Summary: LoopFuse offers attractive but limited demand generation functions at an easy-to-swallow price.
It’s been nearly a year since I took my first close look at the LoopFuse OneView demand generation system. I didn't write about them because the vendor was planning some major improvements and it made more sense to publish a review after these in place. We reconnected in December and the product is now ready for its close up.
The resulting picture is much prettier than before because the main changes in LoopFuse have been improvements in the user interface. It is now an attractive system with wizards to drive major functions and extensive in-line help messages to clarify next steps. The help functions are built with Helpstream customer support technology, which also provides a knowledge base and online community.
The process to set up multi-step campaigns (which the vendor calls “lead flows”) is now quite straightforward. Users first create the lead flow and link it to recipient and suppression lists that will determine who enters the flow. They then define the flow itself by following prompts to add nodes for activities, conditional decisions, waiting periods and retrial periods. (A retrial resembled a waiting period except that the system keeps retesting the previous condition. For example, the retrial node might check every hour to see whether someone has responded to a previous email. Come to think of it, it would probably make more sense to build the retesting into the conditional node itself.)
Esthetics aside, however, the actual capabilities of the lead flows are still somewhat limited. The only direct action available in an activity node is to send an email; all other options involve updates to the CRM system such as adding a lead, changing data, or assigning an activity. This leaves out other tasks that I consider basic, such as updating data within the LoopFuse database, removing the lead from the flow, or adding the lead to a list. (In the case of data changes, the omission is intentional: Loopfuse argues that such changes should be made in the CRM system and replicated into Loopfuse).
The conditional nodes make up some of the deficit. For example, failure to meet the node condition can remove the lead from the flow. (An activity to remove leads from a different flow will be available around next April.) The conditional nodes can check for several specific conditions, such as email responses, Web page visits, CRM lead status, data values and lead scores. These probably serve most purposes, but some users may be frustrated by the inability to combine several conditions within a single node or to specify more than two branches as outcomes.
Leads enter LoopFuse lead flows when they join the associated recipient list. Lists can include leads with specified data values on the lead record, that originate from a particular Web site or form, or that visited a particular Web page. Several conditions can be combined and lists can be static or regularly updated. But lists can't be selected based on lead scores, email response or activity levels. Again, processes that depended on these would need to incorporate them through conditional nodes in the lead flows.
Lead scores themselves can be based on data values in the lead record, email response or Web pages visited. However, the system cannot base scores on activity patterns such as "three Web site visits in the past week". The system stores one score per lead. Scores are recalculated every hour, which does not support immediate reaction to score-changing events.
LoopFuse provides a graphic email designer that can generate both text and HTML versions. Emails can be personalized with data from the lead record, including the assigned salesperson if available. But data from account or opportunity tables is not available, even though it’s imported from CRM. Nor does LoopFuse support any type of A/B testing, either in the email definition or its lead flows. Each email is tied directly to just one email “campaign”, although the email campaigns themselves can be reused in multiple lead flows.
Unlike most demand generation vendors, LoopFuse does not host landing pages or Web forms for its clients. Instead, the vendor provides a wizard that reads existing, externally hosted forms and generates modified versions that will post data into the LoopFuse database. Another wizard helps users to generate HTML forms from scratch. Either way, the new forms must be copied into pages hosted outside of LoopFuse.
LoopFuse will also provide tags that can be placed on other pages on a client’s Web site to track and report on Web page visits. It lets it generate some page-oriented Web analytics reports similar to Google Analytics.
Reporting is another area that LoopFuse has significantly strengthened in the past year. In addition to Web analytics, it provides detailed reports on Web site visitors, including reports that link anonymous visitors to their company through their IP address. The system also tracks lead movement through sales funnel based on a combination of its own data and information imported from CRM. Other reports show results from email campaigns and lead capture forms.
LoopFuse also gives salespeople a report showing recent activities by their assigned leads, allowing them to drill into each lead for details. A “company dashboard” report lets both sales people and marketers see all visitors from a particular company, again based on IP address. The report shows both known and anonymous visitors and lets users connect directly with external databases including Hoovers, Jigsaw and Zoominfo to look up additional information. LoopFuse can also alert salespeople by email when high-priority accounts perform specified activities captured in the system.
LoopFuse does a particularly good job with CRM integration. Because its sales process depends heavily on free trials, the company has developed a self-service wizard that guides users through the process of connecting to Salesforce.com, including an automated check for whether LoopFuse has been granted access permissions in the client’s Salesforce.com installation. (Apparently this is a very common omission.) Users have field-by-field control over how data conflicts between the systems are resolved. In addition to Salesforce.com, the vendor has a standard integration for SugarCRM.
Pricing in LoopFuse is based on email and Web page volume, with no limit on the number of names in the system database. This is unusual but not unique: Pardot and LeadLife take a similar approach. (See my recent list of demand generation vendors for an overview of competitive pricing.) Rates are quite aggressive: $750 per month for 50,000 emails and page views combined, or $1,250 per month for a much more generous 250,000 total.
LoopFuse was founded in 2007 although it was largely in stealth mode through early 2009. The company currently has more than 50 paid clients.
Tuesday, December 29, 2009
Monday, December 14, 2009
Spredfast Offers Systematic Management for Social Media Campaigns
Summary: Social Agency’s Spredfast helps marketers schedule social media campaigns the same way they schedule paid advertising. Cool.
It seems like common courtesy to listen to an existing conversation before jumping in with a comment. If social media worked the same way, companies would first buy a monitoring system to track what’s being said, followed by tools to respond to comments made by others. Only later would they initiate conversations and, eventually, provide tools to help their friends spread the word.
Silly me. I should have known that marketers talk first and listen later.
I’m not talking about personal style, although the decibel level at any marketing conference speaks for itself. But a recent eMarketer article B2B Marketers to Increase Social Spend cited two surveys that showed this is also a matter of policy.
Specifically, a study from Visible Technologies and SiriusDecisions found the most common use for social media was to “generate awareness” (25%), while another study in B2B Magazine found the top use for social networks was “thought leadership” (60%). True listening ranked fifth in the Visible Technologies/SiriusDecision survey (“monitor and respond” at 14%), and third in the B2B Magazine survey (“customer feedback” at 46%).
On reflection, this makes sense. Marketers are primarily interested in getting out their messages. Perhaps this is an old habit that will change in a customer-driven world. But I suspect that marketing results will always be driven by activity, and results are ultimately what matter. So I’ve now revised my expected sequence of social media activities to start with broadcast, only then followed by monitor, respond, initiate individual conversations and empower advocates.
Armed with this insight, I was much less surprised when Kenneth Cho of social marketing agency Social Agency told me that his new social media campaign tool Spredfast had been purchased immediately after release by major companies including AOL, IBM, HP, Cisco and Porter Novelli. Although I’ve seen plenty of “listening platforms” like Radian6, Alterian Techrigy and Scout Labs, I hadn't previously seen a system aimed primarily at managing outbound social messages. (Now that I'm looking, though, I find that ObjectiveMarketer seems to offer something similar.)
Of course, the listening platforms can also post social media messages, as can the social media features now found in many marketing automation systems. What distinguishes Spredfast is that marketers can schedule their posts through the life of a social media campaign, rather than simply replying or initiating conversations on demand. Spredfast supports on-demand posting too.
Another key feature is that Spredfast supports multiple “voices” of actual or constructed individuals, each having accounts in multiple channels (Facebook, Twitter, blogs, etc.). The campaign calendar lays out of scheduled events by all voices over time, and is color-coded to show whether a particular event has already been delivered, is ready to go, or still needs approved content. This looks strikingly similar to the media plan for a flight of broadcast ads and serves very much the same purpose.
Users can drill into an event to add the content itself including bit.ly links that allow the system to track the click-through. One particularly nice feature is that when users assign the same content to multiple events, the system will automatically create different bit.ly links for each event. This makes it easy to track results for each event independently.
Spredfast's developers also recognized that large companies will have many different people working on different aspects of a project. Users can be assigned rights to specific campaigns, voices and events, with precise control over who can view, edit and approve content. Pricing is based on the number of campaigns, not users, so large organizations can incorporate as many people as needed.
As the bit.ly tags suggest, Spredfast also pays substantial attention to measurement. It provides three major summary metrics:
- activity (how much content the system is publishing),
- reach (the number of views, friends, followers, subscribers, etc.), and
- engagement (numbers of comments, retweets, likes, etc.).
Top-level reports summarize these by campaign and let users drill down to see detailed statistics by channel and voice and, ultimately, the actual content such as comments or reviews.
The system archives content and responses so they remain available even after they are dropped from the social media platforms that originally carried them. In addition to cumulative statistics, Spredfast displays daily statistics for the past seven days, giving a sense of trends.
Perhaps wisely, Spredfast's developers drew the line at reporting the raw numbers for its metrics. Users who want more elaborate scoring, perhaps applying different weights to different kinds of activities, can export the raw data and calculate outside the system. Similarly, Spredfast makes no attempt at relating social media programs to business results such as leads or revenue.
The system does provide what Cho called a “minimalist” listening platform, which can automatically search across public listening tools (Google, Google Blog Search, Social Mention, Twitter, Boardreader, Bing) for key words, and present any results so users can review and republish or reply to them. It also provides an RSS reader for feeds selected by the user, as well as a site indexer that can show the frequency of different terms in user-specified blogs as a word cloud. This helps users tailor their posts to encourage coverage.
Spredfast began its public beta in mid-November. The system is a vendor-hosted service. It is available in a free version with limited functionality; a $50 per month standard version with one campaign, no collaboration and no metrics after the first month; and $250 per month enterprise version supporting all features for up to three campaigns.
It seems like common courtesy to listen to an existing conversation before jumping in with a comment. If social media worked the same way, companies would first buy a monitoring system to track what’s being said, followed by tools to respond to comments made by others. Only later would they initiate conversations and, eventually, provide tools to help their friends spread the word.
Silly me. I should have known that marketers talk first and listen later.
I’m not talking about personal style, although the decibel level at any marketing conference speaks for itself. But a recent eMarketer article B2B Marketers to Increase Social Spend cited two surveys that showed this is also a matter of policy.
Specifically, a study from Visible Technologies and SiriusDecisions found the most common use for social media was to “generate awareness” (25%), while another study in B2B Magazine found the top use for social networks was “thought leadership” (60%). True listening ranked fifth in the Visible Technologies/SiriusDecision survey (“monitor and respond” at 14%), and third in the B2B Magazine survey (“customer feedback” at 46%).
On reflection, this makes sense. Marketers are primarily interested in getting out their messages. Perhaps this is an old habit that will change in a customer-driven world. But I suspect that marketing results will always be driven by activity, and results are ultimately what matter. So I’ve now revised my expected sequence of social media activities to start with broadcast, only then followed by monitor, respond, initiate individual conversations and empower advocates.
Armed with this insight, I was much less surprised when Kenneth Cho of social marketing agency Social Agency told me that his new social media campaign tool Spredfast had been purchased immediately after release by major companies including AOL, IBM, HP, Cisco and Porter Novelli. Although I’ve seen plenty of “listening platforms” like Radian6, Alterian Techrigy and Scout Labs, I hadn't previously seen a system aimed primarily at managing outbound social messages. (Now that I'm looking, though, I find that ObjectiveMarketer seems to offer something similar.)
Of course, the listening platforms can also post social media messages, as can the social media features now found in many marketing automation systems. What distinguishes Spredfast is that marketers can schedule their posts through the life of a social media campaign, rather than simply replying or initiating conversations on demand. Spredfast supports on-demand posting too.
Another key feature is that Spredfast supports multiple “voices” of actual or constructed individuals, each having accounts in multiple channels (Facebook, Twitter, blogs, etc.). The campaign calendar lays out of scheduled events by all voices over time, and is color-coded to show whether a particular event has already been delivered, is ready to go, or still needs approved content. This looks strikingly similar to the media plan for a flight of broadcast ads and serves very much the same purpose.
Users can drill into an event to add the content itself including bit.ly links that allow the system to track the click-through. One particularly nice feature is that when users assign the same content to multiple events, the system will automatically create different bit.ly links for each event. This makes it easy to track results for each event independently.
Spredfast's developers also recognized that large companies will have many different people working on different aspects of a project. Users can be assigned rights to specific campaigns, voices and events, with precise control over who can view, edit and approve content. Pricing is based on the number of campaigns, not users, so large organizations can incorporate as many people as needed.
As the bit.ly tags suggest, Spredfast also pays substantial attention to measurement. It provides three major summary metrics:
- activity (how much content the system is publishing),
- reach (the number of views, friends, followers, subscribers, etc.), and
- engagement (numbers of comments, retweets, likes, etc.).
Top-level reports summarize these by campaign and let users drill down to see detailed statistics by channel and voice and, ultimately, the actual content such as comments or reviews.
The system archives content and responses so they remain available even after they are dropped from the social media platforms that originally carried them. In addition to cumulative statistics, Spredfast displays daily statistics for the past seven days, giving a sense of trends.
Perhaps wisely, Spredfast's developers drew the line at reporting the raw numbers for its metrics. Users who want more elaborate scoring, perhaps applying different weights to different kinds of activities, can export the raw data and calculate outside the system. Similarly, Spredfast makes no attempt at relating social media programs to business results such as leads or revenue.
