The Early ABM Process Flaw

April 22, 2016 Damon Waldron

Attending Demandbase’s B2B Summit, it’s easy to get excited by the promise of ABM. Funnels are flipped, targeting is laser-focused and content is personalized. In all that excitement, I think there’s a danger some of us are missing something. Conventional ABM wisdom starts with intelligently establishing the right target account list. Great. Then identifying all the right people at those accounts. Again, makes sense. Many of us then map out our strategy with all these cool things we can do now: IP-targeting target companies, personalized company and even persona-specific emails, direct mail, etc. We turn it all on and it’s off to the races.

Ok let’s pause right there. In the non-ABM world, we savvy demand gen pros would carefully understand the exact performance impact of each and every channel and campaign (hopefully using multi-touch attribution): MQLs generated, cost per MQL, pipeline created, pipe to spend, revenue created, lead to opportunity conversion, velocity. Then we would take this data to optimize our efforts and plan our path forward. Why has this core data-driven concept been lost? “But Damon, this is ABM! It’s all new! The old rules are gone.” Uh, no they’re not. Hate to break it to you but you can and should be data-driven from the outset of your ABM initiative.

It reminds me a bit of my own shift from using email service providers like Strongview (who can do some really sophisticated things on the deliverability front) to marketing automation. I found myself spending way less time caring about deliverability and way more on all the cool things I could do with Marketo. Unfortunately bounce rates still matter in a marketing automation-driven B2B world and can have a big impact on your marketing performance. Anyway that’s a subject for another post. Back to ABM.

I’d propose when embarking on an ABM initiative, after identifying the right target companies, look back and understand how your channels and campaigns performed against those target accounts. Which tactics were successful? Which campaigns resonate? Now I know, you’re going to be trying some “new” tactics like IP-targeted display. They’re new but you can ground your performance forecasts for these in real historical data (knowing that they will behave a bit differently given the tighter targeting). At least you have something to go on vs. just flying blind and hoping all these new shiny toys work. Don’t get me wrong, I think these tactics can be great. Just apply the same analytical rigor you normally would when rolling them out.

The Early ABM Process Flaw

I’d also strongly urge you to do this on the account-specific level too. Our Engagement Fingerprint on this target account shows that they just love our emails. Perhaps we should double-down on the tactic?

The Early ABM Process Flaw

So yes, ABM is real. People are having great success with the strategy and we believe in it for our own operation. Just make sure you keep your data-driven hat on as you dive in.

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