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How to Scale ABM With AI

How to Scale ABM With AI

ABM has always been a laborious process, but if you harness the potential of AI tools you can scale up your strategy and reach more prospects than ever before.

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Account-based marketing has many challenges, but perhaps the biggest is just how resource-intensive it is. If you’re focused on 1:1 or 1:few ABM campaigns, you’ll be very aware of how much time it takes to personalize everything.

But there is a way to scale your ABM efforts without ditching other priorities or hiring an army of marketers, and that’s by embracing AI.

Award-winning ABM agency Hut 3 has been using these tools to accelerate its campaigns for various clients, and with impressive results. That’s why we invited Director Andy Johnson to join us for a webinar discussing how you can turn up the ABM dial with or without AI. Backed by real-world case studies and practical tech stack recommendations, this session offered valuable lessons for marketers looking to scale ABM programs efficiently, personalize at speed, and secure early buy-in from sales.

Why ABM Still Matters

Today’s buying journey is longer, more complex, and far more crowded with stakeholders.

“We see between seven and 13 decision makers in the average B2B buying group,” Andy explained. And at the same time, buyers are often 70% through the journey before contacting a sales rep, and 80% have already formed preferences.

“Only 3–5% of your potential customers are actively looking to make a purchase at any moment in time,” Andy noted. “Marketing’s job is to make sure we’re always showing up when they do decide to buy.”

That’s where ABM comes in: you can personalize your assets for each of the decision makers within a buying group to maximize your impact and engage multiple stakeholders at the same time. Plus, the always-on nature of ABM means your brand remains visible throughout the prospect’s journey and you can work on building trust, even if they’re months away from looking for solutions.

ABM in Action: Real Campaign Examples

During the webinar, Andy shared some examples from agency Hut 3 that achieved impressive results with ABM:

  • Immuta’s 1:1 ABM campaign generated ÂŁ800k in pipeline with relatively low budget.
  • Atos’s account-based demand campaign achieved ÂŁ255M in pipeline growth across global regions, with ÂŁ49M closed during the campaign period.
  • UiPath’s 1:1 ABM campaign drove a 137% increase in annual recurring revenue across 34 accounts.

“These numbers prove that ABM does pay off—when it’s done correctly,” Johnson said.

Scaling ABM with AI: Faster, Smarter, More Personalized

The secret to Hut 3’s ABM success is embracing AI to scale campaigns. But they use more than just a LLM chatbot: they’ve embraced agentic AI and built their own suite of tools called Enigma.

It’s made up of four AI-powered engines:

  1. Enigma Insights rapidly gathers intelligence on accounts and clusters.
  2. Remix Engine converts content into multiple sector-specific versions.
  3. Personalization Engine tailors messaging at scale for target accounts.
  4. Enigma Stories turns fragmented data into compelling narratives.

“The remix engine is especially powerful,” Andy said. “It lets us take a thought leadership asset and remix it into multiple campaigns — say for industries like life sciences, food and beverage, and automotive — within weeks instead of months.”

But Andy’s advice is clear: AI doesn’t replace human input. “The human part of ABM is how we connect with sales, customer experience, and make sure personalized contacts are meaningful,” he stressed.

Your Essential AI Tech Stack

Many marketers assume a full-scale ABM platform is required to get meaningful results. But that’s not the case.

“You don’t have to start your ABM with an all-singing, all-dancing tech stack,” Andy reassured us. “You can piece that together.”

Hut 3’s Recommendations

Andy shared that the baseline tech stack you’d need to scale ABM includes:

  • LinkedIn to load target accounts and engage with tailored content.
  • Astrad for programmatic advertising to surface in-market accounts.
  • Lead Forensics to identify which accounts hit your landing pages and what they viewed.
  • Cognism to enrich data for GDPR-compliant contact targeting.
  • CRM to tie all engagement data back to existing pipelines.

“Lead Forensics, especially when paired with Cognism, has been a game-changer for us,” Andy revealed. “It allows us to see what content accounts are engaging with and match that to sales-ready data almost instantly.”

Launch Wide, Then Go Deep

A good way to launch your ABM campaigns is to cast your net wide, then focus on the prospects that bite.

That’s how Hut 3 approaches a lot of their campaigns, but Andy shared a specific example of cybersecurity company TXOne. Their strategy was:

  • Start with an always-on programmatic campaign to engage a wide set of 1,000 target accounts.
  • Use insights from that to trigger 1:few sector-specific campaigns (e.g., pharma, food and beverage).
  • Spot the highly engaged accounts and prioritize them with 1:1 strategic programs.

This helped reduce costs and focus effort.

“We don’t expend energy on 1:1 unless we know the account is already engaging,” Johnson explained. “It’s more efficient and reduces media spend duplication.”

You can use AI tools to help you spot those accounts that give off buying signals and analyze firmographic and technographic details to highlight the prospects that are your highest-fit accounts.

And when it comes to personalizing your assets, tools like ChatGPT (and its new Agent Mode) can make those content edits for you – at an impressive scale.

Data Isn’t Just the Foundation; It’s the Proof

Johnson emphasized the importance of ongoing data storytelling to secure internal buy-in.

“The data doesn’t just inform the campaign; it proves the value. Especially early on, before revenue comes in, those insights are what show stakeholders this is working.”

Tools like Google Looker Studio or similar dashboards help bring together disparate data (LinkedIn, Astrad, CRM, etc.) to provide a single view of what’s working, and spotlight where to optimize.

Don’t overlook the potential of AI tools to help with data analysis, too. It can unify fragmented data sources to give you a more holistic view of account engagement or surface hidden insights by spotting patterns you may not.

You can also use AI to help with your data presentation and storytelling, as it can produce reports that are easy to digest and adapted according to the audience.

Remember: ABM Success Is a Team Sport

“There’s huge promise in ABM,” Johnson concluded. “But you need your content, your tech stack, your data, and your sales alignment to all come together. Once that happens, ABM becomes a machine that can consistently generate qualified pipeline.”

The key to getting there is to start simple, prove value quickly, and build from there. But make sure you’re powered by data, driven by insight, and amplified by AI.

Get Advanced ABM Insights

Visitor identification software like Lead Forensics helps you see which accounts are engaging with your ABM campaigns, so you know who to prioritize for 1:1 personalization.  Book a demo to see how our platform can help you solve your ABM challenges.

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