Top 10 ABM Mistakes


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I may not be a market analyst, but from what I see working with our agency’s B2B clients, it seems to me that, in the language of technology adoption lifecycles, Account-Based Marketing (ABM) stands at that pivotal junction – what Geoffrey Moore calls the “chasm” – between early adopters and early majority.

The hype around ABM has subsided. That mad rush to jump on the ABM bandwagon (for Fear of Missing Out) has given away to more practical considerations. Is ABM a fit for our company, our product, and our audience? How can ABM best coexist with a more traditional funnel-based demand generation model? What are the key elements that make for a successful ABM initiative? When so many technology vendors claim to be an “ABM solution,” what are the smartest investments?

ABM mistakesThere was a time, not so long ago, when Marketing Automation went through a similar transition. In the giddy, early days when solutions like Marketo first arrived on the scene, the reigning view was that the technology was all a company needed to solve their lead management and email marketing woes. But then reality kicked in, and companies realized (and are still realizing, to this day) that technology alone, without adequate resources, people, planning, strategy, content, and creative, won’t solve anything.

So it is, I would argue, with ABM. Many early adopters are showing real success, but a sizable number have seen their lofty ambitions for ABM fall short. Why is that? In talking to clients about how to better achieve ABM success, here are what we see as the most common pitfalls, misassumptions, and ABM mistakes:

1. Measuring the wrong thing.

ABM is radically different from inbound, funnel-based demand gen in many ways, and it starts with how to measure success. Not only is ABM success not measured by clicks, conversions, and leads, but the KPIs may vary according to campaign stage. For example, in the very early stages of an ABM campaign, success is best measured by Account-Based Awareness and Account Engagement. In later stages, the measuring stick is more likely to be Sales Qualified Accounts, Meetings, or Pipeline.

2. Thinking that ABM is a 60-day initiative.

One of the most common misperceptions about ABM is that it’s a quick fix. ABM is typically best-suited for companies selling complex solutions to buying committees at large enterprises. These are not impulse purchases. ABM can be a highly effective way to navigate a long, complex sales cycle, but the marketer who thinks that an ABM program is going to convert cold names to pipeline opportunities in a few short weeks is destined for disappointment. As I wrote in this earlier post, ABM is a strategy, not a campaign.

3. Lack of personalization.

One of the cornerstones of ABM is that it is primarily, if not exclusively, a “one-to-one” approach vs. “one-to-many.” Implicit in that one-to-one principle is the need to personalize messaging, content and creative in order to maximize relevance for, and engagement from, a particular account, buying group, or individual decision-maker. If you’re simply recycling the same broad messages and demand gen content for your ABM initiative, it’s unlikely to generate the results you’re looking for.

4. Failing to get sales sufficiently involved (planning, engagement)

The days of simply throwing unqualified leads “over the fence” to sales are long behind us, and marketing’s role in the sales cycle is greater than ever. Nowhere is that more true than with ABM. ABM is not solely a marketing initiative, and moreover, without the buy-in, advice, and active involvement of sales and sales management, starting early in the planning process, the performance of any ABM initiative is greatly compromised.

5. Shortchanging message, offer and creative.

B2B marketing is more technology-driven than ever, but technology without the right message, offer, and creative simply empowers you to – as industry observers have put it, “generate more cr*p, more quickly.” Like Marketing Automation before it, ABM is no exception. ABM technologies lend efficiency, accountability, and scalability to the process. But they are only part of the total investment.

6. Not having the right technology.

It may seem contrary, therefore, to argue that – message, offer, and creative aside – technology is still an essential part of the ABM puzzle. Can you execute ABM effectively without technology? Certainly. (Just as you can nurture leads without marketing automation.) But the lack of appropriate technology, and forcing legacy systems to do things they aren’t built for, can jeopardize success.

7. Attempting ABM on the cheap.

As I discussed in this earlier post, attempting to execute on ABM without careful planning, audience definition, sales enablement, executive buy-in, personalized content, and dedicated technology is a recipe for disappointment. Like it or not, ABM is an investment. Any shortcuts in planning, content and other processes and resources are likely to have a proportionate effect on results.

8. Not knowing your audience.

Creating personalized messaging and content is one thing. But personalization relies first on understanding your audience, defining an Ideal Customer Profile (ICP), defining key personas within the buying committees at your target accounts, and doing the research it takes to develop and document the pain points and value propositions most likely to resonate with those specific individuals. Relevance relies first on talking to the right person, and then knowing what makes that person tick.

9. Ignoring the buying cycle.

I’ve made the case elsewhere that part of the appeal of ABM can be attributed to 1) an inability of many companies to effectively nurture leads through the funnel, and 2) the impatience of sales executives as that process runs its course. Even the most successful ABM strategy does not eliminate the buying cycle. ABM can help generate awareness and engagement and even meetings, and bring your company to the table so to speak, but it does not inherently abbreviate the sales cycle. Many an ABM initiative fails not from lack of success per se, but misaligned expectations.

10. Approaching account selection like a wish list

ABM journeys often begin with asking sales for a list of their target accounts. And therein lies the first mistake. Account selection is not the same as compiling a wish list. Selecting a list of target accounts should revolve around finding those organizations that are the best fit for your solution, not simply those companies that sales wants most to penetrate. Look at your own customer data. Are there industries that have a higher renewal rate? Or leverage technologies like Predictive Analytics and Intent Data. They ignore assumptions and sales bias, and help marketers find the “high propensity” accounts that genuinely, and scientifically, are most likely to buy your solution.

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Republished with author's permission from original post.

Howard Sewell
Howard has worked in marketing for 25+ years, and is president of Spear Marketing Group, a full-service B2B marketing agency. Howard is a frequent speaker and contributor to marketing publications on topics that include demand generation, digital marketing, ABM, and marketing technology.


  1. Hi Howard: 1 – 8 is a solid list. The risks you’ve identified rank high in my experience, as well. On #9, the perceived impatience of sales executives is primarily an artifact of the pressure that management exerts on the sales team to produce revenue. This pressure often puts customers at risk from the ethical compromises that salespeople might feel are necessary to make goal, achieve a bonus, and ultimately, to preserve their jobs. It’s important to call out the frequent proximate cause, which is more about management’s impatience, and less about the rep’s.

    Regarding #10, a ‘wish list’ from the rep might not be all bad. In my experience, predictive analytics don’t remove, but rather embed bias and assumptions into the output. Bias infects the results because the opportunities a sales organization choose to pursue are fully influenced by what the sales team has chosen to work on in the past. Excellent opportunities that were overlooked or omitted in past sales activities aren’t included in the data set.

    Assumptions are connected to bias: “past is prologue.” Of course, this is not necessarily true. Moving forward, selling conditions can be very different, so companies should not assume that conditions are or will be the same, and that must be considered for determining which accounts to pursue.

    This is not to suggest that predictive analytics doesn’t have value for making recommendations. But companies should not be lulled into thinking the alleged science of predictive analytics offers an indisputably lower-risk path forward. Sometimes – many times, maybe – the vantage point of the territory rep of the best nascent opportunities provides the most compelling choices for target accounts.


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