An Account Based Marketing primer for enterprise IT

In the age old attempt to “learn the business” there is a rather old marketing strategy that has been amplified recently by new ways of unearthing client insight from corporate databases and CRMs. I think it’s worthwhile for IT to understand this concept if for no other reason than to be proactive about it in discussions with the sometimes-prickly sales and marketing types.

Account Based Marketing (ABM) is actually quite simple. The strategy moves marketing from the general to the specific. Rather than fishing with a net, ABM uses a hook baited to reel in business from a pre-defined list of target accounts. This may rightfully beg the question, “What’s so revolutionary about that ?”  The answer is that at first blush this should be a natural element of the selling process — salespersons targeting the accounts that are most likely to invest larger sums of money into your goods or services.

In the golden age of rolodexes and stacks of business cards in rubber bands, that would have been very true. But in an age of digital interaction, the concept of an “account” takes on a totally different complexion than when Willy Loman ran sales.

So how can enterprise IT executives incorporate ABM into their data and analytics strategies, before sales and marketing ask?

ABM and analytics

For those who’ve read my work in the past, you won’t be surprised that my first question would be related to the content strategy that sales and marketing will use for the target account list. While in the old world ABM was simply looking at files of client titles and contact information at the same buying site, ongoing experiences tell me that some very large companies still operate in this 19th century ABM model.

But then content marketing and ABM converged and a whole new data set emerged to define the propensity for accounts to buy. Regardless of whether the database is owned organizationally by marketing or IT, technology strategists must still understand how CRMs and Content Management Systems (CMSs) are being populated and, more importantly, how they talk with each other.

The ABM model requires a much deeper look into customer sites in addition to the individuals who populate them. More important, there is a need to derive insights on the possible relationship between persons in that site.

So let’s put it in the context of the IT buyers reading this piece.

Collaborative buying influences

I’m tech firm InteropCo selling an interoperability system to XYZ Global Enterprises. I want to do everything I can to generate data that would reflect any possible collaborative buying influences that might be working together on that initiative at a particular XYZ company site. In addition, I would like to smoke out those influences at headquarters who might be buying enterprise-wide for all XYX Global sites .

To do this, the marketers in your enterprise would be driving very specific content to this company to unearth influencers at the site and enterprise level. As clusters of like-minded IT professionals self-identify by engaging with or registering for this targeted content, there is a gestalt effect where the collaborative buying data is worth more than the sum of its parts.

For the data scientist, the ability to confirm some formal behavioral/buying relationship between the parties who have engaged results in an incredibly powerful ABM insight.

This collaborative buying data process can be established for any considered purchase, whether a sophisticated IoT deployment or the determination of a new corporate benefits supplier for a Fortune 500 company.

Tells us how you’ve worked with your sales and marketing counterparts on deep data insights for Account Based Marketing programs.


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