define rules to estimate incremental revenue per campaign | |
| Report on revenue generated per campaign | |
| Capture campaign costs | |
| Report on campaign revenue vs. campaign cost |
The next post in this series will present additional steps in our process.
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