Why More MQLs
Is Not the Answer

When a B2B marketing team gets told that pipeline is light, the usual first response is to generate more leads. Run another campaign. Lower the scoring threshold. Capture more contacts. Get the MQL number up.

The problem is that this treats a quality problem as a volume problem, and the two have opposite solutions.

How MQL inflation happens

MQL criteria drift under pressure. A contact who opened one email gets counted alongside someone who attended a product demo and has buying authority. The scoring model gets tweaked to include lower-intent signals because the pipeline looks thin and something needs to change this quarter.

The number goes up. Sales gets more MQLs. Sales follows up on a handful, finds most of them unqualified, and stops following up on the rest. The handoff breaks. Marketing says sales isn’t working the leads. Sales says marketing sends them rubbish. Both are right.

This pattern is worth understanding at its root, because it’s almost always caused by the same thing: no agreed, written definition of what an MQL actually means for this business, at this stage of its growth, selling to this specific buyer. Who owns that definition is a separate but equally important question.

Volume isn’t the metric that matters

The metric that matters is MQL-to-opportunity conversion rate. If that rate is sitting at 5% or below, adding more MQLs doesn’t fix anything — it just increases the amount of noise sales has to sort through before giving up.

A team generating 50 MQLs per month at 20% conversion creates 10 opportunities. A team generating 200 MQLs at 5% conversion also creates 10 opportunities, but has burned four times the sales capacity doing it. The second team will feel busier and produce the same output.

There is also a secondary cost that’s harder to measure: when sales stops trusting marketing’s leads, they start sourcing their own. The sales and marketing relationship degrades. Alignment conversations become defensive. The commercial team fragments into two groups with different priorities and little shared accountability for pipeline.

What the quality problem actually requires

Fixing MQL quality means going backwards through the funnel to understand what won deals looked like before they became opportunities. What firmographic signals did they share? What intent behaviour appeared early? What content did they engage with, and at what depth?

Then the MQL definition gets rewritten to reflect that pattern — not to reflect what’s technically possible to track, or what makes the number look good in a report.

Volume will likely drop when you do this. That’s correct. A lower volume of better-fit leads almost always produces more pipeline than a high volume of mixed-quality ones. The distinction between lead capture and demand generation is relevant here: if the underlying programme is only capturing existing intent rather than building new demand, tightening criteria just makes the volume problem more visible without solving it.

A note on target-setting

MQL volume targets are often set by people who don’t control what counts as an MQL. If the conversation about lead quality only happens at the operational level but the targets are set at the leadership level, nothing changes. The pressure to inflate will always win unless leadership understands that a lower MQL number with better conversion is a more productive outcome than a higher MQL number with a broken handoff.

Common questions

What is a good MQL-to-opportunity conversion rate?

Conversion rates vary widely by industry and deal complexity, but for complex B2B the benchmark sits between 10% and 20%. If your rate is consistently below 5%, that’s not a volume problem — it’s a definition or targeting problem. More MQLs at the same low conversion rate just means more wasted sales time.

How do you fix MQL quality without just reducing the number?

Start by auditing what closed-won deals had in common before they became opportunities — seniority, company size, industry, engagement pattern, intent signals. Rewrite your MQL criteria to match that pattern. Volume will likely drop initially and conversion rate will rise. The pipeline output stays the same or improves.