Account-Based Marketing (ABM) is a broad category. It’s one that everyone defines differently, from those who have done it for years (without the ABM tech) to those who are still trying to wrap their heads around the strategy and accompanying technology.
Now, there is more and more talk redefining what account-based marketing means. For example, is it ABM? Or is it Account-Based Experience (ABX)? Are they the same thing? It seems we've reached the next stage of technological advancement in this industry, or have we? The trouble is, most companies are still back in the traditional ABM world.
Randi Barshack is the CMO of RollWorks, an ABM platform provider. As CMO of RollWorks, this is the first time she finds herself marketing to marketers. For her, it's been an interesting journey. Barshack doesn't buy into all the terms and hype around ABM. She thinks marketers just need to get to what they need to do and argues that the fundamental aspects of marketing and sales and the common sense logic of what companies are trying to do in many ways haven't changed:
I still have a universe of opportunities, whether that's big or small, identified, not identified. There's some sort of something I'm cultivating and trying to translate that into value for my company. And value could be the sale value, could be the lifetime value, or that value could be the combination. It could be the subscription value, it could even be getting into an opportunity stage, but I'm trying to take something that is not very defined and create value.
Good marketers haven't really changed, she suggests. There's more data than ever before, but it’s still important to make sense of that data in a meaningful way. What has changed is the need for marketers to do that at scale. That's where Artificial Intelligence (AI) and Machine Learning (ML) come into play.
AI in ABM
According to Barshack:
The biggest misconception about AI is that it's about the hard stuff. And I actually think the potential of AI is about the easier things at scale.
While it takes time to train a computer, but once you do it, it can work at scale, providing marketers with something very important - more time. But AI is often confusing for marketers because they think they need to understand the inner workings of the algorithms and how the tech works. In fact, says Barshack, marketers shouldn't care.
A marketer has a goal or a challenge and whether it's the world's greatest algorithm or the proverbial '26 elves at the North Pole' helping you solve it shouldn't matter as long as you get the results for the investment, she says:
There are many, many ways where AI can be well deployed and get you there better faster and more efficiently. And I think it's great if you can understand that because you can ask more probing questions. But I think it's more important that you're not buying something because it says AI and then force-fitting it into a problem that you don't have or something that doesn't make sense to your business. I think it's much more important for marketers to be attuned to what they're trying to do and then understand the tools and technologies out there, which is, by the way, so overwhelming.
AI in ABM can tell marketers which of all the accounts out there are the ones most likely to bring in business, and, at any given time, what are the different variables impacted. Then, this information can be used to determine next steps and personalize the experience with that account and its contacts, from sending a gift to having an SDR reach out to checking them out on Linkedin or Facebook. (Mind you, she also notes that you could get the same result talking to someone at a trade show. )
The point Barshack is making is that the ability to do things at scale shouldn't eclipse common sense. As marketers, it’s easy to get wrapped up in cool new technology, but it shouldn't be the first thing you think about. The first step, said Barshack, is understanding your business. In other words:
- What are you driving?
- What are gaps in what you need to do?
- Where are there opportunities to gain efficiencies?
With all the pressure, often from management, to implement AI solutions, marketers tend just to get something in place and check the box. However, once you know what problems you are trying to solve, you can shop for AI solutions to help you.
AI gives marketers the power to ask many questions and get the answers much faster than doing the same thing manually. It can help put marketing and sales on the same page regarding the list of accounts to pursue and how to do that.
Does intent work?
I have my misgivings about the value of intent, a fundamental aspect of ABM. For example, how well can an ABM solution, or even a marketing automation solution to some degree, accurately predict intent? Intent, says Barshack, can be a powerful tool if looked at it on multiple dimensions:
- Is the account a fit? In my ICP? On my list of target accounts (a subset of my ICP)?
- How ready are these accounts, and what are the signals of readiness that I may or may not know?
Readiness signals can be explicit, like visiting a specific page on the website, downloading a content asset, or attending an event. If multiple people from the same account do similar things, it's likely not a coincidence. Also, getting signals from third-party sources is extremely valuable, Barshack suggests, because it's someone you haven't engaged with yet, and it might be a good time to reach out.
There is a lot of discussion around what a strong intent signal is, and more often than not, weak signals get misrepresented. Barshack acknowledges this, but is confident marketers can work things out:
I think the market will probably sort itself out in terms of learning what a good intent signal is versus one that's weaker and, and more, you know, more of a stretch"
Three ways AI/ML can impact ABM strategies
Barshack punts three areas where AI and machine learning can impact account-based marketing strategies:
AI can tell you where there are patterns without you explicitly laying out what those patterns are. You could find those patterns manually, but it would take forever to go through various variables and parameters to find any number of permutations, especially with the number of data marketers now have. Even for traditional ABM strategies, where marketing gets its top accounts from Sales, those accounts can be taken, scored using the algorithm and other accounts found that should be on your radar. Also, AI is a continuous loop - as more data is fed in, the algorithm is learning and course-correcting.
Barshack pitches that the strength of RollWorks lies in its sophisticated algorithms that help optimize reach. For example, using display advertising, which is pretty much table stakes in ABM, you can get precision and scale that can go very deep into an account.
There are multiple ways to leverage display advertising, including:
- Reaching accounts that are showing intent but haven't expressed interest in your solution
- Supporting SDR outreach
- Reaching existing customers up for renewal.
The fact that I can take my most scalable channel, which is display ads, and I can fine-tune it down to a buying committee at a specific account and not waste a single impression, outside of the accounts that matter. And I can even right size the impressions to the accounts that I want to cover. To me, that was like that was the biggest 'aha!' in terms of falling in love with ABM.
The buyer's journey is not linear; it's multi-faceted - despite how many marketers define it. AI can help marketers understand where an account is in its journey, its trajectory, and what's getting them there. Factor in velocity (the speed at which things are changing for that account), and you have the opportunity to reach accounts in a highly personalized way.
ABM solution providers always tend to be two steps ahead of what many companies are trying to, and that’s fine; it makes sense to be forward-thinking and work with customers who can help them innovate and build better solutions. But it still feels like we are working against the hype around ABM and ABX, with some thinking ABM is the answer to everything in B2B marketing.
It is a critical strategy that companies can’t operate as a side project or in a silo. But I appreciate the realism Barshack adds to the conversion. You shouldn’t do ABM just to say you do ABM. You shouldn’t leverage AI just to check a box. There is some serious thinking and strategizing behind every tactic, activity, and technology used in marketing. It’s a puzzle that is unique for every company, and the smartest marketers understand that and build great marketing programs keeping it all in mind.