Predictive analytics vendor Fliptop today announced its acquisition by B2B social network LinkedIn. It’s an interesting piece of news but I’m personally disappointed at the timing because I have been planning all week to write a post about the relationship between predictive analytics and account-based marketing (ABM). I would have looked so much more prescient had they announced the acquisition after I had published this post!
The original inspiration for the planned post was a set of three back-to-back conversations I had last Friday with one ABM vendor and two predictive analytics companies (none of which were Fliptop or LinkedIn). The juxtaposition highlighted just how much predictive and ABM complement each other. In fact, the relationship is so obvious that it almost seems unnecessary to lay it out: predictive vendors help marketers find accounts to target; ABM helps marketers reach target accounts. You can safely assume that both sets of vendors have noticed the relationship and that many are working to combine the two techniques. The Fliptop/LinkedIn deal is just more evidence of the connection.
To move past the very obvious, ABM vendors – whose basic business is selling ads targeted to specific companies – could also use predictive analytics to refine their ad targeting. This could mean selecting the best people to reach within targeted accounts or selecting the most effective ad placements to reach those accounts. This requires integration of predictive analytics within the ABM product, not just using predictive before ABM begins. I expect LinkedIn will use Fliptop’s capabilities in these ways among others.
But, getting back to last week’s conversations, what really struck me was a less obvious connection of ABM and predictive to content. Two of the vendors described using their systems to select which content to send to specific accounts or individuals. These selections are based on previous behavior, something that certainly makes sense. But I don’t generally recall hearing ABM or predictive vendors discussing as one of their applications. It’s an important idea because it promises to improve results by delivering more relevant content for the same price. The same data gives marketers insights into broader trends in the types of content that buyers find interesting.
Content analysis requires the ABM or predictive system to be aware of the topics of the content being consumed. This is only possible if someone specifically goes to the trouble of tagging the content and capturing the tags. So content analysis is not quite a natural byproduct of the ABM or predictive analytics: it takes some intentional effort. A corollary is that not all ABM and predictive systems can deliver this benefit. So it’s something to specifically ask prospective vendors about if you think you’ll want it.
To put things in a still broader perspective, targeting content with ABM and predictive systems is part of a broader trend of using advanced technology to help marketers create, manage, and optimize content. This is something that vendors like Captora, Persado, and Olapic do in terms of content creation, and Jivox, OneSpot, Triblio, and BloomReach do in terms of personalized content creation. I’ve been looking at a lot of those systems recently although I haven’t written much about them here. New targeting technologies create unprecedented demands for more content, which only new content technologies can meet. So you can expect to hear more about technology-based content creation, whether I write about it or not.
