0 SetLogik Offers B2B Marketers a Real Marketing Database

I’ve now done more detailed research into the SetLogik B2B data management system I mentioned in my Dreamforce post.  If anything, I’m even more impressed.

I originally saw SetLogik as a tool to associate marketing leads with sales opportunities, even when they are not connected directly within Salesforce.com. That’s important in itself, since those missing links are the greatest obstacle to showing the value of B2B marketing efforts through revenue attribution.

But the bigger story, which SetLogik itself recognizes clearly, is that they’re creating a real marketing database. This has been sadly lacking in most B2B marketing automation systems, which supplement the Salesforce.com database with barely-extensible lead profiles and contact histories. In fact, I’ve recently taken to citing the B2B systems' fixed, built-in database as the fundamental difference distinguishing them from B2C systems, which connect to externally-managed databases with any structure.

SetLogik doesn’t replace the database built into the B2B systems.  Rather, it creates a separate database that merges data from marketing automation, Salesforce.com (or, potentially, any other CRM system), and whatever other sources a company has available. The matching capabilities that initially caught my eye are just one part of a larger suite of functions to load, clean, standardize,  merge, and enhance B2B data, ultimately storing it within a database where it can be used with SetLogik tools for segmentation, selection, reporting (including attribution), and predictive model-based lead scoring. Cleansed data and results such as lead scores can be fed back into CRM and marketing automation systems for direct access by their users. SetLogik’s own diagram expresses this separation reasonably well, although I would have suggested they clarify that there’s an independent, persistent database within their cloud.
 

As consumer marketers learned long ago, building a serious marketing database is a big project. The challenge is even greater in B2B, which manages two data levels, companies and contacts, instead of just one level of consumers.  It’s no wonder that B2B marketing automation vendors avoided the issue by piggybacking on the Salesforce.com structure: otherwise, the cost and complexity of building a separate database would have severely limited their growth.

SetLogik’s addresses the problem directly, by creating a nearly-automated system to build the database. The company promises to deliver a completely functional database within 60 days, and to deliver the database plus predictive lead scoring models in 90 days. Compared with the many months or years needed to deploy a traditional marketing database, this is lightning quick.

I call the system “nearly-automated” because a SetLogik analyst works with each client to set up the data preparation steps, tweaking the standard rules and processes as necessary, and because the predictive models are also built by human analysts. These are advantages, not flaws, since a skilled user adds substantial value to both processes. The system still does most of the work, so the initial data quality set-up takes just a few hours of labor – although the full process typically takes several days because clients need time to make decisions. Similarly, modeling takes about two weeks – again, more wait time than work time.  In fact, the model building is so efficient that the company includes it for free in its Enterprise edition, which starts at $1,400 per month for up to 25,000 records.

None of this would matter if the quality of SetLogik’s results were poor. But, while I haven’t run a test, the company certainly describes the features I'd want. Standard inputs include leads, contacts, campaign members, accounts, and opportunities from Salesforce.com, plus leads and activities from marketing automation. Data preparation includes standardization and verification of addresses in the U.S., Canada, United Kingdom, Australia; phone numbers verification for North America; email format verification (but not sending test emails); table-based transformations and coding for elements like titles and sales territories; and enhancement with client-licensed external data such as D&B listings.

The matching engine uses multiple rule sets, supports both similar and exact matches, and can compare data across several fields (such as mobile vs. home vs office phone number). The system will match at individual and company levels and can link individuals to companies. It will choose the best value for each field and return a consistent best record to all source systems. Predictive modeling can include derived variables, such as number of emails received, as well as raw inputs. The system’s database stores snapshots of old data values so it can track changes and trends. New and changed records run through the system at user-determined intervals that can be frequent as hourly.

The system doesn’t provide an interface for end-users to set their own data processing rules, although one is planned. As SetLogik correctly argues, very few B2B marketers have the interest or skills to do this. In fact, the company’s larger problem is that so few marketers even recognize they need better data cleansing, let alone a separate marketing database. This will likely limit SetLogik's initial clients to the upper tier of sophisticated marketers who do see the problem.  We can hope that the importance of a serious marketing database will eventually become clear to everyone.