The system does provide what Cho called a “minimalist” listening platform, which can automatically search across public listening tools (Google, Google Blog Search, Social Mention, Twitter, Boardreader, Bing) for key words, and present any results so users can review and republish or reply to them. It also provides an RSS reader for feeds selected by the user, as well as a site indexer that can show the frequency of different terms in user-specified blogs as a word cloud. This helps users tailor their posts to encourage coverage.
Spredfast began its public beta in mid-November. The system is a vendor-hosted service. It is available in a free version with limited functionality; a $50 per month standard version with one campaign, no collaboration and no metrics after the first month; and $250 per month enterprise version supporting all features for up to three campaigns.
Wednesday, November 18, 2009
My List of Demand Generation Vendors and Their Target Customers
[Note: I update this post periodically to keep the information reasonably current.]
Summary: Demand generation features often sound similar, but the different vendors do aim at different types of clients. If you're looking for a system, try to find a vendor who will match your company.
One of the audience members at the B2B Marketing University in Boston asked about demand generation systems for small businesses, and how to distinguish among the vendors in general. My brief answer was that the biggest difference was less functionality than the target markets the different vendors pursue. This has more to do with the degree of personal selling (and after-sale service) than anything else. I also promised a blog post on the topic. Here it is.
(Incidentally, there's one more B2BU session left this year, in Seattle on December 1. I'll be flying cross country to attend, so you could too.)
The table below presents a reasonably comprehensive list of demand generation (a.k.a. B2b marketing automation) vendors, with links to my reviews where I've written one. The vendors are divided into four categories based on my understanding of their target customers. I'm sure some of the vendors will tell me they're in the wrong place -- and since this ranking is based on their own perception of their target markets, I'll make adjustments when they do. (Clever of me to write this while they're all distracted by DreamForce, don't you think?)
- Micro Business: these products are aimed at companies where the owner does their own marketing, or perhaps one employee who does marketing along with other functions. The systems have very low starting prices tailored to low volumes. Most offer a CRM option (typically priced at $10 to $20 per seat per month) for companies who don't want to pay for Salesforce.com. The feature/function lists of these products are often comparable to systems aimed at larger companies, although there are certainly differences when you look at the details. (Note: I've put NurtureHQ into this category based on their price and what I can tell from the Web site. I haven't had a chance to review it personally.)
- Small Business: these products are sold to small businesses, often with just one or two people in the marketing department. Vendors keep costs to a minimum by selling largely online or over the phone, and through self-service approaches such as free trials and pay-by-month arrangements without contracts. Prices are a little lower than products in the Small/Mid Size category, but the difference isn't usually that large. Similarly, functionality is generally comparable although they may be less sophisticated at some tasks such as dynamic content generation (automatically altering an email or Web page based on lead characteristics) and branching campaign flows.
- Small/Mid Size: these firms sell to small and mid-size companies, and occasionally to divisions of the giants. Every vendor cites a different revenue range for its "sweet spot" but $50 million to $500 million might be typical. Starting prices are all over the map; I've assigned vendors to this category based on a combination of pricing, features and my personal sense of their business. Functionally, these are pretty sophisticated products, although they don't usually meet all the needs of very large marketing organizations, such as fine-grained security and advanced content management. (See the Vendor Usability Study on the Raab Guide site for a discussion of these features.)
- Mid/Large: these vendors have the features needed to serve large companies and large marketing departments. They also tend to have a broader range of supplemental capabilities, such as support for telephone call centers. Pricing tends to be higher and more complicated, allowing buyers to pay for specific components as needed. These vendors have geared their sales process to selling to large firms, with the in-person demonstrations, technical reviews, formal proposals and contract negotiations that implies. Of course, these companies will sell to mid-size firms as well.
Final Thoughts: I know it's a cliche, but you really do need to select a vendor that matches your own company needs. Considerations extend beyond feature checklists to include sales and support models, pricing structures, training requirements, consulting partners, and usability. This list should aim you at the right neighborhood to begin your search -- but don't be afraid to look elsewhere if you find a product that seems appropriate.
* also in Raab Guide
Summary: Demand generation features often sound similar, but the different vendors do aim at different types of clients. If you're looking for a system, try to find a vendor who will match your company.
One of the audience members at the B2B Marketing University in Boston asked about demand generation systems for small businesses, and how to distinguish among the vendors in general. My brief answer was that the biggest difference was less functionality than the target markets the different vendors pursue. This has more to do with the degree of personal selling (and after-sale service) than anything else. I also promised a blog post on the topic. Here it is.
(Incidentally, there's one more B2BU session left this year, in Seattle on December 1. I'll be flying cross country to attend, so you could too.)
The table below presents a reasonably comprehensive list of demand generation (a.k.a. B2b marketing automation) vendors, with links to my reviews where I've written one. The vendors are divided into four categories based on my understanding of their target customers. I'm sure some of the vendors will tell me they're in the wrong place -- and since this ranking is based on their own perception of their target markets, I'll make adjustments when they do. (Clever of me to write this while they're all distracted by DreamForce, don't you think?)
- Micro Business: these products are aimed at companies where the owner does their own marketing, or perhaps one employee who does marketing along with other functions. The systems have very low starting prices tailored to low volumes. Most offer a CRM option (typically priced at $10 to $20 per seat per month) for companies who don't want to pay for Salesforce.com. The feature/function lists of these products are often comparable to systems aimed at larger companies, although there are certainly differences when you look at the details. (Note: I've put NurtureHQ into this category based on their price and what I can tell from the Web site. I haven't had a chance to review it personally.)
- Small Business: these products are sold to small businesses, often with just one or two people in the marketing department. Vendors keep costs to a minimum by selling largely online or over the phone, and through self-service approaches such as free trials and pay-by-month arrangements without contracts. Prices are a little lower than products in the Small/Mid Size category, but the difference isn't usually that large. Similarly, functionality is generally comparable although they may be less sophisticated at some tasks such as dynamic content generation (automatically altering an email or Web page based on lead characteristics) and branching campaign flows.
- Small/Mid Size: these firms sell to small and mid-size companies, and occasionally to divisions of the giants. Every vendor cites a different revenue range for its "sweet spot" but $50 million to $500 million might be typical. Starting prices are all over the map; I've assigned vendors to this category based on a combination of pricing, features and my personal sense of their business. Functionally, these are pretty sophisticated products, although they don't usually meet all the needs of very large marketing organizations, such as fine-grained security and advanced content management. (See the Vendor Usability Study on the Raab Guide site for a discussion of these features.)
- Mid/Large: these vendors have the features needed to serve large companies and large marketing departments. They also tend to have a broader range of supplemental capabilities, such as support for telephone call centers. Pricing tends to be higher and more complicated, allowing buyers to pay for specific components as needed. These vendors have geared their sales process to selling to large firms, with the in-person demonstrations, technical reviews, formal proposals and contract negotiations that implies. Of course, these companies will sell to mid-size firms as well.
Final Thoughts: I know it's a cliche, but you really do need to select a vendor that matches your own company needs. Considerations extend beyond feature checklists to include sales and support models, pricing structures, training requirements, consulting partners, and usability. This list should aim you at the right neighborhood to begin your search -- but don't be afraid to look elsewhere if you find a product that seems appropriate.
| vendor | link to my review | CRM option available | published price list | starting price |
Micro Business | ||||
| Infusionsoft* | blog | yes | yes | $199/month for 10,000 names, 25,000 emails |
| MakesBridge* | blog | yes | yes | $150 / month for 50,000 names, 5,000 emails, |
| NurtureHQ | yes | $295 / month for 5,000 names | ||
| OfficeAutoPilot* | blog | yes | $597 / month for 50,000 names, 100,000 emails | |
Small Business | ||||
| ActiveConversion | blog | $500 / month for 10,000 visitors (email not included) | ||
| Act-On Software | blog | yes | $500 / month for 5,000 active names | |
| Alsamarketing | blog | $750 / month for 10,000 names and 25,000 emails | ||
| Beanstalk Data | blog | yes | $1,500/month | |
| Genoo | blog | yes | $599 / month for 10 users, unlimited leads, up to 50,000 emails / month - other versions from $199 / month | |
| HubSpot* | blog | yes | $1,000/month for 10,000 names - other versions from $200/month | |
| LoopFuse | blog | yes | $350 / month for 10,000 names, unlimited email and pageviews - free version up to 2,500 names, 5,000 email / month | |
| Net-Results* | blog | $350 - $400 / month for 30,000 page views, 10,000 emails, 2 hours of support | ||
| Pardot* | blog | yes | $1,000 / month for 30,000 emails | |
| SalesFusion* | blog | yes | $1,500 / month for 25,000 names, 125,000 emails | |
| True Influence | blog | yes | $1,500 for 10,000 names | |
Small/Mid-Size | ||||
| eTrigue | blog | $1,000 / month for 10,000 names (unlimited email, page views, users) | ||
| Genius.com* | blog | $1,100 / month - free version up to 3,000 names, 10,000 emails / month | ||
| LeadFormix (was LeadForce1)* | blog | limited | $500 / month | |
| Lead Genesys | yes | $995 / month for 10,000 names, 20,000 emails, 25,000 page views | ||
| LeadLife | blog | $500 / month for 1,500 emails; $1,395 / month for 25,000 emails | ||
| Manticore Technology* | blog | $2,000 / month up for 10,000 names | ||
| Marketo* | blog | yes | $1,500 / month up to 10,000 names (lite); $2,400 / month up to 25,000 names (full) | |
| Marqui | blog | $1,000 / month | ||
| Right On Interactive* | blog | $1,700 / month | ||
| Treehouse Interactive* | blog | yes | $599 / month for 5,000 contacts | |
Mid/Large | ||||
| Aprimo Marketing Studio* | blog | $4,000 per month for the base version with up to 10 users and 250,000 emails | ||
| Eloqua* | blog | yes | typically starts above $2,500/ month | |
| Marketbright (out of business) | blog | $1,600 / month | ||
| Oracle CRM On Demand Marketing* | blog | $2,000 - $4,000 per month | ||
| Neolane* | blog | $5,000 / month | ||
| Silverpop Engage8* | blog | (not available) |
* also in Raab Guide
Sunday, November 15, 2009
Aberdeen Predicts Web Content Systems Will Add Marketing Automation: I Agree, But...
Summary: a new Aberdeen Group report argues that Web content management systems should add customer management features and will ultimately compete with traditional marketing automation products. I agree with one reservation: I doubt large companies will use a single system to manage all customer touchpoints.
I’ve been convinced for some time that Web content management systems (CMS) will become important platforms for marketing automation. The logic is that Web sites are increasingly the primary method of interaction between a company and its customers, and that Web analytics, testing and personalized treatments are better executed within the content management system rather than by external products. See my July 14 post on CMS vendor SiteCore for a more detailed explanation, and the admission that I borrowed much of this thinking from SiteCore VP Marketing Darren Guarnaccia.
(Opposing viewpoint: marketing automation vendors tell me they don’t see CMS systems as competitors, largely because the systems are sold to IT rather than marketing departments. But this could change.)
Aberdeen Group’s report Next Generation Web Content Management makes a convincing case for a similar position. In fact, the study contains any number of pithy summaries of what I see as the fundamental trends driving the industry:
“Supporting prospects throughout the buying cycle requires a dialogue between a company and the prospect, and this dialogue should be highly relevant, timely and personalized to maximize marketing effectiveness and grow top-line revenue.”
“The new paradigm in customer engagement assumes consumers have control over the buying process, not marketers. Marketers now have to embrace the customer centric shift and deliver relevant, timely content when and where the buyer wants to receive it. This demands multi-channel engagement and automated personalized content delivery.”
“By incorporating some of the most valuable components of today’s marketing technologies (like lead scoring, dynamic content, analytics, profiling, and integration), the next generation of WCM [Web content management] tools have the potential to deliver highly personalized online experiences with little or no effort from marketers.”
Exactly.
Author Ian Michiels has been evangelizing integrated marketing platforms for the past year or longer. One section of the paper specifically describes the “battle for the integrated platform.” Michiels writes:
“Niche technology providers are increasingly starting to realize consolidation and integration will be inevitable for marketing technologies. The question is: Which technology will emerge as foundation for integrated capabilities?”
He then offers email marketing, web analytics, web content management and customer relationship management as contenders.
I agree with one major reservation. If I read Michiels correctly, he believes that one integrated system will execute the interactions across all channels. Certainly this is the fond hope of the marketing automation vendors, but I don’t believe that large companies will use the same system for all touchpoints. There are just too many channels, and new options appear too quickly, for any one vendor to satisfy everyone in a large enterprise. It’s more likely that companies will employ multiple touchpoint systems and use a central marketing platform to coordinate them.
More specifically, I see the integrated marketing platform as an underlying technology with three main roles:
- gather data from multiple sources, including touchpoint systems. This will happen in both batch and real time.
- apply analytics and decision rules to select treatments for each customer.
- push the treatment decisions back to the touchpoints for execution.
Products to do this already exist. Major contenders include Chordiant, thinkAnalytics and Infor’s CRM Interaction Advisor.
How important is the distinction having one system execute all interactions and having one system coordinate interactions that are executed by separate systems? Michiels would probably argue it’s a big difference (and I'm wrong) because he sees the difficulty of integrating multiple systems as a major barrier to coordinated treatments, and therefore a primary reason companies will be forced to adopt a single system.
But I feel the main barriers to cross-channel coordination are organizational, not technical. In my view, getting a company to replace all its existing touchpoints with a single central system faces greater organizational and financial barriers than getting it to coordinate its existing separate systems.
