The 4 Steps To Resurrecting The MQL

Published: May 10, 2023

To MQL, or not to MQL — that is the question. Over the past year, the industry’s narrative toward MQLs has shifted: It went from the golden goose of marketing to an allegedly inefficient way of driving leads. However, a new perspective is emerging throughout the industry. RollWorks, an ABM platform, is taking the stance that MQLs aren’t dead; just the bad ones are.

To understand how marketers can revive MQLs’ reputation, the Demand Gen Report team chatted with Jodi Cerretani, RollWorks’ VP of Marketing, to get her perspective on the MQL debate. While we’ll reveal the full discussion later this month on our sister publication, ABM In Action, here’s a sneak peek into what you can expect:

1. Focus On Fit

According to Cerretani, one of the most common reasons an MQL fails is because practitioners aren’t fully focusing on fit. She continued that, “many organizations don’t use fit as a focus and equate it to activity, which results in disqualified or low-fit leads sneaking through to the MQL stage through scoring.”

Additionally, she explained that sometimes marketers practice “bad habits” — if they’re not hitting their KPIs, they might:

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  • Change the definition of an MQL;
  • “Fudge” their numbers a bit; or
  • Make up their own definition of an MQL, due to misalignment with sales.

2. Align Sales & Marketing

Naturally, the solution to generating better fit leads relies on aligning sales and marketing teams. Cerretani explained that the tech explosion of the last decade enables practitioners to get a much clearer picture of buyer data than ever before. Through first- and third-party insights, organizations can now combine data that traditionally existed in disparate systems to unite internal departments.  She also pointed to machine learning and AI as beneficial factors, as the technologies help marketers drive multiple buying signals and pass them over to sales.

3. Implement A ‘Signal First’ Approach

The ‘big picture’ of a signal-based approach is when marketers can combine data sources in a meaningful way and include some combination of fit and intent, or fit and engagement — basically any sort of fit and activity combination, Cerretani explained. She continued that this helps determine what accounts and contacts are worthy of sales outreach.

However, she recommended that marketers proceed with caution and turn to their partners for help, as “there’s so much activity happening across your first-party properties and third-party engagements that it’s a little too complex to coordinate without a technology partner.”

4. Eliminate ‘Bad’ Leads

Organizations must focus on the KPIs that have the ultimate business impact — and Cerretani pointed to data that indicates fit is the most important focus. She continued that marketers need to broaden the signals that maximize ‘at-bats’ for sales and ultimately influence revenue impact.

“I’m a big fan of killing bad leads — if you don’t have a lot of qualification criteria or a target account list, then a lead isn’t going to be valuable for your business,” she explained. “Instead of killing all leads, get rid of poor fit accounts and people. Killing the MQL only makes sense if the lead isn’t a high fit person or account.”

This is only the beginning of repairing the MQL’s reputation — sign up for our ABM In Action newsletter to receive the full interview when it’s live!

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