16 “Expert” ABM Tips that Miss the Mark

by | Aug 10, 2017 | ABM, Deep Learning, How To, News

Don’t call us haters: We’re obviously advocates of account-based marketing (ABM), and we’re happy to cheer on any B2B marketer who’s trying to advance the state of that game.

Unfortunately, there’s also a huuuuuuge amount of static arising around ABM, just as there does with nearly any new area of innovation that suddenly catches fire with a general audience. Punditry and lists of must-do! ideas rise like swarms of locusts, eager to devour a reader’s attention. The sheer volume and variety of it heightens the confusion and may fracture any clear vision of how to implement ABM.

One example? This recent HuffPost piece that baited us in with the very alluring promise about ABM Content: 16 Tips for Creating Personalized Content at Scale. If that’s not a sexy come-on for a digital marketer, what is?

The experts quoted sharing their pearls of wisdom all hail from the trenches of marketing automation and ABM services. But their advice somehow manages to range all over the map without covering any new ground. Some snippets?

Prioritize and segment your accounts based on some common criteria that cuts across them. Once you’ve done that, you can craft messaging for the segment and do some small A/B testing on the sample.

Personalizing content helps sales teams to better differentiate their offerings versus their competitors, which is why it’s so important for marketing teams to provide it. But it’s a huge headcount challenge—from content creators to designers—unless you have a solution that can automate that content.

You need to identify your personas, their pain and goals, and from there you can start crafting messaging that speaks to their pain points.

You need to have a content map. You need to examine all the different personas and stages of the buyer’s journey, then determine how certain types of content can help each persona in each stage.

One tip to rule them all

All their well-meaning wisdom doesn’t offer up anything particularly new. Moreover, none of it tracks back to the real core challenge that marketers need to solve first and foremost if they’re going to make ABM work at scale:

How do you identify your actual prospects, the members of the Buying Groups and Demand Centers you have to penetrate at targeted accounts?

Our #1 tip, of course, is to use Deep Learning to identify those people, understand their roles and personalize your messaging and engagement channels for maximum effectiveness.

That’ll relieve you of the gruntwork involved in many of the “expert” recommendations, now that many of those tasks are now being done automatically by an A.I. Better still, such a platform (like ours) integrates seamlessly with marketing automation products and other systems.

The benefits? There are two biggies we can think of, right off the bat:

  1. You’ll revolutionize your ABM efforts, since you can now identify higher-quality leads with far greater speed, but with practically no elbow grease required on your end. Engagement and conversion increases and media spends are optimized or even reduced, since you’re able to target your ABM with much greater accuracy.
  2. You’ll never feel the need to look at articles like the one from HuffPost ever again.

You’ll thank us for it.  Believe me.