0 Mintigo InterestBase Harvests Web and Social Data for Marketing and Sales

Every marketer recognizes that the Web and social media could be rich sources of information about customers and prospects. But harvesting that data has been frustratingly difficult.  Doing it yourself  takes multiple tools to gather different kinds of information, and then patching the result together into personal profiles. Most tools do little more than keyword searches, which only capture a fraction of the potential information and only cover keywords that marketers know in advance are important.

More advanced technology does exist. Semantic engines can extract information such as executive changes and product announcements from press releases and social media profiles. Sentiment analysis can (with limited reliability) detect the attitudes that individuals express. Identity aggregators can link email, social media, and other addresses for the same individual. Predictive models can show how different attributes correlate with targeted behaviors such as purchasing a product.

Few marketers have the skill or resources to pull all these tools together for themselves. Vendors are another matter: there’s inherent scale economy to scanning the Web and social media once and applying the results to many different clients. I recently wrote about Lattice Engines,  which has assembled these pieces to create prospect lists. Infer starts with your own customer data, enhances it with information mined from the Web, and generates predictive scores.

Mintigo has also been mining Web and social data to build prospect lists, starting in 2011. This week it announced a new platform, InterestBase, that gives clients an interface to define target groups, analyze group members’ interests, push prospect lists to marketing automation and CRM systems, and enhance individual lead records.

The foundation of InterestBase is a central repository of 30 million names and 3 million companies (and growing), built by scanning Web sites and social media for job postings, product and technology names, group memberships, accounts followed, hashtags, Javascript calls, and other information. The system uses this data to assign individuals and companies such attributes as job title, company size, technologies used, hiring plans, and interest scores for products and topics. Marketers can use titles and other attributes to define their own target groups, called personas.

Lists containing members of a persona can be assigned to marketing campaigns and sent to external marketing automation or CRM systems for execution. Connectors are currently available for Marketo and Salesforce.com, with an Eloqua connector due soon. A campaign list can include the entire persona universe or a quantity specified by the user. Once the campaign is run, responders are loaded back into Mintigo and the system will identify attributes that distinguish them from non-responders.

Clients can also upload their own lists of customers or campaign respondents.  Mintigo will determine which attributes correlate with group membership, display the most important ones in reports, and use the findings in predictive models that score the entire database on likelihood of purchase or response. Clients can also upload other lists for Mintigo to enhance with its own information. This enhanced data can be used in lead scoring or to help guide salespeople.  External systems like Web sites can also accessed the data in real time via API calls.

The features are interesting, but what really matters about Mintigo is the data: fresh, powerful, and unique information about a large share of the business universe. Richer information lets Mintigo clients identify new prospects they’d otherwise miss, distinguish strong prospects from weak ones, and target messages to each prospect’s interests. The result is substantially more effective marketing and sales operations, finally letting marketers use data the Web has so tantalizingly exposed.

In case you're wondering, I do consider Mintigo a Customer Data Platform: it assembles a persistent customer database, uses predictive models to classify the members, and makes the data available to external systems for marketing execution.  

Pricing for InterestBase is based on the number of names in the client’s prospect pool, based on automated analysis of their actual customers. An average client starts around $3,000 per month.

0 Salesforce.com and Oracle Buy Social Marketing Systems: Not the End of Marketing As We Know It

Salesforce.com yesterday announced agreement to buy social media publishing vendor Buddy Media for $689 million, thereby adding another big fluffy piece to its “marketing cloud”. Oracle followed suit this morning  with an acquisition of social media monitoring and semantic analysis vendor Collective Intellect. This followed Oracle’s $300 million acquisition last month  of social publishing system Vitrue. Just for symmetry, it’s worth pointing out that Salesforce.com acquired its own social monitoring system, Radian6, in March 2011.

What are marketers to make of all this activity, not to mention Marketo’s acquisition in April  of social marketing vendor Cloud Factory? Is this the death of marketing as we know it?

In a word, no. Social media are certainly a new way to hear what buyers are saying and send them marketing messages. But only the most besotted booster would argue that it will replace, rather than supplement, traditional methods. Every serious marketer already recognizes this, so I’m not even being boldly contrarian by saying it out loud.

The more interesting question is whether social media can be the foundation of a company’s marketing infrastructure. Both Marketo and Oracle already offer robust marketing platforms, so they presumably see social media as a supplement rather than a replacement. (It’s possible that Marketo hopes to reinvent itself as a social media specialist, which is surely more attractive to investors than marketing automation. The key positions taken by Cloud Factory executives might even support the theory.  But Marketo hasn’t hinted at this approach.)

Salesforce.com is another story.  They’ve always avoided traditional marketing automation, so perhaps they feel a complete “marketing cloud” can be built without it.

The gaps in this approach are obvious to anyone familiar with standard marketing automation systems: no Web behavior tracking, no multi-step nurture campaigns, no marketing resource management. But Salesforce.com could close those gaps by gradually extending its existing products. This might actually be easier than acquiring a separate marketing automation system and shoe horning it into other Salesforce.com components.

One thing I don’t see is social media systems themselves expanding to be marketing automation platforms. So far as I know, the data structures within the social media systems are simple contact profiles – little more than flat files – which can’t easily be extended to store and analyze detailed activity histories across multiple channels. Nor does a standard social media publishing or monitoring platform have the multi-step, branching campaign flows that are the heart of marketing automation. It’s probably easier to add social marketing functions to a marketing automation platform than the other way around. Indeed, many marketing automation vendors have already started.

So, back to the original question: what do these acquisitions mean? I’d say they’re good news for marketers, who will increasingly find social marketing functions available within core marketing platforms, ending the need to integrate separate products. The acquisitions are more problematic for marketing automation vendors, who now need to build, buy, or connect with social marketing systems to remain competitive. This will make it still harder for smaller vendors to compete, hastening the industry consolidation we all know is coming anyway. Nothing boldly contrarian about that prediction either, but it’s still worth bearing in mind.