Let’s assume I’m right that most companies will deploy a central decision engine with multiple touchpoint systems. Doesn't this contradict my prediction that touchpoints like Web content management and CRM will expand their marketing automation functions, threatening the current marketing automation vendors?
I don’t think so. Even though I expect touchpoint systems to ultimately become delivery channels for central decisions, I doubt the touchpoint vendors will accept this role without a fight. Rather, they will expand their ability to manage interactions, thereby positioning themselves to provide the central decisioning platform itself.
Indeed, there’s a good case for having one touchpoint system make decisions for itself and other touchpoints. This avoids integration hassles between the central decision platform and one execution system, while still allowing coordination across all interactions. The logical candidate for this joint role is a company’s primary touchpoint system, which these days is probably either the Web site or CRM. Hence my prediction.
In fact, if I had to bet, I’d wager that the hybrid model will be the most successful. Financially and organizationally, it's easier to expand a major execution system than to integrate a separate decision engine. Even though an independent decision system may be technically more elegant, the organizational and financial issues are likely to be decisive.
At this point, the “hybrid model” and “one big system” may be sounding pretty similar. After all, both involve central decisions made within a major touchpoint system. But there’s a fundamental difference: “one big system” is designed to avoid integration issues by doing everything internally, while the “hybrid model” uses a primary system designed with external integration in mind. These imply very different technical approaches. Vendors building these systems, and companies looking to buy them, need to choose which philosophy they favor and act accordingly.
I’ve been convinced for some time that Web content management systems (CMS) will become important platforms for marketing automation. The logic is that Web sites are increasingly the primary method of interaction between a company and its customers, and that Web analytics, testing and personalized treatments are better executed within the content management system rather than by external products. See my July 14 post on CMS vendor SiteCore for a more detailed explanation, and the admission that I borrowed much of this thinking from SiteCore VP Marketing Darren Guarnaccia.
(Opposing viewpoint: marketing automation vendors tell me they don’t see CMS systems as competitors, largely because the systems are sold to IT rather than marketing departments. But this could change.)
Aberdeen Group’s report Next Generation Web Content Management makes a convincing case for a similar position. In fact, the study contains any number of pithy summaries of what I see as the fundamental trends driving the industry:
“Supporting prospects throughout the buying cycle requires a dialogue between a company and the prospect, and this dialogue should be highly relevant, timely and personalized to maximize marketing effectiveness and grow top-line revenue.”
“The new paradigm in customer engagement assumes consumers have control over the buying process, not marketers. Marketers now have to embrace the customer centric shift and deliver relevant, timely content when and where the buyer wants to receive it. This demands multi-channel engagement and automated personalized content delivery.”
“By incorporating some of the most valuable components of today’s marketing technologies (like lead scoring, dynamic content, analytics, profiling, and integration), the next generation of WCM [Web content management] tools have the potential to deliver highly personalized online experiences with little or no effort from marketers.”
Exactly.
Author Ian Michiels has been evangelizing integrated marketing platforms for the past year or longer. One section of the paper specifically describes the “battle for the integrated platform.” Michiels writes:
“Niche technology providers are increasingly starting to realize consolidation and integration will be inevitable for marketing technologies. The question is: Which technology will emerge as foundation for integrated capabilities?”
He then offers email marketing, web analytics, web content management and customer relationship management as contenders.
I agree with one major reservation. If I read Michiels correctly, he believes that one integrated system will execute the interactions across all channels. Certainly this is the fond hope of the marketing automation vendors, but I don’t believe that large companies will use the same system for all touchpoints. There are just too many channels, and new options appear too quickly, for any one vendor to satisfy everyone in a large enterprise. It’s more likely that companies will employ multiple touchpoint systems and use a central marketing platform to coordinate them.
More specifically, I see the integrated marketing platform as an underlying technology with three main roles:
- gather data from multiple sources, including touchpoint systems. This will happen in both batch and real time.
- apply analytics and decision rules to select treatments for each customer.
- push the treatment decisions back to the touchpoints for execution.
Products to do this already exist. Major contenders include Chordiant, thinkAnalytics and Infor’s CRM Interaction Advisor.
How important is the distinction having one system execute all interactions and having one system coordinate interactions that are executed by separate systems? Michiels would probably argue it’s a big difference (and I'm wrong) because he sees the difficulty of integrating multiple systems as a major barrier to coordinated treatments, and therefore a primary reason companies will be forced to adopt a single system.
But I feel the main barriers to cross-channel coordination are organizational, not technical. In my view, getting a company to replace all its existing touchpoints with a single central system faces greater organizational and financial barriers than getting it to coordinate its existing separate systems.
Let’s assume I’m right that most companies will deploy a central decision engine with multiple touchpoint systems. Doesn't this contradict my prediction that touchpoints like Web content management and CRM will expand their marketing automation functions, threatening the current marketing automation vendors?
I don’t think so. Even though I expect touchpoint systems to ultimately become delivery channels for central decisions, I doubt the touchpoint vendors will accept this role without a fight. Rather, they will expand their ability to manage interactions, thereby positioning themselves to provide the central decisioning platform itself.
Indeed, there’s a good case for having one touchpoint system make decisions for itself and other touchpoints. This avoids integration hassles between the central decision platform and one execution system, while still allowing coordination across all interactions. The logical candidate for this joint role is a company’s primary touchpoint system, which these days is probably either the Web site or CRM. Hence my prediction.
In fact, if I had to bet, I’d wager that the hybrid model will be the most successful. Financially and organizationally, it's easier to expand a major execution system than to integrate a separate decision engine. Even though an independent decision system may be technically more elegant, the organizational and financial issues are likely to be decisive.
At this point, the “hybrid model” and “one big system” may be sounding pretty similar. After all, both involve central decisions made within a major touchpoint system. But there’s a fundamental difference: “one big system” is designed to avoid integration issues by doing everything internally, while the “hybrid model” uses a primary system designed with external integration in mind. These imply very different technical approaches. Vendors building these systems, and companies looking to buy them, need to choose which philosophy they favor and act accordingly.
Friday, November 06, 2009
B2B Marketing University Part 2: Marketing Content Has to Work Harder
Summary: As marketers add more content to meet needs throughout the purchase cycle, they must work harder to ensure prospects actually read it.
One of the emergent themes at Tuesday’s session of the B2B Marketing University was the growing importance of marketing “content”. The general logic was that marketers increasingly interact with prospects throughout different stages of the sales cycle, and each stage needs different materials. The materials also need to be tailored to different types of buyers – or “personas” if you want to get fancy – so you need even more variety.
Of course, buying stages and buyer types have always existed. But much of the information now delivered through Web interactions was previously delivered in person by salespeople, who could just talk or write an email. Since Web interactions require formally prepared “content”, the need for content has grown.
There’s no arguing with that, and as someone who is paid to write the occasional white paper, I'm glad to hear it. But, still, as I listened to people talking about needing to build more and more content, this little voice in my head kept reminding me of another grand theme of the conference, which is the increasing range of information that prospects already have available. Odd, my little voice said: We’re being told to generate more content even though buyers have less time to read it.
This isn’t really a contradiction. The greater competition for buyers’ attention actually means we have to build content they find more useful than anyone else’s. Creating a wide variety of items does this by letting us offer buyers something that precisely matches their needs of the moment.
The little voice went away after that. (It helped that the bar had opened.) But this perspective also offers some additional guidance. Recognizing that buyers are extremely time-constrained, marketers should:
- create small, bite-sized pieces of content rather than huge chunks of it. (Yes, this implies fewer, shorter white papers. **sigh** But there are still situations where old-style, long white papers are appropriate.) The good news here is this should help to keep content creation costs down.
- put additional energy into mechanisms that make it easier for prospects to find the content they want. This means bulking up on-site search engines and carefully monitoring the queries people submit. It also means better navigation tools to expose what’s available so people can find it quickly. As a side benefit, letting people specify exactly what they want to know also lets you store that information and use it to better target your future treatments.
- ruthlessly evaluate the utilization of the content we do provide, to ensure we don’t create more than necessary and to identify topics that may need additional coverage.
- incorporate feedback mechanisms so that prospects can rate the content we’ve sent them, again to foster continuous improvement.
- make the content easily available to salespeople so they can use it themselves. This saves them the time spent crafting emails that convey pretty much the same information.
In sum, as marketers increase their investment in content, they also need to manage that investment more carefully. This may mean shifting funds from content creation to content distribution and evaluation. Bad news for marketing creators, perhaps, but good news for marketing performance.
One of the emergent themes at Tuesday’s session of the B2B Marketing University was the growing importance of marketing “content”. The general logic was that marketers increasingly interact with prospects throughout different stages of the sales cycle, and each stage needs different materials. The materials also need to be tailored to different types of buyers – or “personas” if you want to get fancy – so you need even more variety.
Of course, buying stages and buyer types have always existed. But much of the information now delivered through Web interactions was previously delivered in person by salespeople, who could just talk or write an email. Since Web interactions require formally prepared “content”, the need for content has grown.
There’s no arguing with that, and as someone who is paid to write the occasional white paper, I'm glad to hear it. But, still, as I listened to people talking about needing to build more and more content, this little voice in my head kept reminding me of another grand theme of the conference, which is the increasing range of information that prospects already have available. Odd, my little voice said: We’re being told to generate more content even though buyers have less time to read it.
This isn’t really a contradiction. The greater competition for buyers’ attention actually means we have to build content they find more useful than anyone else’s. Creating a wide variety of items does this by letting us offer buyers something that precisely matches their needs of the moment.
The little voice went away after that. (It helped that the bar had opened.) But this perspective also offers some additional guidance. Recognizing that buyers are extremely time-constrained, marketers should:
- create small, bite-sized pieces of content rather than huge chunks of it. (Yes, this implies fewer, shorter white papers. **sigh** But there are still situations where old-style, long white papers are appropriate.) The good news here is this should help to keep content creation costs down.
- put additional energy into mechanisms that make it easier for prospects to find the content they want. This means bulking up on-site search engines and carefully monitoring the queries people submit. It also means better navigation tools to expose what’s available so people can find it quickly. As a side benefit, letting people specify exactly what they want to know also lets you store that information and use it to better target your future treatments.
- ruthlessly evaluate the utilization of the content we do provide, to ensure we don’t create more than necessary and to identify topics that may need additional coverage.
- incorporate feedback mechanisms so that prospects can rate the content we’ve sent them, again to foster continuous improvement.
- make the content easily available to salespeople so they can use it themselves. This saves them the time spent crafting emails that convey pretty much the same information.
In sum, as marketers increase their investment in content, they also need to manage that investment more carefully. This may mean shifting funds from content creation to content distribution and evaluation. Bad news for marketing creators, perhaps, but good news for marketing performance.
Thursday, November 05, 2009
B2B Marketing University: For Now, Marketing Automation and CRM Are Still Separate
Summary: Marketing automation and CRM systems may eventually converge, but for now marketers need help explaining why they need a system of their own.
I hugely enjoyed yesterday’s Boston session of the Silverpop-sponsored B2B Marketing University. (You can catch another session in Atlanta next week and in Seattle on December 1.) I won’t try to recap four hours of insights from Adam Needles from Silverpop, Carlos Hidalgo of Annuitas Group and Joe Moloney of Conselltants (no Web site, it seems), as well as Yours Truly. But there were a couple of topics that caught my fancy:
1. People still don’t understand the difference between marketing automation vs. CRM.
I really thought the distinction was pretty clear by now, but the question came up more than once. My own answer boiled down to a perhaps-not-convincing “trust me, they’re really different”, although I’ve addressed the question in depth in the resources section of the Raab Guide Web site.
Joe Moloney gave a more detailed answer about limits in Salesforce.com in particular, including lack of CAN-SPAM compliance and limits on mass emails. Someone (I think it was end-of-day panelist Meg Heuer of Sirius Decisions) also pointed out that CRM data is often very dirty, which isn't a problem for salespeople working with one record at a time, but making it hard to use for marketing.
The immediate take-away here is that the industry still needs to educate prospective buyers on why marketers need a separate system. Vendors take note.
2. Will Marketing automation and CRM remain separate?
The discussion also segued into whether marketing automation and CRM will merge in the long run. I still suspect they will, driven by the need for ever-closer cooperation between marketing and sales teams in managing prospect relationships. But the other presenters disagreed, largely arguing that the separate groups have distinct needs. (See Who’s Afraid of the Big, Bad Wolf? Is Salesforce.com a threat to vendors of marketing automation solutions? by Market2Lead CMO Kevin Joyce for a good statement of the separatist position.)
Part of the reason I expect convergence to happen is that it’s already taking place. (The past is so much easier to predict than the future.) The movement is coming mostly from the marketing automation side, presumably because there is more money to gain by moving into sales from marketing systems than vice versa:
- marketing automation systems for small businesses (Infusionsoft, Office Autopilot, Net-Results, etc.) typically include a CRM option for clients who don’t want to pay for a separate Salesforce.com or other license.
- firms aimed at larger installations (Marketo, Eloqua, Pardot, Genius.com, Active Conversion) are providing widgets that give sales people direct access to marketing automation information.