SetLogik is a Software-as-a-Service application, available directly from the company or through the Salesforce.com AppExchange. The system has an Eloqua connector today and a Marketo connector in the works. The company promises basic implementation in 60 days, although it is usually much less, and full implementation including predictive modeling in 90 days.

Pricing is based on the system edition and number of records (unique individuals and companies). The Express Edition, starting at $500 per month for 25,000 records, builds the database and feeds the cleansed, enhanced records back to Salesforce.com and marketing automation. Professional Edition, starting at $1,000 per month, adds segmentation, list building, attribution, and other reporting. Enterprise Edition, starting at $1,400 per month, offers all the other features plus predictive lead scores. The price tag gets more serious for large systems – Enterprise costs about $11,000 per month for one million-records – but is still much less than a conventional marketing database. In fact, SetLogik points out that some services built into the price, such as address and phone verification or access to lead profiles within Salesforce.com, would ordinarily cost nearly as much as the entire SetLogik fee if purchased separately.

SetLogik officially released its system in October 2011 and now has several large enterprise clients.

0 B2B and B2C Marketing Automation: Understanding the Differences

As you might have guessed from my recent list of B2C marketing automation systems, I’ve recently been spending some time helping consumer marketers to select vendors. This is more a return than a departure: although I’ve written mostly about B2B systems for the past few years, my earlier work was largely in consumer marketing. Like any traveler, I’ve returned home with some new perspectives. Here are some observations

- consumer marketers have to build databases; B2B marketers don’t. You can file this under “things so obvious that it feels stupid to even mention them”, but it’s still an important difference. In setting up a consumer marketing system, the primary discussion is always around where the data will come from and how it will be managed. This accounts for most of the work and most of the cost. By very sharp contrast, B2B marketers rely primarily on their CRM system (that is, Salesforce.com or a competitor) as the primary data source, and complement that with information captured directly by the marketing automation systems’ own landing pages and Web tracking tags. The CRM integration can be set up in days, if not minutes, and next to no time is spent worrying about the marketing database design or update processes.

On the whole, this situation is an advantage for B2B marketers, since they can direct their attention to other issues and can start using their systems almost immediately (for simple tasks, at least). But it also means that B2B systems are much less flexible than B2C marketing automation systems, since the B2B systems are built around a fixed data structure that is derived from the CRM data model. Only a few B2B vendors can add custom tables to systems and I doubt any could accommodate a fundamental departure from the core CRM data structure.

The main practical implication of this is that consumer marketers would have a hard time using a B2B system. (So do the largest B2B marketers, who also need specialized data structures and update processes.) This is frustrating for consumer marketers, who see the huge variety, slick features, and attractive pricing of the B2B systems. Some B2C systems offer similar features and pricing with the same Software-as-a-Service business model. But the total costs are still higher because someone has to build and maintain the underlying database.

- B2B systems include landing pages and web behavior tracking; most B2C systems don’t. It’s technically possible for B2C systems to offer these features, and some do. But many B2C products leave them out. I’d guess the reason is B2C marketers more often have the capabilities available from other sources, such as a Web content management system or Web analytics product. We can probably expect more B2C systems to add them as vendors see that marketers like having them integrated with their primary system.

- B2B systems are cheaper. B2B marketing automation systems start around $750 per month, or under $9,000 per year, and a typical B2B installation probably runs under $30,000 per year. By contrast, it’s pretty much impossible to imagine a B2C system that costs less than $50,000 per year. As I mentioned earlier, that’s really frustrating for B2C marketers.

- B2C deployments are easier. This might spark some debate. But B2C marketers don’t have to deal with marketing-sales alignment, can usually measure results directly, and are often already running the same types of campaigns they expect to run with marketing automation. This means there’s less need for process reengineering, program design, content development, and the other changes that often trip up B2B marketing automation projects. Of course, the exception is building that new marketing database, which I’ve already noticed is much harder for B2C. But the need for the database is obvious from the start and plenty of experts are available to help. So I’d say the risks of a failed deployment are much lower for B2C.

These are simply the differences that pop out as I look at consumer marketing systems with fresh eyes. Further thought might reveal others.  What’s intriguing is that B2B marketers, often considered less sophisticated than their B2C cousins, may actually be more advanced in some ways. It’s worth putting aside the old attitudes and considering what each group can learn from the other.

