Struggling with low conversion rates in your ABM campaigns? You're not alone.
The challenge for most marketers isn’t knowing who to target—it’s knowing where to start, and how to keep momentum once you do.
You’ve got cross-functional buy-in, a list of dream accounts, and a ton of strategic possibilities—industries, segments, personas, pain points. But too often, that early energy fades. Marketing wants to narrow the focus. Sales wants to go wide. The effort stalls before it ever really begins.
That’s when things break down:
In this blog, I’ll walk through how combining both fit and engagement-based lead-scoring models can dramatically improve how you prioritize and convert prospects.
Before we dive into lead scoring specifics, let’s take a quick bird’s eye view of our strategy.
To run an effective ABM motion, marketing and sales need to stay tightly aligned—not just on who to target, but on when and why a lead is ready to move forward.
That’s where the lifecycle funnel comes in.
It provides a shared language for buyer journey status and lead quality with a clear framework for moving prospects from initial interest to real opportunity.
Though each lifecycle stage should be customized based on the unique buyer’s journey of the organization, general definitions for standard lifecycle stages usually look something like this:
While the lifecycle stage allows sales and marketing to measure where customers are in their buying process, mapping the customer journey shares insight into how these teams plan to move prospects through the funnel to closed won business - together.
Here’s how I’ve built out the first half of this customer journey for a few of my recent clients:
The HubSpot Fit Score is a tool used to evaluate how closely a contact aligns with your Ideal Customer Profile (ICP). It helps prioritize leads before any engagement begins—ensuring marketing and sales only spend time on accounts with a high likelihood of converting.
Rather than relying on guesswork, the Fit Score uses a combination of firmographic and demographic signals—like industry, company size, and job title—to assign each contact a numerical score. The higher the score, the stronger the fit.
In one client implementation, a structured Fit Score model was built to reflect the attributes most relevant to their buying process and audience. The model included:
Each of these inputs was weighted, with a maximum score of 100 points. A threshold of 75+ was set to determine whether a lead was qualified to move forward. If a contact fell below the threshold, they were suppressed or marked unqualified, ensuring the database stayed focused and clean.
In the first month of the campaign, about two-thirds of all inbound leads were flagged as a strong fit—thanks to Fit scoring layered on top of our initial filters.
That stat alone reshaped how we viewed lead quality. Even with solid segmentation, static filters weren’t enough. Fit scoring added a crucial second check that helped us prioritize faster, with more confidence.
The result? A cleaner, more conversion-ready pipeline from day one—built on automation, not manual guesswork.
While the Fit Score determines who should be nurtured, the Engagement Score helps identify when they’re ready for sales. In HubSpot, the Engagement Score tracks a lead’s interaction with marketing efforts—capturing behavioral signals that indicate interest, urgency, and buying intent.
The score is built around key actions that reflect increasing levels of interest. A typical model might assign:
Once a lead’s Engagement Score crosses a predefined threshold, they’re considered highly engaged and ready to be handed off to Sales.
In one client setup, the Engagement Score was designed to reflect both frequency and depth of interaction. For example:
This ensured Sales only spent time on leads who were not just a good fit on paper—but also actively showing signs of intent.
Conversion rates between lifecycle stages aren't just performance metrics; they're also signals. They reveal what's working, where leads are falling off, and where to focus your efforts to improve performance.
Here's what we uncovered at each stage - and the actions we took to improve them.
Lead → MQL
MQL → SQL
SQL → Opportunity
Analyzing conversion rates by lifecycle stage enables focused optimization. Each transition reveals what’s resonating, what’s missing, and where you have the opportunity to drive stronger conversions. Here’s how we used those insights:
Using Fit scores alongside static filters gave us a more nuanced view of lead quality—and with automation, we were able to scale those decisions across the entire funnel.
Once we had a high-fit, high-intent pipeline, the next challenge was turning that into actual conversations—without overwhelming the sales team or losing momentum.
Our solution? Automated sequencing through HubSpot. It gave us a scalable, repeatable way to move SQLs into outreach the moment they were ready—without relying on manual follow-ups or scattered workflows.
Using dynamic sequence allows you to:
This hybrid approach keeps your team efficient while ensuring no hot lead goes cold. By blending automation with timely sales touchpoints, you can seamlessly move qualified leads into meaningful sales conversations—scaling outreach without sacrificing quality.
I’m always looking for ways to unlock new levels of performance through smarter systems and sharper insights. This campaign was no different. By layering HubSpot’s lead scoring system with automation, we found a repeatable way to prioritize the right leads at the right time—without burning out our team.
When the wrong leads move through your funnel:
And all of that leads to missed revenue opportunities.
ABM often feels daunting—many assume it demands a complex tech stack and endless manual effort. But with HubSpot’s built-in automation, lead scoring, and workflows, it doesn’t have to be.
And the best part? You can start seeing results faster than you might think.