3. Technology may impede Software-as-a-Service sales automation vendors from adding marketing automation.
As Joe Moloney was listing the limits that Salesforce.com places on mass access to client data, I recalled that these are in place fundamentally to avoid large analytical queries that could slow down response for all other users of the shared systems. This isn’t an inherent problem with Software-as-a-Service itself: remember, the B2B marketing automation vendors themselves all operate on a SaaS model, and there is a growing number of SaaS business intelligence systems too.
But even though modern database technology allows one system to handle both CRM transactions and analytical marketing queries, this does take an appropriate design. I strongly suspect that existing SaaS CRM vendors like Salesforce.com would need to fundamentally rearchitect their systems to support serious marketing automation processing, especially for clients with millions of contact records. This may impede them from adding marketing automation capabilities, although newer SaaS CRM systems could emerge that are designed from the start to do both.
From this perspective, another reason combined marketing automation/CRM systems are first being offered to small companies may be that it’s easier to provide good performance for both applications when volumes are small.
Yesterday also triggered another set of thoughts regarding the importance of marketing content. But since one of these was the need to keep materials short, I’ll put them into a separate post.
I hugely enjoyed yesterday’s Boston session of the Silverpop-sponsored B2B Marketing University. (You can catch another session in Atlanta next week and in Seattle on December 1.) I won’t try to recap four hours of insights from Adam Needles from Silverpop, Carlos Hidalgo of Annuitas Group and Joe Moloney of Conselltants (no Web site, it seems), as well as Yours Truly. But there were a couple of topics that caught my fancy:
1. People still don’t understand the difference between marketing automation vs. CRM.
I really thought the distinction was pretty clear by now, but the question came up more than once. My own answer boiled down to a perhaps-not-convincing “trust me, they’re really different”, although I’ve addressed the question in depth in the resources section of the Raab Guide Web site.
Joe Moloney gave a more detailed answer about limits in Salesforce.com in particular, including lack of CAN-SPAM compliance and limits on mass emails. Someone (I think it was end-of-day panelist Meg Heuer of Sirius Decisions) also pointed out that CRM data is often very dirty, which isn't a problem for salespeople working with one record at a time, but making it hard to use for marketing.
The immediate take-away here is that the industry still needs to educate prospective buyers on why marketers need a separate system. Vendors take note.
2. Will Marketing automation and CRM remain separate?
The discussion also segued into whether marketing automation and CRM will merge in the long run. I still suspect they will, driven by the need for ever-closer cooperation between marketing and sales teams in managing prospect relationships. But the other presenters disagreed, largely arguing that the separate groups have distinct needs. (See Who’s Afraid of the Big, Bad Wolf? Is Salesforce.com a threat to vendors of marketing automation solutions? by Market2Lead CMO Kevin Joyce for a good statement of the separatist position.)
Part of the reason I expect convergence to happen is that it’s already taking place. (The past is so much easier to predict than the future.) The movement is coming mostly from the marketing automation side, presumably because there is more money to gain by moving into sales from marketing systems than vice versa:
- marketing automation systems for small businesses (Infusionsoft, Office Autopilot, Net-Results, etc.) typically include a CRM option for clients who don’t want to pay for a separate Salesforce.com or other license.
- firms aimed at larger installations (Marketo, Eloqua, Pardot, Genius.com, Active Conversion) are providing widgets that give sales people direct access to marketing automation information.
3. Technology may impede Software-as-a-Service sales automation vendors from adding marketing automation.
As Joe Moloney was listing the limits that Salesforce.com places on mass access to client data, I recalled that these are in place fundamentally to avoid large analytical queries that could slow down response for all other users of the shared systems. This isn’t an inherent problem with Software-as-a-Service itself: remember, the B2B marketing automation vendors themselves all operate on a SaaS model, and there is a growing number of SaaS business intelligence systems too.
But even though modern database technology allows one system to handle both CRM transactions and analytical marketing queries, this does take an appropriate design. I strongly suspect that existing SaaS CRM vendors like Salesforce.com would need to fundamentally rearchitect their systems to support serious marketing automation processing, especially for clients with millions of contact records. This may impede them from adding marketing automation capabilities, although newer SaaS CRM systems could emerge that are designed from the start to do both.
From this perspective, another reason combined marketing automation/CRM systems are first being offered to small companies may be that it’s easier to provide good performance for both applications when volumes are small.
Yesterday also triggered another set of thoughts regarding the importance of marketing content. But since one of these was the need to keep materials short, I’ll put them into a separate post.
Monday, October 26, 2009
Survey Suggests Marketers Are Moving from Paid to Social Media
Summary: a new survey suggests that marketers are less focused on lead generation than on final sales, growing current customers and building online communities. I’m not sure I trust the data, but it’s a pretty picture nevertheless.
I don’t know quite what to make of the 2009 Survey on Marketing, Media and Measurement released earlier this month by custom content company King Fish Media.
- On one hand, it’s a rare opportunity to see data from business, rather than consumer, marketers. (Of the 230 respondents, 52% were pure B2B and another 36% were mixed B2B and business-to-consumer.) So I'd really like to believe it.
- But on the other hand, the sample seems dangerously unrepresentative: 44% said their organization’s primary industry was “publishing/media/advertising/marketing”, which is vastly higher than the real-world proportion. Presumably this was the result of the survey method – an online survey based on email invitations to the lists of King Fish and co-sponsors HubSpot, Junta42 and Upshot Institute. In addition to the industry skew, this probably reached a group that’s much more online-oriented than marketers as a whole.
The best I can do is to treat the results very carefully: assuming that this group shares some characteristics of the broader universe, but keeping in mind that some answers might reflect its atypical composition. Here goes.
1. Marketing Measurement Practices
The group reported using three broad types of marketing success measurements:
- 91% measured new customers acquired or leads generated.
- 63% measured customer retention or sales from current customers or lapsed customers.
- 54% measured brand-marketing-style metrics such as awareness, perception or intent.
Directionally, this seems about right: more marketers focus on new business than on existing customers, and brand-style measurements are less common than business results. The figures for existing-customer measurements are higher than I would expect, but perhaps that’s because publishing marketers are more directly responsible for renewals than business marketers in general.
Another oddity was that more people report measuring new customers (77%) than leads (73%). An optimist would treat this as evidence that marketers are adopting an end-to-end vision (as they should) rather than ending their responsibility when a lead is handed over to sales. But think the more likely cause is that marketers in publishing are more likely to sell directly (i.e., without a sales force) than in other industries.
Incidentally, the survey also found that 73% of respondents had guidelines in place to measure marketing success, but just 50% said their company requires a measurement plan as part of its program approval process. Treat this as you wish: is it impressive that 73% have measurement guidelines or frightening that 27% do not? Also bear in mind that 91% were at least using measurement on acquisition programs (some, apparently, without standard guidelines). So I think we can conclude that basic measurement is widespread, although its quality and consistency are questionable.
2. Spending on Acquisition vs. Existing Customers
Media spending by purpose was distributed:
- 56% for new leads
- 33% for retention
- 10% for other
This is interesting because I don’t recall seeing other data showing this split. The actual numbers show much more spending on retention than I would have expected. As with the measurement figures, this probably reflects the business of the survey responders.
3. Media Preferences
The main thrust of the survey was how marketers view different media. Marketers were asked to rate "the most effective way to communicate with customers and prospects", with separate answers for each. Here are the results:
If there’s a pattern here, it’s that awareness-generating media (e-mail, direct mail and online/print/broadcast advertising) rank shockingly low, especially for prospecting. Apart from using email for customer communications, the respondents gave their highest rankings to the corporate Web site, social media, and custom content.
But how, exactly, can they attract traffic for the Web site, social media message and custom content if they don’t reach out to new audiences? I can think of (at least) two answers:
- they can’t, and the answers just reflect an infatuation with online media. I’m not saying the respondents are poor marketers: chances are they really do use the low-ranked media, but don’t consider them terribly effective. (Other answers in the survey suggest the same thing, showing that budgets are moving away from the low-ranking media to the high-ranked categories.)
- they can, by using social media and custom media in the awareness- and traffic-building roles previously handled by paid advertising. Put another way, the traditional first steps of generating awareness and interest are handled by the community rather than by marketers themselves. In this world, marketing’s role becomes to nurture communities of enthusiasts and evangelists, and then to meet the needs of prospects attracted by the community. This is what I meant in my September 23 post about community-centric marketing replacing customer centricity. (Can I coin CBM as a new acronym for Community Based Marketing?)
Obviously the second possibility is more intriguing. It’s surely correct to some degree, although the Big Question is how quickly and how far marketers’ role will shift. Given my concerns about this survey, I wouldn’t treat its results as definitive answers. But they're still tasty food for thoughts.
I don’t know quite what to make of the 2009 Survey on Marketing, Media and Measurement released earlier this month by custom content company King Fish Media.
- On one hand, it’s a rare opportunity to see data from business, rather than consumer, marketers. (Of the 230 respondents, 52% were pure B2B and another 36% were mixed B2B and business-to-consumer.) So I'd really like to believe it.
- But on the other hand, the sample seems dangerously unrepresentative: 44% said their organization’s primary industry was “publishing/media/advertising/marketing”, which is vastly higher than the real-world proportion. Presumably this was the result of the survey method – an online survey based on email invitations to the lists of King Fish and co-sponsors HubSpot, Junta42 and Upshot Institute. In addition to the industry skew, this probably reached a group that’s much more online-oriented than marketers as a whole.
The best I can do is to treat the results very carefully: assuming that this group shares some characteristics of the broader universe, but keeping in mind that some answers might reflect its atypical composition. Here goes.
1. Marketing Measurement Practices
The group reported using three broad types of marketing success measurements:
- 91% measured new customers acquired or leads generated.
- 63% measured customer retention or sales from current customers or lapsed customers.
- 54% measured brand-marketing-style metrics such as awareness, perception or intent.
Directionally, this seems about right: more marketers focus on new business than on existing customers, and brand-style measurements are less common than business results. The figures for existing-customer measurements are higher than I would expect, but perhaps that’s because publishing marketers are more directly responsible for renewals than business marketers in general.
Another oddity was that more people report measuring new customers (77%) than leads (73%). An optimist would treat this as evidence that marketers are adopting an end-to-end vision (as they should) rather than ending their responsibility when a lead is handed over to sales. But think the more likely cause is that marketers in publishing are more likely to sell directly (i.e., without a sales force) than in other industries.
Incidentally, the survey also found that 73% of respondents had guidelines in place to measure marketing success, but just 50% said their company requires a measurement plan as part of its program approval process. Treat this as you wish: is it impressive that 73% have measurement guidelines or frightening that 27% do not? Also bear in mind that 91% were at least using measurement on acquisition programs (some, apparently, without standard guidelines). So I think we can conclude that basic measurement is widespread, although its quality and consistency are questionable.
2. Spending on Acquisition vs. Existing Customers
Media spending by purpose was distributed:
- 56% for new leads
- 33% for retention
- 10% for other
This is interesting because I don’t recall seeing other data showing this split. The actual numbers show much more spending on retention than I would have expected. As with the measurement figures, this probably reflects the business of the survey responders.
3. Media Preferences
The main thrust of the survey was how marketers view different media. Marketers were asked to rate "the most effective way to communicate with customers and prospects", with separate answers for each. Here are the results:
| for prospects/leads | for current customers | |
| corporate Web site | 75% | 70% |
| social media | 73% | 72% |
| custom content and media | 70% | 77% |
| face-to-face events | 69% | 62% |
| white papers / e-books | 67% | 52% |
| Webcasts and virtual trade shows | 64% | 51% |
| e-mail marketing | 58% | 78% |
| online advertising | 42% | 13% |
| direct mail promotions | 33% | 34% |
| print advertising | 33% | 17% |
| broadcast advertising | 10% | 11% |
If there’s a pattern here, it’s that awareness-generating media (e-mail, direct mail and online/print/broadcast advertising) rank shockingly low, especially for prospecting. Apart from using email for customer communications, the respondents gave their highest rankings to the corporate Web site, social media, and custom content.
But how, exactly, can they attract traffic for the Web site, social media message and custom content if they don’t reach out to new audiences? I can think of (at least) two answers:
- they can’t, and the answers just reflect an infatuation with online media. I’m not saying the respondents are poor marketers: chances are they really do use the low-ranked media, but don’t consider them terribly effective. (Other answers in the survey suggest the same thing, showing that budgets are moving away from the low-ranking media to the high-ranked categories.)
- they can, by using social media and custom media in the awareness- and traffic-building roles previously handled by paid advertising. Put another way, the traditional first steps of generating awareness and interest are handled by the community rather than by marketers themselves. In this world, marketing’s role becomes to nurture communities of enthusiasts and evangelists, and then to meet the needs of prospects attracted by the community. This is what I meant in my September 23 post about community-centric marketing replacing customer centricity. (Can I coin CBM as a new acronym for Community Based Marketing?)
Obviously the second possibility is more intriguing. It’s surely correct to some degree, although the Big Question is how quickly and how far marketers’ role will shift. Given my concerns about this survey, I wouldn’t treat its results as definitive answers. But they're still tasty food for thoughts.
Thursday, October 22, 2009
SalesFusion Combines Online and Offline Marketing with CRM
Summary: SalesFusion combines all channels within marketing, and merges marketing automation with CRM as well. This one-stop-shopping will be most attractive to small and mid-size companies, although I expect that larger firms will eventually want it too.
Look, I know online marketing is important. But let’s not forget that offline channels still account for nearly 90% of total advertising expenditures. Business marketers probably spend more online, but, once you add in the cost of salespeople, I’d guess that online spending still accounts for less than 10% of the combined total.