0 Coremetrics Survey: Online Marketers Eager to Consolidate Data Across Channels

Summary: a survey sponsored by Coremetrics shows that online marketers are eager to merge data from multiple sources. This is the long-term solution to closing the gap between database and digital marketers.

I was debating yet another post on database vs digital marketing when I saw a Direct Newsline headline that said “Online Marketers Talk The Talk, But Don't Walk The Walk”. The accompanying article suggested the online marketers don’t give personalization a high priority, which supports the theme of my last few posts. Sweet.

But reality proves a bit more complex.

The article referred to a survey of online marketers sponsored by Web analytics vendor Coremetrics. As the headline suggests, about three-quarters of the marketers listed personalized email, display advertising and onsite pages as a high priority, but just under half are actually using them. So, yes, there’s more talking than walking.


But a closer look* shows that the “future priority” numbers are also related to current deployment: items like basic email marketing have low future priority scores because they’re already in widespread use. So the apparent discrepancy in the personalization rankings is less because online marketers don’t really care about it, than because they’ve had other, more fundamental things to do first.

If I were feeling particularly tendentious, I could argue other data in survey supports my claim that digital marketers are relatively disinterested in personalization. For example, “manual onsite cross-selling promotions and product recommendations” has a higher deployment rate (63%) than “manual onsite personalized content and recommendations” (49%). But a simpler explanation is that personalized recommendations are just technically harder. Indeed, the two “technology-driven” options, recommendations based on individual behavior and on “wisdom of the clouds”, have the lowest of all current deployment rates.

That said, it’s still interesting that the survey shows personalized email (52% deployed) as not significantly more common than personalized advertising (50%) or personalized site content (49%). This seems to contradict my position: if email is run by personalization-oriented database marketers, while Web advertising and (perhaps) site content are run by behavioral-targeting-oriented digital marketers, then email personalization should be more common.

But the actual question asks about email, display advertising and onsite content which are personalized "based on individual online behavior”. This adds the additional constraint of whether marketers have been able to tie (mostly anonymous) online behavior to other channels. That constraint applies across all the delivery channels, and is likely why the deployment rates are so similar. Surely the vast majority marketers are personalizing their email using information in their databases, particularly if you extend the definition of "personalization" to include segmentation that determines which messages are sent to whom.

A separate question asked marketers to rate the importance of automating different marketing tools.


What's interesting about those answers is that five of the top six didn't involve individual-level data: three are about campaign, channel and vendor performance, and the other two are about search keywords in aggregate. The only exception, "personalized content or product recommendations based on online behavior" is based on reusing data within a single channel, which means that individuals need not be personally identified. (The survey makes clear that its definition of "personalization" includes treatments based on anonymous behavior tracking.) Actually, the two applications that do rely on consolidating personal data across channels are the lowest ranked of all the options presented. I'd say this supports my fundamental contention that digital marketers are mostly concerned about non-personal, channel-specific applications.

On the other hand, respondents did rate “obtaining an integrated view of customers across online marketing touch points” as their highest challenge, or at least as a tie with measuring marketing impact. Since it was only listed by 45% of the respondents, I could speculate that those might have been the database (email) marketers in the group, while the digital (Web) marketers could have all ignored it.

But I’m not inclined to bother: I have no problem believing that digital marketers are perfectly willing, even eager, to consolidate data across channels when it’s possible. My main point is consolidation is generally not possible because most digital touchpoints do not collect identifiable, addressable information. (See yesterdays’ post for my definitions of those terms.) And, because consolidated data is often not available, the digital marketers have learned to work without it.


By contrast, Coremetrics is focused on a future (or, perhaps, imaginary) world where data-gathering techniques have improved. Coremetrics is arguing, and I fully agree, that consolidating data across channels does add value and that marketers should be willing to invest in making it happen.

In fact, if I hadn’t seen the survey this morning, my intent was to write about the convergence of database and digital marketing, precisely because digital marketers are increasingly aware of the value and possibilities of working from a consolidated database. So even though I’ve been arguing that database and digital marketing today are quite different, I do think they’ll become more similar over time as each group learns from the other. The marketers themselves are already leading in that direction, and vendors who want to survive will surely follow.

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* very close indeed. Sorry for the small print in the charts. It's the best I could do. The actual data is available in the surveys.