B2B marketers are ramping up reliance on AI. But what role does it have to play in ABM?

Using AI to scale ABM. Many B2B brands are doing it right now. Is that a good thing?

For now, the jury’s out. It remains a live experiment in outsourcing craft and thinking to a technology with huge potential, though few people really understand it.

During which parts of the ABM process can AI be legitimately helpful? Are there areas that should be strictly off limits? And what practical steps can B2B marketers take to get the most out of it?

To address those questions and more, we sat down with Suzi Bentley Tanner and Anna Harris from Havas.

Big picture, what’s your view on how B2B brands are using AI within ABM?

Anna
Above all, ABM is about getting a truly in-depth understanding of the audiences you’re targeting.

What’s the overall ICP of the company, what are the account segments within that, what keeps your audience up at night, what are the biggest blockers your brand can solve for?

If you don’t really understand who you’re targeting, if you start the process by feeding AI a series of generic prompts, you’ll just end up with generic output — the exact opposite of what successful ABM looks like.

Suzi
I think that’s a real danger with AI. Yes, it can accelerate that early groundwork, but the risk is you just scale mediocrity. And if you’re essentially asking it to do the thinking for you, you’ll never have that deep understanding of the accounts you’re looking to reach.

So where does AI have a role to play in the research and planning phase?

Anna
One area we’ve found it really helpful in is reviewing poll survey data, specifically for comparing and contrasting responses across audience groups. It’s also great at summarizing findings from qualitative research. On average, we’re saving around two days of manual analysis by using Havas’ proprietary AI for tasks like these.

We can also code ABM variables into AI, so content can be updated to meet the needs of the segment.

Suzi
Agree. AI can help pull together and synthesize early research, offering initial insights. But what it can’t do is say, ‘What does this insight actually mean? How does this relate to what we’re trying to achieve?’ You still need a human to make sense of it and determine how to apply it to best effect.

Essentially, AI is great at aggregating and interpreting data from different sources, but it shouldn’t be responsible for deciding on strategy, the creative approach, or how to engage different accounts.

Anna
I’d say that’s where the value of a strategist comes in. The ability to hypothesize, test ideas, scrutinize findings against past experiences — these are important qualities that can’t be automated.

So we’ve discussed the areas that AI falls short in ABM. But where can it add value?

Suzi
Used properly, it can support rapid, atomized content production. Once you’ve got your master creative concept and key assets in place, AI can help create variations on messaging to accelerate and scale the production process. With one of our clients, for example, we’ve reduced time to market from several weeks to just a few days.

Anna
As another example, we’ve used AI for account scoring, prioritization, and segmentation. Once you’ve built a target account list, AI can conduct pattern matching across firmographic data and organize accounts into segments based on shared characteristics or behaviors. And it can then group them into different ABM tiers.

What should organizations do if they’re looking to improve their ABM processes? Can AI be a useful tool?

Suzi
I think you need to review the process first without thinking about AI. We try to look at the whole value chain, consider what is and isn’t working well, and identify which skills or capabilities need improvement.

There may be areas where it makes sense to think about AI. But first, you need to fix the process. And that’s something that requires human expertise.

Anna
I agree that AI is a secondary element. As an organization, you need to have the right structures in place first. Focus on the strategic or cultural change management steps you need to take. Once those foundations are in place, AI can help accelerate the processes you’ve decided are right.

Any final recommendations for marketers around using AI within ABM?

Anna
Make sure you personally understand the recommendations AI is making. Interrogate them, understand them, and then make sure you can confidently articulate them.

I’d also recommend using AI to flag inconsistencies in your work. Ask it to pick holes and challenge it from different perspectives. For example, when you’re running messaging across multiple segments, AI can flag inconsistencies, such as a value prop that has drifted from the agreed positioning or messaging that hasn’t been updated to reflect a new product launch.

Suzi
You can’t fake a relationship. And asking AI to help create an authentic relationship is destined to fail, particularly as we all get better at spotting AI content. In the end, ABM has to make your audience believe you get them. Using AI in the wrong ways can expose the fact you really don’t.

Bring your next ABM campaign to life

At Havas, we’re continually experimenting with AI and the value it can bring to ABM. But it’s clear that before putting AI to work, the strategic foundations have to be in place, and that still relies on human expertise and insight.

To find out how we can apply that expertise and insight to your ABM efforts, get in touch.