My point here – have you met my pet, Peeve? – is that nobody needs a comprehensive online marketing suite. They need a comprehensive marketing suite, period, that includes both online and offline activities. And, while we’re on the subject, they need REALLY TIGHT integration between marketing and sales automation, if not one shared system.
This brings us, somewhat abruptly, to SalesFusion360, a B2B marketing automation system that does merge online, offline and sales channels. This breadth isn’t accompanied by tremendous depth: SalesFusion’s campaign management and built-in CRM tools are a bit limited. But the system does offer a comprehensive solution for smaller firms and, at least on the CRM side, can integrate with more powerful solutions including Salesforce.com, Microsoft Dynamics CRM and Siebel CRM On Demand.
Let’s start with SalesFusion’s strongest point, which is the scope of marketing channels supported. Beyond the usual outbound email and Web forms, the system provides:
- Web analytics to support search engine optimization and Web advertising,
- API-level integration with Google AdWords to support paid keyword campaigns,
- IP-address lookup to identify the company and location of anonymous Web visitors (and send rule-based alerts to salespeople),
- personalized URLs (PURLs) to tie in responses from offline campaigns.
- online chat and
- telemarketing support through the CRM component.
Results from all these channels are managed through a unified campaign structure, which creates a hierarchy of campaigns and subcampaigns to allow channel-level rollups. Campaign data includes budgets, actual costs, and revenues imported from sales opportunities.
The email features cover all the basic requirements: template-driven personalized messages, universal and campaign-level exclusion rules, and both static and dynamic list definitions. Campaigns can be executed manually by the user or triggered by selected events including completion of a form, selecting a specific answer within a form, completing a step in a multi-step marketing campaign, or reaching a score threshold.
The main weakness is that multi-step campaigns can only send messages in a fixed sequence (i.e., no branching based on prospect behavior) at fixed intervals. A skilled user could implement some branching by using step-level inclusion and exclusion rules to send different messages to different people and by using Web forms to send leads to new campaigns. But these are awkward solutions. SalesFusion promises a more flexible, visual campaign builder and dynamic content generation for delivery early next year.
The system’s features for lead scoring and routing are more impressive. Users can build separate scoring rules for different marketing campaigns, regions, products or other entities. These scoring rules can be active for specified date ranges and can post scores at contact or account levels.
Users can define value ranges (hot, warm, cold, etc.) for each score, and can set up routing rules triggered by entry into each range. These rules trigger an email campaign, send an alert, create a log entry, or add a lead, task or opportunity record in the CRM system. Multiple scores are particularly important at large companies where contacts need to be treated differently for different products, regions and other variables.
Each scoring rule can incorporate Web activity, campaign events, form responses and static data. Score calculations can ignore events before a specified period, but do not make interim reductions as events reach this limit. The system can cap the number of points earned by any one type of event, although this takes some configuration by the vendor. Users can specify whether scores are recalculated on daily, weekly or monthly.
The integrated CRM system provides most of the features needed by small and mid-size companies, and is used by about half of SalesFusion's current clients. The company plans to enhance the CRM system to be more competitive with enterprise-class systems by early next year. The CRM and marketing automation components of the system already work on a shared data structure. Clients who use a separate CRM system can synchronize data via regular updates.
Reporting includes prebuilt dashboards and an ad hoc report writer that lets users query system tables directly. The latter is an unusual feature for Software-as-a-Service systems like SalesFusion, since most vendors are concerned that ad hoc queries could harm system performance.
SalesFusion starts at $250 per month for a light version with limited features, under 1,000 names in the database, five users, and 10,000 emails per month. The lowest-priced full version costs $1,500 per month and includes up to 25,000 names, 75 users, and 125,000 monthly emails. CRM is currently included at no extra cost, although the vendor plans to start charging around $10 per user per month when the enhanced version is released.
The first version of SalesFusion was released in 2003, when the company was named FirstReef. It merged in 2007 with online forms vendor AxiomFire and assumed its current name in January 2009. The system has about 50 current installations, many sold by resellers including some major accounts in Australia and South America. SalesFusion is now expanding its direct sales efforts.
Look, I know online marketing is important. But let’s not forget that offline channels still account for nearly 90% of total advertising expenditures. Business marketers probably spend more online, but, once you add in the cost of salespeople, I’d guess that online spending still accounts for less than 10% of the combined total.
My point here – have you met my pet, Peeve? – is that nobody needs a comprehensive online marketing suite. They need a comprehensive marketing suite, period, that includes both online and offline activities. And, while we’re on the subject, they need REALLY TIGHT integration between marketing and sales automation, if not one shared system.
This brings us, somewhat abruptly, to SalesFusion360, a B2B marketing automation system that does merge online, offline and sales channels. This breadth isn’t accompanied by tremendous depth: SalesFusion’s campaign management and built-in CRM tools are a bit limited. But the system does offer a comprehensive solution for smaller firms and, at least on the CRM side, can integrate with more powerful solutions including Salesforce.com, Microsoft Dynamics CRM and Siebel CRM On Demand.
Let’s start with SalesFusion’s strongest point, which is the scope of marketing channels supported. Beyond the usual outbound email and Web forms, the system provides:
- Web analytics to support search engine optimization and Web advertising,
- API-level integration with Google AdWords to support paid keyword campaigns,
- IP-address lookup to identify the company and location of anonymous Web visitors (and send rule-based alerts to salespeople),
- personalized URLs (PURLs) to tie in responses from offline campaigns.
- online chat and
- telemarketing support through the CRM component.
Results from all these channels are managed through a unified campaign structure, which creates a hierarchy of campaigns and subcampaigns to allow channel-level rollups. Campaign data includes budgets, actual costs, and revenues imported from sales opportunities.
The email features cover all the basic requirements: template-driven personalized messages, universal and campaign-level exclusion rules, and both static and dynamic list definitions. Campaigns can be executed manually by the user or triggered by selected events including completion of a form, selecting a specific answer within a form, completing a step in a multi-step marketing campaign, or reaching a score threshold.
The main weakness is that multi-step campaigns can only send messages in a fixed sequence (i.e., no branching based on prospect behavior) at fixed intervals. A skilled user could implement some branching by using step-level inclusion and exclusion rules to send different messages to different people and by using Web forms to send leads to new campaigns. But these are awkward solutions. SalesFusion promises a more flexible, visual campaign builder and dynamic content generation for delivery early next year.
The system’s features for lead scoring and routing are more impressive. Users can build separate scoring rules for different marketing campaigns, regions, products or other entities. These scoring rules can be active for specified date ranges and can post scores at contact or account levels.
Users can define value ranges (hot, warm, cold, etc.) for each score, and can set up routing rules triggered by entry into each range. These rules trigger an email campaign, send an alert, create a log entry, or add a lead, task or opportunity record in the CRM system. Multiple scores are particularly important at large companies where contacts need to be treated differently for different products, regions and other variables.
Each scoring rule can incorporate Web activity, campaign events, form responses and static data. Score calculations can ignore events before a specified period, but do not make interim reductions as events reach this limit. The system can cap the number of points earned by any one type of event, although this takes some configuration by the vendor. Users can specify whether scores are recalculated on daily, weekly or monthly.
The integrated CRM system provides most of the features needed by small and mid-size companies, and is used by about half of SalesFusion's current clients. The company plans to enhance the CRM system to be more competitive with enterprise-class systems by early next year. The CRM and marketing automation components of the system already work on a shared data structure. Clients who use a separate CRM system can synchronize data via regular updates.
Reporting includes prebuilt dashboards and an ad hoc report writer that lets users query system tables directly. The latter is an unusual feature for Software-as-a-Service systems like SalesFusion, since most vendors are concerned that ad hoc queries could harm system performance.
SalesFusion starts at $250 per month for a light version with limited features, under 1,000 names in the database, five users, and 10,000 emails per month. The lowest-priced full version costs $1,500 per month and includes up to 25,000 names, 75 users, and 125,000 monthly emails. CRM is currently included at no extra cost, although the vendor plans to start charging around $10 per user per month when the enhanced version is released.
The first version of SalesFusion was released in 2003, when the company was named FirstReef. It merged in 2007 with online forms vendor AxiomFire and assumed its current name in January 2009. The system has about 50 current installations, many sold by resellers including some major accounts in Australia and South America. SalesFusion is now expanding its direct sales efforts.
Monday, October 12, 2009
5 Steps to Marketing Measurement Maturity
Summary: marketing performance measurement can start with simple response tracking, and grow in stages to show business impact, track the buying process, optimize results and demonstrate strategic alignment. Each stage adds new data, systems, measures and processes.
I’ll be talking about marketing measurement this Tuesday at Silverpop’s B2B Marketing University seminar in Palo Alto, with a repeat performance in Boston on November 4. The core of my presentation will be a 5-step measurement maturity model for B2B marketers. This post will give you a brief summary.
A little background: marketers’ objectives for performance measurement generally fall into five broad categories: measure response, show business impact, track the buying process, optimize results and demonstrate marketing alignment with business strategy. Each category has different requirements for data, systems, measures, and processes. Because some of these requirements overlap, there’s a natural progression starting with the simplest requirements and adding new requirements for each stage. This progression leads to a maturity model. Here are the details.
1. Measure Response. The most basic requirement is simply to count the number of responses to each marketing program. This stage also includes the closely related step of calculating the cost of those responses for a simple cost-per-response measure that can be used for a rough ranking of investments.
Key data needs for this stage include mechanisms to capture responses and campaign costs and to link responses to campaigns. This requires a campaign management system to execute the campaigns and track their costs, and a marketing database that stores the identity, promotion history and response history of leads generated by the campaigns.
2. Show Business Impact of Marketing Campaigns. The cost per response tells little about the business impact of a marketing program. You must also know the value of those responses. At a minimum, this requires linking marketing leads to closed sales. This typically means importing closed opportunity records from a sales automation system and linking those opportunities back to the original marketing lead. Add the cost data already gathered in stage 1 (response measurement) and you can calculate a simple Return on Investment based on revenue / acquisition cost.
Of course, true ROI is based on profits, not revenue, and incorporates all incremental costs, not just the initial marketing expense. A proper business impact measurement thus requires capturing the full marketing, sales and product costs associated with new leads, as well as their actual or estimated long-term value. These give a ROI measure that comes reasonably close to showing the true business impact of each acquisition campaign.
In terms of new requirements, this step adds sales opportunity data, which implies integration with a sales force automation or CRM system. It also requires processes to assign opportunities to leads and leads to campaigns, and, optionally, ways to import and connect lifetime costs and revenues.
Keep in mind that this approach only applies to lead acquisition campaigns, not to campaigns that nurture existing leads or customers, or branding campaigns that don’t generate a direct response. This is a smaller issue for B2B marketers than many consumer marketers, who often have no direct way to identify the customers acquired or influenced by their activities.
3. Understand the Buying Process. This stage looks at the impact of non-acquisition marketing treatments on moving customers through the buying process. It requires defining stages within the buying process, tracking the movement of individual leads through those stages over time, recording the marketing treatments applied to those individuals, and measuring the correlation (if any) of treatments to stage changes. The result is both a more detailed understanding of the buying process and a way to decide which treatments are most valuable.
Meeting these requirements implies capturing more information about leads, including static attributes (company, job title, etc.) and behaviors such as Web site visits and email responses. These can be used in scoring models or other tools that decide which stage a lead is in at any given moment. The system must also keep a history of each lead’s stages over time, so it can correlate stage changes with treatments. The treatments themselves are already captured in the marketing database needed for response measurement, so they do not represent a new requirement.
4. Optimize Results. Once you’re tracking lead movement through process stages and measuring the impact of individual treatments, you’re ready to build an end-to-end model that calculates the impact of each small change on final sales. You can then optimize the combination of treatments across the process. For example, you might find you can spend less on acquiring new leads if you spend more on nurturing existing ones, to produce the same sales volume at lower cost.
The calculations for this type of optimization are fairly simple, and they don’t require any new information beyond the previous stage in the maturity model. But you do need more precise information about the impact of different treatments, which means formal testing of alternative treatments and careful analysis of results. You’ll also need a business simulation model that can estimate the impact of changes on near-term revenues and costs, since the company still has its quarterly targets to hit. You'll also need to define you goals -- higher revenue? higher profit rate? lower marketing costs? -- so you know what to optimize.
Ideally, you’ll also add optimization software that can automatically find the best of all possible treatment combinations. But few B2B marketers have the data volume or statistical skills required for this, so you’ll probably end up manually running a variety of scenarios through your simulation model instead.
5. Demonstrate Strategic Alignment. Delivering the optimal set of treatments won’t satisfy your CEO if your marketing programs don’t align with the larger business strategy. That alignment may in fact require campaigns that produce low short-term returns, such as investing in a new product or market segment.
To demonstrate alignment, you must first show that your planned marketing activities support business goals, and then show that those activities have yielded the expected results. For example, a strategy based on selling to a new group of customers might yield a marketing plan with 10% of acquisition spending aimed at generating leads from that segment, and a goal of that segment accounting for 5% of new leads received.
The exact requirements for this stage will depend on your specific strategic goals. But it’s likely that you’ll need more information about the purposes of your marketing spending (so you can show which funds are supporting which strategic goals) and more about lead attributes and behaviors (so you can show that results are in line with expectations).
