ReachForce Buys SetLogik: One-Stop-Shopping for B2B Marketing Data Plus Database

B2B marketing data vendor ReachForce today announced its purchase  of SetLogik, which provides technology to build cloud-based marketing databases and do predictive modeling against them. (See my post from last October for more on SetLogik.)

There’s an obvious peanut butter-meets-jelly type of logic to this match. Reachforce’s core business is assembling data on marketing prospects, which it then sells for as many uses as possible: appending to Web leads, enhancing existing databases, and buying as lists. The SetLogik acquisition takes this a step further by letting them build databases to hold their data, thereby expanding the market beyond people with a database already in place. Conversely, having a readily-available data source encourages marketers to build their own database. SetLogik’s predictive modeling features make it even easier for marketers to get a return on their investment once the database is in place. Everybody wins!

The two products will be combined in what ReachForce calls the “Connected Marketing Data Hub”. The name is frightfully generic, but the key points are:

• cloud-based system, making it easy to deploy
• comprehensive customer view including data from marketing automation, CRM, transaction systems, and ReachForce’s own sources
• continuously updated and cleansed
• connectors available for Salesforce.com, Eloqua, and Marketo  

In other words, the ReachForce solution supplements rather than replaces your marketing automation or CRM database. As I wrote in my earlier SetLogik review, one particularly attractive result is the ability to match sales revenues with marketing leads, always a challenge in measuring the value of marketing programs.

ReachForce has just begun to offer the combined system, which is currently deployed at one pilot client. Pricing is based on data volume, whether the client wants a one-time append or continuous cleaning, and on the data sources included. Minimum is $625 per month for continuous cleaning on 50,000 records.

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.

Marketing Automation Beer Goggles: What I Think I Learned at Dreamforce

I’m writing this on my way home from Dreamforce, the Salesforce.com user conference that has become the primary industry gathering for marketing automation vendors. With a reported 90,000 attendees (I didn't count them personally), the show is fragmented into many different experiences. My own experience was mostly talking to marketing technology vendors in the exhibit hall, private meetings, and maybe a party or two. I did attend the main keynote and the “marketing cloud” announcement, but neither contained  major product news and the basic story – that social networks change everything – was true but far from novel.

So what did I learn? On reflection, there were two themes that hadn’t expected when I arrived.

The first was data. I generally think of marketing systems as relying primarily on data from the company’s own marketing, sales, and operational systems. But the exhibit hall was filled with vendors offering information – mostly from Web crawling or social media – to supplement the company’s internal resources. Of course, this isn’t new but it seems that external sources are becoming increasingly important. The main reason is so much valuable public information is now available. A lesser factor may be that there’s less internal information, at least for sales and marketing, because so many prospects engage indirectly and anonymously until deep in the buying process.

But there’s more to data than the data itself. The theme includes easier connectivity to external data, via standard connectors in general and the Salesforce.com AppExchange in particular. A closely related trend is real-time, on-demand access to the external data: say, when a salesperson views a lead record or a lead is first added to marketing automation. This requires immediate matching to find the right person in the supplier’s database, and, sure enough, matching was another popular technology on the show floor. I also saw broader use of Hadoop to handle all this new data: as you probably know, Hadoop effectively handles large volumes of unstructured and semi-structured data, so it’s a key enabling technology for data expansion. A final component is continued growth in the reporting, analytics, and predictive modeling systems that make productive use of the newly-available data.

Some products combine all these attributes, others offer a few, and some just one. Obviously a single integrated solution is easiest for the buyer, but as Scott Brinker recently pointed out in an insightful blog post, platforms like Salesforce.com may actually make it practical for marketers to mix and match individual products without the technical pain traditionally associated with integration. It therefore makes sense to view the data-related systems as a cluster of capabilities that will develop as parts of single ecosystem, collectively raising the utility and importance of external data to marketers.

The second theme, considerably less grand, was lead scoring. I suppose this is really just a subset of the analytics component of the data theme, but I saw enough new lead scoring features from enough different vendors to treat it separately. In particular, predictive modeling vendor KXEN announced a free, cloud-based service to automatically score a new Salesforce.com lead’s likelihood of converting into a contact. (If you’re not familiar with Salesforce.com terminology: contacts are linked to an account, while leads are not. The conversion usually indicates the salesperson has deemed the person a valid prospect and is thus a critical stage in most sales processes.)

The KXEN service requires absolutely no set-up; users just install it from the AppExchange. KXEN then reads the data, builds a predictive model based on past results, and returns the scores on current leads. From a technical standpoint, the modeling is nothing new, and indeed the people I met at the KXEN booth seemed to feel the product was barely worth discussing. But I’ve long felt that an automated, predictive-model-based scoring service was a major business opportunity because it would replace the time-consuming, complicated, and surely suboptimal lead scoring models that most companies now build by hand, usually with little basis in real data. Of course, there are plenty of other predictive modeling systems available for marketers, but I’m excited because I don’t think anyone else has made model-based lead scoring as simple as the KXEN offering. Maybe I need to get out more.

Speaking of which, I met SetLogik at a loud party after several glasses of wine, so I may have been wearing the marketing technology equivalent of beer goggles. But if I understood correctly, it tackles the really hard part of revenue attribution by using advanced matching technologies to connect the right leads and contacts to sales (reflected in closed opportunities in Salesforce.com). Once you’ve done that, determining which marketing touches influenced those people is relatively easy.  It’s a unique solution to a huge industry problem. Come to think of it, correct linkages are also critical for building effective lead scoring models, which it turns out that SetLogik also does. (I'll admit it: I Googled them the next day.) So they're part of that theme as well.

As I mentioned earlier, data and lead scoring were themes that emerged for me during the conference. I did have some other themes in mind when I started, which are also worth sharing. I’ll do that another day.

Finally, it’s worth noting that the conference itself was tremendously well run. It sometimes felt that one-third of those 90,000 people were Salesforce.com employees hired to stand around and answer questions. Where they found so many cheerful people outside of the Midwest I’ll never know. Congratulations and thanks to the Salesforce.com team that made it happen.