Let’s face it—ABM has always been resource-intensive. Long cycles, endless back-and-forth with sales, fragmented data, and a constant pressure to prove impact. And now, many of us are asked to do more with the same resources—plus, somehow “use AI.”

At UserGems, ABM has been a core program since our earliest days. Even when we were bootstrapped with five customers, it was one of our top three pipeline drivers. Fast forward to today, our ABM program delivers:

• 10–15% conversion to opportunity across 600 accounts per quarter
• 25–30% of total pipeline
• Up to 40% of closed-won revenue

The key? Pairing a solid strategy with AI—not to replace humans, but to remove the repetitive, low-leverage work so people can focus on what matters.

Here’s how we actually make it work.

ABM Is a Mindset, Not a Tool

Too many companies treat ABM as a tech stack or a campaign in a box. For us, it’s a go-to-market philosophy. Sales and marketing align around a focused list of accounts, and we deploy our limited resources with precision.

We run our ABM program like an assembly line—clear steps, clear owners, and now, AI-enhanced at every stage.

Step 1: Mapping the ABM Assembly Line

We documented our entire ABM process in granular detail. Here’s a simplified version:

1. Start with a master list of 10K+ ICP accounts (updated semi-annually).
2. Each quarter, select 500 priority accounts for ABM.
3. Align with SDRs—they review the list, flag accounts they disagree with, and suggest additions.
4. Build contact lists and enrich data (a massive pain point).
5. Add prospects to outbound sequences.
6. Run campaigns, ads, and events across sales and marketing.

At every stage, we asked our team: “What parts do you hate the most?” Their answers pointed us directly to our biggest inefficiencies.

Step 2: Use AI to Fix the Right Problems

We didn’t start with AI. We started with process. Once we knew where the bottlenecks were, we introduced AI (and automation) where it made a meaningful difference.

Examples:

• Account prioritization used to be subjective and manual. Now we use dynamic scoring based on real buying signals.
• Contact list building used to take hours per SDR per week. Now signals tell us which people matter, not just which accounts.
• Sequencing prospects was a copy-paste job. Now it’s automated.

Step 3: Prioritize Using Signals, Not Gut Feelings

The biggest shift AI enabled was precision targeting. Instead of relying on rep nominations or gut feel, we rank accounts using real buying signals.

We group signals into three types:

1. People-Level Signals

• Past champions
• Persona-match in buying group
• New hires, promotions, referrals
• Website visits (de-anonymized)

2. Account-Level Signals

• Intent (keyword searches)
• Website traffic spikes
• Funding rounds, hiring, M&A
• Competes with your customers

3. CRM Signals (Your Gold Mine)

• Closed-lost opps
• Previous evaluations
• NPS scores, usage data
• Past engagement (emails, calls)

We assign fit scores + signal scores in Salesforce. Our ABM manager then pulls a report each month with the top 500 dynamically ranked accounts. SDRs see exactly why an account was chosen, and who within that account scored highest.

Alignment skyrocketed.

Step 4: Run ABM Like a System

With a precise list in hand, we run consistent 1:1 ads and outbound. A few highlights:

• Logo-personalized ads stop the scroll.
• Top accounts get hyper-personalized landing pages and SDR/AE attention.
• Multi-threading ads target entire buying groups—not just the lead contact.
• Executive dinners and events are tied into the ABM campaign for human touch.

Our SDR sequences include 7+ touches across email, phone (with voicemails!), LinkedIn, and gifting. Every step is tracked and reinforced with automation—Slack alerts for website visits, pre-demo nudges, reminders to follow up, etc.

Step 5: AI + Human = A Winning Pod

AI helps us identify the right accounts and people, and it drafts outreach that reflects the real context. Our reps still personalize it—but they start from a much better place.

The magic is when our reps and our AI both get credited for the win.

Example: When a meeting is booked, we shout out “Taylor & Jimmy” (our SDR + AI agent). Over time, the team believes what we’ve been saying all along: this isn’t man vs. machine. It’s a pod. It’s partnership.

TL;DR: How to Start

1. Map your current ABM process step-by-step. Talk to your team.
2. Identify the bottlenecks—the tasks people hate.
3. Use AI to fix specific jobs-to-be-done, not as a magic bullet.
4. Start small, build trust, and scale when it works.
5. Celebrate wins publicly—credit both human and AI contributions.

If you're “AI curious but overwhelmed,” don’t chase autopilot. Start with one painful part of the job and solve it. Use ChatGPT for simple prompts (like building ICPs from closed-won job titles). Learn by doing.

Final Thought

ABM that works isn’t flashy. It’s consistent, disciplined, and—when done right—quietly compounding in the background.

AI won’t replace your team. But it can remove the work that slows them down, so they can focus on driving real results.

If you want to see how we do it, or want help figuring out where to start, let’s talk.

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UserGems helps marketing and sales teams run AI outbound programs powered by buying signals & your CRM data. ‍

Ready to see how UserGems is the easy button for AI outbound campaigns? Talk to Us

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