Incidentally, demonstrating strategic alignment doesn’t depend directly understanding the buying process (stage 3) or optimizing results (stage 4). So a company that has reached stage 2 in the maturity model could jump immediately to demonstrating strategic alignment if desired.
Final Thought: once you get past counting response, all later stages in the maturity model assume you are measuring your marketing performance against the ultimate goals of closed sales and long-term customer value. This is increasingly necessary as marketing remains involved with leads even after they are officially transferred to sales. It implies that marketing and sales must integrate their systems, so they can view, coordinate, analyze and ultimately optimize sales and marketing activities across the entire buying cycle.
In companies where the marketing's responsibility still ends with the hand-off of qualified leads to sales, the maturity model could be adjusted to optimize only through that stage. But that's an increasingly obsolete approach.
I’ll be talking about marketing measurement this Tuesday at Silverpop’s B2B Marketing University seminar in Palo Alto, with a repeat performance in Boston on November 4. The core of my presentation will be a 5-step measurement maturity model for B2B marketers. This post will give you a brief summary.
A little background: marketers’ objectives for performance measurement generally fall into five broad categories: measure response, show business impact, track the buying process, optimize results and demonstrate marketing alignment with business strategy. Each category has different requirements for data, systems, measures, and processes. Because some of these requirements overlap, there’s a natural progression starting with the simplest requirements and adding new requirements for each stage. This progression leads to a maturity model. Here are the details.
1. Measure Response. The most basic requirement is simply to count the number of responses to each marketing program. This stage also includes the closely related step of calculating the cost of those responses for a simple cost-per-response measure that can be used for a rough ranking of investments.
Key data needs for this stage include mechanisms to capture responses and campaign costs and to link responses to campaigns. This requires a campaign management system to execute the campaigns and track their costs, and a marketing database that stores the identity, promotion history and response history of leads generated by the campaigns.
2. Show Business Impact of Marketing Campaigns. The cost per response tells little about the business impact of a marketing program. You must also know the value of those responses. At a minimum, this requires linking marketing leads to closed sales. This typically means importing closed opportunity records from a sales automation system and linking those opportunities back to the original marketing lead. Add the cost data already gathered in stage 1 (response measurement) and you can calculate a simple Return on Investment based on revenue / acquisition cost.
Of course, true ROI is based on profits, not revenue, and incorporates all incremental costs, not just the initial marketing expense. A proper business impact measurement thus requires capturing the full marketing, sales and product costs associated with new leads, as well as their actual or estimated long-term value. These give a ROI measure that comes reasonably close to showing the true business impact of each acquisition campaign.
In terms of new requirements, this step adds sales opportunity data, which implies integration with a sales force automation or CRM system. It also requires processes to assign opportunities to leads and leads to campaigns, and, optionally, ways to import and connect lifetime costs and revenues.
Keep in mind that this approach only applies to lead acquisition campaigns, not to campaigns that nurture existing leads or customers, or branding campaigns that don’t generate a direct response. This is a smaller issue for B2B marketers than many consumer marketers, who often have no direct way to identify the customers acquired or influenced by their activities.
3. Understand the Buying Process. This stage looks at the impact of non-acquisition marketing treatments on moving customers through the buying process. It requires defining stages within the buying process, tracking the movement of individual leads through those stages over time, recording the marketing treatments applied to those individuals, and measuring the correlation (if any) of treatments to stage changes. The result is both a more detailed understanding of the buying process and a way to decide which treatments are most valuable.
Meeting these requirements implies capturing more information about leads, including static attributes (company, job title, etc.) and behaviors such as Web site visits and email responses. These can be used in scoring models or other tools that decide which stage a lead is in at any given moment. The system must also keep a history of each lead’s stages over time, so it can correlate stage changes with treatments. The treatments themselves are already captured in the marketing database needed for response measurement, so they do not represent a new requirement.
4. Optimize Results. Once you’re tracking lead movement through process stages and measuring the impact of individual treatments, you’re ready to build an end-to-end model that calculates the impact of each small change on final sales. You can then optimize the combination of treatments across the process. For example, you might find you can spend less on acquiring new leads if you spend more on nurturing existing ones, to produce the same sales volume at lower cost.
The calculations for this type of optimization are fairly simple, and they don’t require any new information beyond the previous stage in the maturity model. But you do need more precise information about the impact of different treatments, which means formal testing of alternative treatments and careful analysis of results. You’ll also need a business simulation model that can estimate the impact of changes on near-term revenues and costs, since the company still has its quarterly targets to hit. You'll also need to define you goals -- higher revenue? higher profit rate? lower marketing costs? -- so you know what to optimize.
Ideally, you’ll also add optimization software that can automatically find the best of all possible treatment combinations. But few B2B marketers have the data volume or statistical skills required for this, so you’ll probably end up manually running a variety of scenarios through your simulation model instead.
5. Demonstrate Strategic Alignment. Delivering the optimal set of treatments won’t satisfy your CEO if your marketing programs don’t align with the larger business strategy. That alignment may in fact require campaigns that produce low short-term returns, such as investing in a new product or market segment.
To demonstrate alignment, you must first show that your planned marketing activities support business goals, and then show that those activities have yielded the expected results. For example, a strategy based on selling to a new group of customers might yield a marketing plan with 10% of acquisition spending aimed at generating leads from that segment, and a goal of that segment accounting for 5% of new leads received.
The exact requirements for this stage will depend on your specific strategic goals. But it’s likely that you’ll need more information about the purposes of your marketing spending (so you can show which funds are supporting which strategic goals) and more about lead attributes and behaviors (so you can show that results are in line with expectations).
Incidentally, demonstrating strategic alignment doesn’t depend directly understanding the buying process (stage 3) or optimizing results (stage 4). So a company that has reached stage 2 in the maturity model could jump immediately to demonstrating strategic alignment if desired.
Final Thought: once you get past counting response, all later stages in the maturity model assume you are measuring your marketing performance against the ultimate goals of closed sales and long-term customer value. This is increasingly necessary as marketing remains involved with leads even after they are officially transferred to sales. It implies that marketing and sales must integrate their systems, so they can view, coordinate, analyze and ultimately optimize sales and marketing activities across the entire buying cycle.
In companies where the marketing's responsibility still ends with the hand-off of qualified leads to sales, the maturity model could be adjusted to optimize only through that stage. But that's an increasingly obsolete approach.
Saturday, October 10, 2009
Beautiful BABI: SiSense PrismCubed Offers Business Intelligence for Business Analysts
Summary: SiSense PrismCubed offers a reasonable option for a business-analyst business intelligence system. It’s probably a little harder to use than some competitors, but gives a bit more power and flexibility in return.
SiSense PrismCubed, officially launched this past August, is another member of the growing set of business intelligence systems aimed at empowering business analysts to build their own applications. I’ve also written about QlikView and Lyza, and think there are others.
What distinguishes these tools from other business intelligence systems is they let non-technical users manipulate source data in more sophisticated ways than a spreadsheet or report writer. Specifically, data from several sources can be merged on a common key, filtered, aggregated and processed through complex formulas.
This sort of manipulation has traditionally required SQL programmers, OLAP cube designers, or similar technical experts. Allowing business analysts to do it without having to learn deep technical skills is precisely what lets them build applications with minimal external assistance. (I say "minimal" because technical staff must still handle connections to the source data.)
These systems also provide report creation and distribution. But unlike business-analyst data manipulation, those capabilities are also found in other business intelligence products.
You’ll note that my definition does NOT specify a particular database technology, such as in-memory or columnar, that the data is updated in real time, that the system is targeted at mid-sized businesses, or that results are distributed pervasively through the organization. Those have all been proposed as ways to classify business intelligence systems, and several of the products in my business-analyst business intelligence (BABI--how cute!) category fall into one or another such group. But I think it’s a mistake to focus on those other features because they don’t get at real value provided by these tools, which is the flowering of applications made possible when business analysts can create them independently.
Now that I've defined a new type of application, complete with the all-important acronym, the next step is defining an evaluation framework to help compare the competitors. I’d like to claim I do this through deep research and brilliant insights into user needs, but, in fact, I generally start with the features in the existing systems. This runs the risk of missing some critical requirement that no vendor has yet uncovered, but it saves a ton of work. And I can still argue that I’m piggybacking on the vendors’ own deep research and insights as embodied in their products.
In any event, a starter set of review criteria for BABI systems (sorry, but I find the acronym irresistible) would include:
- combine data from multiple, heterogeneous sources (relational databases, CSV files, Excel tables, etc.)
- allow non-technical users to define processing flows to manipulate the data (merge, filter, aggregate, calculate)
- present the manipulated data in a structure that’s suitable for reporting and visualization
- allow non-technical users to create applications including reports, visualizations, and (optionally) additional functions such as data refresh and export
- allow other users to view (and optionally interact with) the applications
- meet reasonable performance standards for data load, storage, response time and scalability
- use appropriate technology (actually, I don’t care if the thing is powered by hamsters. But understanding the underlying technology helps to predict where problems might arise.)
- affordable pricing (not exactly a criterion, but important nevertheless)
Obviously these criteria could be much more detailed, and no doubt they will grow over time. But for now, they provide a useful way to look at PrismCubed.
1. Combine data from multiple sources: PrismCubed provides a wizard to connect with different data sources, including SQL Server, Oracle, CSV files, Excel and Amazon S3 logs (which earns them extra coolness points). The system can read the database schemas directly, saving users the need to define basic data structures. Users have the option modify structures if they desire. A connection can be live (i.e., the source is requeried each time a report is run) or reloaded on demand from within a completed application. This provides real-time data access, which isn’t always available in business intelligence systems. The system can also reload data automatically on a user-specified schedule.
2. Allow non-technical users to manipulate source data: PrismCubed does a particularly good job here. At a basic level, users can write complex formulas to add derived fields to a table during the import process. More important, a drag-and-drop interface lets them build complex visual processing flows from standard icons including data definition, filtering, inclusion or exclusion, unions, and top or bottom selects. These flows can combine multiple data sources and include branches that generate separate output sets that are all available to use in applications.
3. Present the manipulated data for reporting: the system automatically classifies input data as dimensions (text, dates, etc.) and measures (numbers which can be aggregated). Users can override the system’s assignments and can add new dimension fields during the data load. They can create derived measures at any time. Once the load is complete, the system presents the dimensions and measures in an “ElastiCube” available for reports and other applications.
4. Create reports and other applications: the system provides a remarkably rich development environment. Users build applications by dropping different types of objects (which the vendor calls widgets) onto dashboard pages. Widgets can make selections; display data in pivot tables, charts, calendars, and images; and execute actions including refresh data, jump to different pages, query external data sources, edit data, and export to Excel. A dashboard can have multiple pages.
The primary reporting widget is the pivot table, which itself is built by dragging dimensions into rows and columns, and the measures into cell values. Users can apply filters to widgets, such as selecting the top 10 values for a dimension. These filters can be static (a fixed list) or dynamic (reselected each time the dashboard is updated). PrismCubed also provides special features for time series calculations such as period-to-period growth and differences. That's a nice touch, because those can be quite difficult to define with conventional reporting systems.
Reporting widgets can be connected to the ElastiCube dimensions and measures or directly to SQL data sources. Users can also specify whether selections made in one widget affect the data displayed in other widgets. There are actually three options here, including complete independence, direct links from one widget to another, and global impact on other widgets. This gives more flexibility than systems that automatically apply global selections, but does force users to do more work in specifying which approach they want.
Widgets, filters and other components can be stored in a central repository and reused across applications.
5. Share applications: Users can export dashboard contents to Excel tables or can copy an entire dashboard as a static PDF. Applications, including underlying ElastiCubes, can be copied and run on another user’s PC. In addition, a Web server due for release this month (October) will let dashboard creators publish their dashboards to a central server, where other users will be able to access and modify them. The server will provide fine-grained control over what different users are allowed to change.
6. Scalability and Performance: SiSense has tested the PrismCubed engine on multiple terabytes of data. It cited one client who loaded 30 million telephone call detail records in 30 to 90 minutes. Loaded data usually takes somewhat less disk space than the original source. The system currently requires a complete reload to add new data to an existing ElastiCube, although the vendor plans to add incremental appends by the end of November. Once the data is loaded, reports within applications usually update in seconds.
7. Technology: PrismCubed stores data in a columnar data structure. It also stores a dimension map for each column, but doesn’t preaggregate the data along the dimensions. As with other columnar databases, this avoids the need for specialized data structures to handle particular queries. When data has not been preloaded into the system, PrismCubed can also run the same query across multiple external data sources.
Although PrismCubed stores the entire ElastiCube on disk, it only loads into memory the columns required for a particular query. This lets it can handle larger data sets than purely in-memory systems without massive hardware. There might be some problems if the selected columns for a query exceeded the system’s available memory.
PrismCubed runs on Windows PCs with the .NET framework installed. On 64 bit systems, this means the amount of potential memory is virtually unlimited. Although PrismCubed itself is new, a previous version of the product using the ElastiCube database engine was launched in September 2008 and has more than 6,000 users.
8. Pricing: PrismCubed is priced on an annual subscription basis, which is unusual for this type of product but common among hosted BI vendors. SisSense offers several versions of PrismCubed, ranging from a free Viewer that can only access dashboards created elsewhere, to a $1,500 per year Professional edition that allows full creation of dashboards and ElastiCubes. There are also a free version (limited to 2,000 rows of data), a $300 per year Personal edition (which can create dashboards but not share them), and a $700 per year Analyzer that can build and share dashboards but not ElastiCubes. Server pricing wasn’t quite set when I spoke with SiSense but will probably be around $3,500 per year per server.
