The industry seems to be moving fast to wipe the term 'MQL' from the marketing and sales vocabulary. Are MQLs really dying? MQLs work when done right.
What's an MQL?
MQL is an abbreviation for Marketing Qualified Lead. It's an easy concept to understand. The marketing team applies a set of lead qualification criteria to a lead. When the lead criteria are met, the lead is passed to the sales team.
The sales team has a higher degree of confidence that an MQL is a lead worth chasing. This process of lead qualification produces higher-quality sales leads. Until it doesn't.
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The MQL concept has been corrupted by marketing automation. Marketing automation relies on behavior to infer an MQL. It's a positive step in the evolution of lead generation but it's incomplete.
The goal is to automate as much as possible to gain efficiencies. But it isn't always possible to completely automate the MQL process.
When Do You Know You Have Good MQLs?
You know you have an efficient MQL machine when 70% to 80% of your MQLs are accepted by the sales team. That's a high bar and one you should aim for.
Anything lower than 70% means the criteria for your MQL is off.
Defining MQL Criteria is a Collaboration
Good MQL definition is a collaboration between the marketing team and the sales team. The goal is to define a set of attributes that represent a higher probability of a successful sale.
It's a process that requires ongoing monitoring and periodic adjusting. Meaning the MQL definition from two years ago may be obsolete today.
The marketing team and the sales team meet to define the attributes of an MQL. It's a process of working backward. Start with the attributes that make an ideal prospect. Then work toward a definition of a good prospect. Somewhere between good and ideal is where you start.
The number of attributes that define an MQL should be as few as possible. As long as the criteria produce good to ideal prospects you have the right number of attributes.
The process of defining MQL criteria is easier for a product you are selling successfully. The attributes of a good prospect are known. A new product requires market knowledge and intuition, followed by disciplined monitoring and experimentation.
MQL Performance Must be Monitored
Revisit the MQL criteria with the marketing team and sales team any time the acceptance rate of MQLs falls below 70%. This requires a mechanism to monitor MQL efficiency and report results.
The frequency of MQL performance assessment increases with the newness of the product. Older products might suffice with lower frequency. Newer products might need higher frequency.
MQL Criteria Changes Over Time
Adjusting MQL criteria is a process of short experiments and quick adjustments.
The marketing team and sales team meet to review MQL progress. They identify potential areas of improvement. Then they develop an experiment to test their hypothesis, which adjusts the MQL criteria. Then they execute an experiment to test the hypothesis. And repeat the process.
The goal is to automate as much of the MQL process as possible while producing an MQL acceptance rate between 70% and 80%
Don't Believe the Hype
The concept of an MQL isn't going away. It might be called something new as part of the hype cycle. But it isn't going away.
MQLs work when the criteria are on target and there is a discipline of continuous improvement.