The Funnel Fix: Engineering a 50% Increase in MQL-to-SQL Conversion

The Challenge: A Funnel Full of Leaks

When I joined LifeFitness as Global Digital Marketing Operations Manager, one of the first red flags I noticed was that marketing was generating a decent volume of leads but sales wasn’t seeing them. On the surface, the numbers looked fine. Campaigns were active, the MQL count was steady, and we had the tools in place - Pardot and Salesforce.

But something wasn’t adding up. Pipeline growth was sluggish. Conversion from MQL to SQL was consistently low. Sales teams were flagging “lead quality” issues, and some regions were reporting that they weren’t getting leads at all.

On digging deeper, it became clear that we had a fundamental disconnect between what marketing was producing and what sales was receiving.

We didn’t have a funnel problem - we had a funnel failure.

What Was Actually Broken

The issue wasn’t one thing it was a series of small breaks across the funnel that, together, created serious revenue leakage. Here’s what I uncovered:

• Leads weren’t being routed properly. In many cases, they weren’t being routed at all. In others, they were going to inactive or incorrect reps.

• No consistent MQL criteria. Different teams had different definitions of a “qualified lead,” and those definitions often weren’t agreed upon with sales.

• Lead data was incomplete or inconsistent. Some records were missing critical info like job titles or company names, which made scoring unreliable and routing impossible.

• No follow-up SLAs. There was no formal agreement on how quickly leads should be picked up by sales or what constituted a “sales-ready” lead.

• Lack of visibility. Marketing couldn’t track what happened to leads after handoff. Sales couldn’t see how or why a lead had been generated. We were operating in silos.

  
  

These gaps weren’t just operational they were cultural. Marketing and sales were pointing fingers. Campaigns were being questioned. And revenue was being left on the table.

My Mandate: Rebuild the System from the Inside Out

The goal wasn’t to run more campaigns or drive more leads. It was to fix the system and to create a marketing operations engine that was connected, predictable, and accountable.

This required a complete teardown and rebuild of the lead management process. Here's how I tackled it:

Step 1: Map Everything. Then Identify the Gaps

I started with a funnel audit across our entire lead lifecycle, from first touch to SQL. This wasn’t just a system check - it involved working directly with regional marketers, sales managers, and operations leads.

We mapped out:

• Lead source by channel and region

• MQL definition and scoring logic in Pardot

• Handoff points between marketing and sales

• Assignment rules in Salesforce

• Response times by sales teams

From that, I built a heatmap showing where leads were dropping. The most common points were:

• Disqualified too early due to poor data

• Stuck in Pardot with no sync to Salesforce

• Assigned to the wrong person or left unassigned

• Picked up too late - sometimes not at all

Step 2: Redefine MQLs, Together

One of the biggest wins came from aligning on a shared definition of an MQL. This wasn’t a marketing decision - it was a joint effort with sales. We built the new definition based on:

• Fit (firmographics, job title, industry)

• Engagement (downloads, site visits, webinar attendance)

• Intent (specific product interest, high-value actions)

We turned that into a structured lead scoring model in Pardot, which was then validated against closed-won data from Salesforce. This helped us define thresholds that actually meant something to sales.

Step 3: Rebuild the Routing Logic in Salesforce

This was the heart of the fix. I redesigned the lead assignment rules from the ground up- by geography, business unit, language, and product interest. We put in fallback rules to catch leads when an assigned rep was unavailable and added workflows to notify reps immediately when a new lead hit their queue.

This step alone reduced lead lag by over 60%.

Step 4: Create Accountability with SLAs and Dashboards

Once the process was rebuilt, we needed operational discipline.

• Sales agreed to a 24–48 hour response SLA for MQLs

• We introduced weekly dashboards tracking lead response time, status, and outcomes

• We created a “lead recycling” loop where marketing could re-nurture untouched leads

Most importantly, I created visibility. For the first time, we could see where leads came from, where they went, and what happened next.

Step 5: Educate and Embed the Process

Finally, I rolled out training across all regional marketing and sales teams to embed the new process.

• Held live sessions with Q&A

• Built simple playbooks for lead follow-up and scoring interpretation

• Worked with RevOps to ensure the process stayed live beyond rollout

The Outcome

Six months after launch, the impact was clear:

• MQL-to-SQL conversion rate increased by 50%

• MQL volume grew by 30% due to better scoring and routing

• Sales engagement with leads improved significantly

• Pipeline attribution became reliable and transparent

• The tension between marketing and sales turned into collaboration

Final Thought

What looked like a lead volume issue was actually a systemic trust problem - trust in the data, the process, and each other. By addressing the mechanics and the relationships, we didn’t just fix the funnel -

we built a foundation for growth.