These prices are quite reasonable compared with similar vendors, even considering the recurring annual subscription fees, particularly because the end-user Viewer is free. Price details are published on the vendor’s Web site.
SiSense PrismCubed, officially launched this past August, is another member of the growing set of business intelligence systems aimed at empowering business analysts to build their own applications. I’ve also written about QlikView and Lyza, and think there are others.
What distinguishes these tools from other business intelligence systems is they let non-technical users manipulate source data in more sophisticated ways than a spreadsheet or report writer. Specifically, data from several sources can be merged on a common key, filtered, aggregated and processed through complex formulas.
This sort of manipulation has traditionally required SQL programmers, OLAP cube designers, or similar technical experts. Allowing business analysts to do it without having to learn deep technical skills is precisely what lets them build applications with minimal external assistance. (I say "minimal" because technical staff must still handle connections to the source data.)
These systems also provide report creation and distribution. But unlike business-analyst data manipulation, those capabilities are also found in other business intelligence products.
You’ll note that my definition does NOT specify a particular database technology, such as in-memory or columnar, that the data is updated in real time, that the system is targeted at mid-sized businesses, or that results are distributed pervasively through the organization. Those have all been proposed as ways to classify business intelligence systems, and several of the products in my business-analyst business intelligence (BABI--how cute!) category fall into one or another such group. But I think it’s a mistake to focus on those other features because they don’t get at real value provided by these tools, which is the flowering of applications made possible when business analysts can create them independently.
Now that I've defined a new type of application, complete with the all-important acronym, the next step is defining an evaluation framework to help compare the competitors. I’d like to claim I do this through deep research and brilliant insights into user needs, but, in fact, I generally start with the features in the existing systems. This runs the risk of missing some critical requirement that no vendor has yet uncovered, but it saves a ton of work. And I can still argue that I’m piggybacking on the vendors’ own deep research and insights as embodied in their products.
In any event, a starter set of review criteria for BABI systems (sorry, but I find the acronym irresistible) would include:
- combine data from multiple, heterogeneous sources (relational databases, CSV files, Excel tables, etc.)
- allow non-technical users to define processing flows to manipulate the data (merge, filter, aggregate, calculate)
- present the manipulated data in a structure that’s suitable for reporting and visualization
- allow non-technical users to create applications including reports, visualizations, and (optionally) additional functions such as data refresh and export
- allow other users to view (and optionally interact with) the applications
- meet reasonable performance standards for data load, storage, response time and scalability
- use appropriate technology (actually, I don’t care if the thing is powered by hamsters. But understanding the underlying technology helps to predict where problems might arise.)
- affordable pricing (not exactly a criterion, but important nevertheless)
Obviously these criteria could be much more detailed, and no doubt they will grow over time. But for now, they provide a useful way to look at PrismCubed.
1. Combine data from multiple sources: PrismCubed provides a wizard to connect with different data sources, including SQL Server, Oracle, CSV files, Excel and Amazon S3 logs (which earns them extra coolness points). The system can read the database schemas directly, saving users the need to define basic data structures. Users have the option modify structures if they desire. A connection can be live (i.e., the source is requeried each time a report is run) or reloaded on demand from within a completed application. This provides real-time data access, which isn’t always available in business intelligence systems. The system can also reload data automatically on a user-specified schedule.
2. Allow non-technical users to manipulate source data: PrismCubed does a particularly good job here. At a basic level, users can write complex formulas to add derived fields to a table during the import process. More important, a drag-and-drop interface lets them build complex visual processing flows from standard icons including data definition, filtering, inclusion or exclusion, unions, and top or bottom selects. These flows can combine multiple data sources and include branches that generate separate output sets that are all available to use in applications.
3. Present the manipulated data for reporting: the system automatically classifies input data as dimensions (text, dates, etc.) and measures (numbers which can be aggregated). Users can override the system’s assignments and can add new dimension fields during the data load. They can create derived measures at any time. Once the load is complete, the system presents the dimensions and measures in an “ElastiCube” available for reports and other applications.
4. Create reports and other applications: the system provides a remarkably rich development environment. Users build applications by dropping different types of objects (which the vendor calls widgets) onto dashboard pages. Widgets can make selections; display data in pivot tables, charts, calendars, and images; and execute actions including refresh data, jump to different pages, query external data sources, edit data, and export to Excel. A dashboard can have multiple pages.
The primary reporting widget is the pivot table, which itself is built by dragging dimensions into rows and columns, and the measures into cell values. Users can apply filters to widgets, such as selecting the top 10 values for a dimension. These filters can be static (a fixed list) or dynamic (reselected each time the dashboard is updated). PrismCubed also provides special features for time series calculations such as period-to-period growth and differences. That's a nice touch, because those can be quite difficult to define with conventional reporting systems.
Reporting widgets can be connected to the ElastiCube dimensions and measures or directly to SQL data sources. Users can also specify whether selections made in one widget affect the data displayed in other widgets. There are actually three options here, including complete independence, direct links from one widget to another, and global impact on other widgets. This gives more flexibility than systems that automatically apply global selections, but does force users to do more work in specifying which approach they want.
Widgets, filters and other components can be stored in a central repository and reused across applications.
5. Share applications: Users can export dashboard contents to Excel tables or can copy an entire dashboard as a static PDF. Applications, including underlying ElastiCubes, can be copied and run on another user’s PC. In addition, a Web server due for release this month (October) will let dashboard creators publish their dashboards to a central server, where other users will be able to access and modify them. The server will provide fine-grained control over what different users are allowed to change.
6. Scalability and Performance: SiSense has tested the PrismCubed engine on multiple terabytes of data. It cited one client who loaded 30 million telephone call detail records in 30 to 90 minutes. Loaded data usually takes somewhat less disk space than the original source. The system currently requires a complete reload to add new data to an existing ElastiCube, although the vendor plans to add incremental appends by the end of November. Once the data is loaded, reports within applications usually update in seconds.
7. Technology: PrismCubed stores data in a columnar data structure. It also stores a dimension map for each column, but doesn’t preaggregate the data along the dimensions. As with other columnar databases, this avoids the need for specialized data structures to handle particular queries. When data has not been preloaded into the system, PrismCubed can also run the same query across multiple external data sources.
Although PrismCubed stores the entire ElastiCube on disk, it only loads into memory the columns required for a particular query. This lets it can handle larger data sets than purely in-memory systems without massive hardware. There might be some problems if the selected columns for a query exceeded the system’s available memory.
PrismCubed runs on Windows PCs with the .NET framework installed. On 64 bit systems, this means the amount of potential memory is virtually unlimited. Although PrismCubed itself is new, a previous version of the product using the ElastiCube database engine was launched in September 2008 and has more than 6,000 users.
8. Pricing: PrismCubed is priced on an annual subscription basis, which is unusual for this type of product but common among hosted BI vendors. SisSense offers several versions of PrismCubed, ranging from a free Viewer that can only access dashboards created elsewhere, to a $1,500 per year Professional edition that allows full creation of dashboards and ElastiCubes. There are also a free version (limited to 2,000 rows of data), a $300 per year Personal edition (which can create dashboards but not share them), and a $700 per year Analyzer that can build and share dashboards but not ElastiCubes. Server pricing wasn’t quite set when I spoke with SiSense but will probably be around $3,500 per year per server.
These prices are quite reasonable compared with similar vendors, even considering the recurring annual subscription fees, particularly because the end-user Viewer is free. Price details are published on the vendor’s Web site.
Friday, October 09, 2009
Survey Looks for Hostility to Behavioral Targeting, and Finds It
Summary: a new survey found that most Americans oppose behavior-based Web targeting. The authors clearly had an agenda, but the industry still needs to present its side of the story.
A recent survey conducted by professors by UC/Berkeley and University of Pennsylvania concluded (to quote its full title) that “Contrary to what marketers say, Americans Reject Tailored Advertising and Three Activities That Enable It.” Is it just me, or do I detect a bit of hostility?
The headlined finding of the survey was that 66% of respondents said they did not want Web sites to show ads tailored to their interests. As eMarketer pointed out in its article on the study, this conflicts with other surveys have found consumers receptive to targeted Web ads.
The Berkeley/UPenn study claims it is more accurate because it is the first nationally representative telephone (rather than Internet-based) survey on the topic. I doubt that really had much impact on the results. As a detailed critique by the business-friendly Progress & Freedom Foundation points out, the answers were more likely influenced by the structure of the poll itself, which asked a variety of somewhat tendentious questions leading up to the final answers.
My own critique is that the questions all asked whether people wanted to see tailored ads, not whether they preferred tailored ads vs. non-tailored ads. People may have interpreted the unstated alternative as no advertising at all. In that case, their rejection had less to do with tailoring in particular than with the near-universal dislike of advertising in general.
Still, the answers I found most interesting have received relatively little attention. This was a set of three questions that found:
- 67% of Internet users agree they have “lost all control over how personal information is collected and used by companies”, but
- 58% feel “most businesses handle the personal information they collect about consumers in a proper and confidential way” and
- 54% agree that “existing laws and organizational practices provide a reasonable level of protection for consumer privacy today”.
In other words, people have finally accepted Scott McNealy’s famous advice from 1999: “You have zero privacy anyway. Get over it”.
I’d like to end the story there, if only for artistic reasons. But the survey also asked several questions about consumers’ understanding of current privacy laws, which basically found that most people think they have more protection than they really do. Another series of questions found support for laws giving consumers rights to insist that companies delete their information.
I don’t take the results too seriously because the questions didn’t indicate these would be new laws or balance the laws against reduced free content or the cost of more regulation. But they do suggest that people might support stronger regulation if they understood how poorly they are now protected. So there continues to be a real need for marketers to both do a good job of protecting consumer privacy and of educating the public and legislators about the benefits provided by easy access to consumer information.
A recent survey conducted by professors by UC/Berkeley and University of Pennsylvania concluded (to quote its full title) that “Contrary to what marketers say, Americans Reject Tailored Advertising and Three Activities That Enable It.” Is it just me, or do I detect a bit of hostility?
The headlined finding of the survey was that 66% of respondents said they did not want Web sites to show ads tailored to their interests. As eMarketer pointed out in its article on the study, this conflicts with other surveys have found consumers receptive to targeted Web ads.
The Berkeley/UPenn study claims it is more accurate because it is the first nationally representative telephone (rather than Internet-based) survey on the topic. I doubt that really had much impact on the results. As a detailed critique by the business-friendly Progress & Freedom Foundation points out, the answers were more likely influenced by the structure of the poll itself, which asked a variety of somewhat tendentious questions leading up to the final answers.
My own critique is that the questions all asked whether people wanted to see tailored ads, not whether they preferred tailored ads vs. non-tailored ads. People may have interpreted the unstated alternative as no advertising at all. In that case, their rejection had less to do with tailoring in particular than with the near-universal dislike of advertising in general.
Still, the answers I found most interesting have received relatively little attention. This was a set of three questions that found:
- 67% of Internet users agree they have “lost all control over how personal information is collected and used by companies”, but
- 58% feel “most businesses handle the personal information they collect about consumers in a proper and confidential way” and
- 54% agree that “existing laws and organizational practices provide a reasonable level of protection for consumer privacy today”.
In other words, people have finally accepted Scott McNealy’s famous advice from 1999: “You have zero privacy anyway. Get over it”.
I’d like to end the story there, if only for artistic reasons. But the survey also asked several questions about consumers’ understanding of current privacy laws, which basically found that most people think they have more protection than they really do. Another series of questions found support for laws giving consumers rights to insist that companies delete their information.
I don’t take the results too seriously because the questions didn’t indicate these would be new laws or balance the laws against reduced free content or the cost of more regulation. But they do suggest that people might support stronger regulation if they understood how poorly they are now protected. So there continues to be a real need for marketers to both do a good job of protecting consumer privacy and of educating the public and legislators about the benefits provided by easy access to consumer information.
Tuesday, September 29, 2009
More Surveys Agree: Web and Non-Web Data Must Be Integrated
It’s not that I’m obsessive, but just to gnaw a bit more on last week’s bone about the coming unification of Web and other marketing data...
- a recent survey sponsored by enterprise marketing automation vendor Unica found that “integration with other marketing solutions” was the most commonly cited web analytics challenge (46%).
This was followed by “verifying accuracy of data (inflation/deflation)” (41%) and “not comprehensive/missing types of data” (32%). It’s interesting that the question was about Web analytics in particular – even analyzing Web results by itself requires non-Web data.
- another survey by another marketing automation vendor, Alterian, found the most-commonly cited top obstacle in online marketing (25% of respondents) was “integration of online with database marketing and offline channels”.
Now, this isn’t exactly the same answer as the Unica survey, since the question isn’t limited to data integration. But Alterian also reported that “lack of ability to assess or manage internal infrastructure and culture challenges (25%) and the integration of all the technology to power the cycle (20%) were identified as the biggest factors in implementing the customer engagement cycle.” So clearly data and system integration are indeed primary concerns for multi-channel marketing.
For still more on this topic, see today’s post on the MPM Toolkit blog, describing a very detailed report in eMarketer about Online Brand Measurement. This provides still more evidence for the need for integration of Web and non-Web data, in addition to other issues.
Case closed.
- a recent survey sponsored by enterprise marketing automation vendor Unica found that “integration with other marketing solutions” was the most commonly cited web analytics challenge (46%).
This was followed by “verifying accuracy of data (inflation/deflation)” (41%) and “not comprehensive/missing types of data” (32%). It’s interesting that the question was about Web analytics in particular – even analyzing Web results by itself requires non-Web data.
- another survey by another marketing automation vendor, Alterian, found the most-commonly cited top obstacle in online marketing (25% of respondents) was “integration of online with database marketing and offline channels”.
Now, this isn’t exactly the same answer as the Unica survey, since the question isn’t limited to data integration. But Alterian also reported that “lack of ability to assess or manage internal infrastructure and culture challenges (25%) and the integration of all the technology to power the cycle (20%) were identified as the biggest factors in implementing the customer engagement cycle.” So clearly data and system integration are indeed primary concerns for multi-channel marketing.
For still more on this topic, see today’s post on the MPM Toolkit blog, describing a very detailed report in eMarketer about Online Brand Measurement. This provides still more evidence for the need for integration of Web and non-Web data, in addition to other issues.
Case closed.
Wednesday, September 23, 2009
Web Analytics Is Dead. So Is Customer Centricity. I Need a Drink.
Summary: Web analytics is merging into the broad world of marketing measurement across all media, which itself is shifting focus from tracking individuals to understanding group behavior. Although Web analytics and marketing automation vendors are currently wrestling over who will house customer data, both are likely to lose custody to enterprises who want to control their data for themselves.
Even as analysts are still sorting through the implications of last week’s acquisition of Omniture by Adobe, the industry saw two additional important announcements this week: Omniture combining its data with comScore to help measure Web advertising audiences, and Nielsen working with Facebook to poll consumers on advertising impact.
Both announcements share several interesting features: they don't rely on traditional Web analytics (tracking page views); they involve vendors who report data from consumer panels; and they relate to measuring advertising measurement. Maybe they coincided simply because the big Advertising Week conference is now under way. But I think they, along with the Omniture/Adobe deal itself, hint at something more profound: the end of Web analytics as we know it.
Ok, that may not be as earth-shattering as the end of several other things you might imagine. But many marketers are just getting their arms around traditional Web analytics. So it’s worth warning them that things are about to change again.
Smarter Content on the Way
Let’s start with Omniture/Adobe. After thinking about it for a week (and hearing what the participants said), I think the main purpose of the deal was to let Adobe build content that was more intelligent in two ways:
- First, the content will be inherently “instrumented” to report how, when, where and which people are consuming it, using techniques go beyond traditional Web analytics methods (server logs, Javascript tags and cookies). This is needed because content increasingly exists outside of plain vanilla Web pages that can be tracked with conventional techniques. Problems include Flash, video, audio and other non-HTML Web content; venues like mobile, digital video recorders and interactive TV; widgets that migrate through social networks; and plain old cookie deletion. Web analytics vendors are striving to extend their technologies to capture these, but at some point you have to look for a different basic model. Content that can itself “phone home” rather than relying on the carrier medium could be the long-term answer.
- Second, content will be self-optimizing. This involves built-in tests and, perhaps, a sort of swarm intelligence where subsequent views are actually modified based on previous results reported by the content itself. Imagine a widget with a built-in A/B headline test: every time someone accesses it, the widget offers one headline or the other, and reports the result to a central server. (This could be done without transmitting personally identifiable information, so privacy issues are minimal.) Once a pattern emerges, the server could instruct the distributed widgets to only display the winning headline, or, better still, to start a new test. Even without a central server, each copy of the widget could still run its own test and, assuming it’s accessed enough times, adjust all by itself.
Who Owns The Data?
So far so good, and I think that’s plenty of reason to justify spending $1.8 billion for Omniture. But I also think Adobe was interested in the fact that Omniture controls so much of its clients’ data.
There is a battle brewing over that issue: like most Web analytics vendors, Omniture stores Web traffic data on its own servers and sells clients the ability to access that data. That didn’t raise any particular business issues when Web data was viewed largely in isolation. But as the Web takes an increasingly central role in customer contacts, marketers need to merge that Web data with their other customer information. Indeed, if you want to use that data to help guide customer interactions across channels, the data must be not just centralized but also updated in real-time. That means marketers either give all their non-Web data to their Web analytics vendor, or directly capture Web analytics data on their own servers.
The Web analytics vendors see this future and recognize that they’ll be more important to their clients, and thus able to charge higher fees, if they hold everything. Marketing automation vendors and in-house IT groups see the same future and recognize the threat to their own positions. Thus, the business-oriented marketing automation vendors (i.e., demand generation vendors: Eloqua, Silverpop, Marketo, etc.) already capture Web behavior in their own systems and integrate it directly with customer management. The big consumer-oriented marketing automation vendors (SAS, Teradata, Unica) also offer Web analytics, although perhaps less tightly integrated.
The problem here is that the Web analytics vendors and demand generation vendors are largely SaaS systems, so both hold the integrated customer data outside of the client’s own data center. It’s not clear that clients – especially big enterprise clients – will continue to accept this. The consumer-oriented marketing automation vendors already largely support on-premise configurations, so they may be the real winners in this battle. Yet bear in mind that looming behind the marketing automation vendors are the enterprise CRM vendors, who also offer largely on-premise installations. They may eventually gobble up the marketing automation business and the Web analytics data along with it. In that case, Web analytics vendors who hope to become rich stewards of centralized customer databases will be very disappointed.
Customer-Centricity Is Obsolete
I also think there may be one still deeper trend at play here, although this is more speculative. Let’s call it a shift from customer-centric to community-centric marketing. Since customer centricity has been the ultimate goal of marketers, or at least marketing gurus, for several decades, I expect some skepticism.
But think of it this way: marketing has always been about deploying and propagating messages to consumers. In recent years, we’ve striven and become technically more able to target those messages directly at individuals. Yet messages were never really limited to one person. Even if they were delivered privately, they could be shared directly through conversation, physical and electronic pass-along, and indirectly as consumers discussed their experiences with the company in general. Thus, there has always been a community component to marketing campaigns. In cases such as word of mouth programs, this was even the primary objective.
Today, of course, that sort of sharing has become increasingly important for every marketing project. Thus marketers have more need to track the secondary impact of their messages on the larger community. Happily, they also have more technology to do the tracking.
Here’s what’s interesting, though. Marketers will never be able to trace the exact path of each message from one person to another. And even if the data were available, there were no privacy constraints and they could handle the volume, marketers would still face the insurmountable challenge of that multiple messages influence final behavior. That is, they could never meaningfully say that one particular message was the single reason a customer did something. All they can ever do is to look at the many different messages a customer probably received and compare these with actual behavior. If the customer did what you wanted, the messages somehow worked.
If this sounds familiar, it should: it’s the classic problem faced by brand marketers in measuring the value of their investments. Their solution has always been to measure intermediate variables such as consumer attitudes, and to measure these through samples rather than by polling everyone in the market.
This brings us full circle to the panel-based attitudinal research at the core of the Omniture/comScore and Nielsen/Facebook deals. Once you recognize that what’s most important is the broad community impact of your marketing efforts, you fall back on those types of measures rather than attempting the impossible, and impossibly expensive, task of tracing the exact path followed by each individual. In other words, what we’re seeing here is not some Mad Men-style reversion to obsolete brand marketing behaviors, but a recognition that modern marketing is community-driven, so its measurements must be as well.
Now, if I can just find a reason to bring back the three-martini lunch….
Even as analysts are still sorting through the implications of last week’s acquisition of Omniture by Adobe, the industry saw two additional important announcements this week: Omniture combining its data with comScore to help measure Web advertising audiences, and Nielsen working with Facebook to poll consumers on advertising impact.
Both announcements share several interesting features: they don't rely on traditional Web analytics (tracking page views); they involve vendors who report data from consumer panels; and they relate to measuring advertising measurement. Maybe they coincided simply because the big Advertising Week conference is now under way. But I think they, along with the Omniture/Adobe deal itself, hint at something more profound: the end of Web analytics as we know it.
Ok, that may not be as earth-shattering as the end of several other things you might imagine. But many marketers are just getting their arms around traditional Web analytics. So it’s worth warning them that things are about to change again.
Smarter Content on the Way
Let’s start with Omniture/Adobe. After thinking about it for a week (and hearing what the participants said), I think the main purpose of the deal was to let Adobe build content that was more intelligent in two ways:
- First, the content will be inherently “instrumented” to report how, when, where and which people are consuming it, using techniques go beyond traditional Web analytics methods (server logs, Javascript tags and cookies). This is needed because content increasingly exists outside of plain vanilla Web pages that can be tracked with conventional techniques. Problems include Flash, video, audio and other non-HTML Web content; venues like mobile, digital video recorders and interactive TV; widgets that migrate through social networks; and plain old cookie deletion. Web analytics vendors are striving to extend their technologies to capture these, but at some point you have to look for a different basic model. Content that can itself “phone home” rather than relying on the carrier medium could be the long-term answer.
- Second, content will be self-optimizing. This involves built-in tests and, perhaps, a sort of swarm intelligence where subsequent views are actually modified based on previous results reported by the content itself. Imagine a widget with a built-in A/B headline test: every time someone accesses it, the widget offers one headline or the other, and reports the result to a central server. (This could be done without transmitting personally identifiable information, so privacy issues are minimal.) Once a pattern emerges, the server could instruct the distributed widgets to only display the winning headline, or, better still, to start a new test. Even without a central server, each copy of the widget could still run its own test and, assuming it’s accessed enough times, adjust all by itself.
Who Owns The Data?
So far so good, and I think that’s plenty of reason to justify spending $1.8 billion for Omniture. But I also think Adobe was interested in the fact that Omniture controls so much of its clients’ data.
There is a battle brewing over that issue: like most Web analytics vendors, Omniture stores Web traffic data on its own servers and sells clients the ability to access that data. That didn’t raise any particular business issues when Web data was viewed largely in isolation. But as the Web takes an increasingly central role in customer contacts, marketers need to merge that Web data with their other customer information. Indeed, if you want to use that data to help guide customer interactions across channels, the data must be not just centralized but also updated in real-time. That means marketers either give all their non-Web data to their Web analytics vendor, or directly capture Web analytics data on their own servers.
The Web analytics vendors see this future and recognize that they’ll be more important to their clients, and thus able to charge higher fees, if they hold everything. Marketing automation vendors and in-house IT groups see the same future and recognize the threat to their own positions. Thus, the business-oriented marketing automation vendors (i.e., demand generation vendors: Eloqua, Silverpop, Marketo, etc.) already capture Web behavior in their own systems and integrate it directly with customer management. The big consumer-oriented marketing automation vendors (SAS, Teradata, Unica) also offer Web analytics, although perhaps less tightly integrated.
The problem here is that the Web analytics vendors and demand generation vendors are largely SaaS systems, so both hold the integrated customer data outside of the client’s own data center. It’s not clear that clients – especially big enterprise clients – will continue to accept this. The consumer-oriented marketing automation vendors already largely support on-premise configurations, so they may be the real winners in this battle. Yet bear in mind that looming behind the marketing automation vendors are the enterprise CRM vendors, who also offer largely on-premise installations. They may eventually gobble up the marketing automation business and the Web analytics data along with it. In that case, Web analytics vendors who hope to become rich stewards of centralized customer databases will be very disappointed.
Customer-Centricity Is Obsolete
I also think there may be one still deeper trend at play here, although this is more speculative. Let’s call it a shift from customer-centric to community-centric marketing. Since customer centricity has been the ultimate goal of marketers, or at least marketing gurus, for several decades, I expect some skepticism.
But think of it this way: marketing has always been about deploying and propagating messages to consumers. In recent years, we’ve striven and become technically more able to target those messages directly at individuals. Yet messages were never really limited to one person. Even if they were delivered privately, they could be shared directly through conversation, physical and electronic pass-along, and indirectly as consumers discussed their experiences with the company in general. Thus, there has always been a community component to marketing campaigns. In cases such as word of mouth programs, this was even the primary objective.
Today, of course, that sort of sharing has become increasingly important for every marketing project. Thus marketers have more need to track the secondary impact of their messages on the larger community. Happily, they also have more technology to do the tracking.
Here’s what’s interesting, though. Marketers will never be able to trace the exact path of each message from one person to another. And even if the data were available, there were no privacy constraints and they could handle the volume, marketers would still face the insurmountable challenge of that multiple messages influence final behavior. That is, they could never meaningfully say that one particular message was the single reason a customer did something. All they can ever do is to look at the many different messages a customer probably received and compare these with actual behavior. If the customer did what you wanted, the messages somehow worked.
If this sounds familiar, it should: it’s the classic problem faced by brand marketers in measuring the value of their investments. Their solution has always been to measure intermediate variables such as consumer attitudes, and to measure these through samples rather than by polling everyone in the market.
This brings us full circle to the panel-based attitudinal research at the core of the Omniture/comScore and Nielsen/Facebook deals. Once you recognize that what’s most important is the broad community impact of your marketing efforts, you fall back on those types of measures rather than attempting the impossible, and impossibly expensive, task of tracing the exact path followed by each individual. In other words, what we’re seeing here is not some Mad Men-style reversion to obsolete brand marketing behaviors, but a recognition that modern marketing is community-driven, so its measurements must be as well.
Now, if I can just find a reason to bring back the three-martini lunch….
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