Death of the MQL

Before you bring out the pitchforks, I didn’t dream this up. Just Google “MQL is dead” and you’ll find page after page after page of experts saying the same thing.

For the uninitiated, MQL means “Marketing Qualified Lead”. In marketing-land, the term is ubiquitous, pretty much like the air we breathe.

So, what happened? Why the coup d'état against an old and established framework?

To understand that, let’s quickly revisit what MQLs mean.

Defining an MQL

The idea behind MQLs is that marketing, through all the initiatives it undertakes, such as organic search, paid media, earned media, and online and offline events—generates leads. Some of those leads, based on a commonly shared understanding of suitable attributes, become MQLs, which are then handed off to the sales team.

Depending on the quality and relevance of the lead, the sales team may then convert the MQL into SQL (Sales Qualified Lead), and eventually the SQL into a deal or opportunity. As with most things, the success of this framework depends largely on how closely marketing and sales teams are (or are not) aligned.

Conversion ratio as an indicator

If you have a really low MQL-to-SQL conversion ratio, it means the alignment is poor and marketing is unfortunately spending a large chunk of its time and resources on channels that don’t materialize into new revenue for the business.

To be honest, that’s a bit of an oversimplification, there are factors that can lead to a lower conversion ratio, for example, if the qualification thresholds are too high or specific. If all you want a lead to do is pay you $10/month for a product or service, that’s a low bar. Anyone with a credit card is a potential SQL. But if you sell inventory management software, to agriculture equipment companies, with a minimum annual spend of $200k—well, a low single-digit ratio is perhaps the best you could hope for.

In the latter case, marketing would be far better off tossing the idea of “leads” altogether, and instead thinking in terms of shared target account lists, buying committees, number of touches, and influenced pipeline—in short, an ABM strategy.

Quality and processing delays

MQLs are also more often than not the classic definition of a vanity metric. Depending on the underlying quality, 10 MQLs could outperform 100 MQLs in terms of revenue (potential or materialized). To take the previous example, landing a John Deere could generate more revenue compared to landing 10 small, agri-tech startups.

Finally, lead qualification usually has processing delays. The sales team may take too long to engage an MQL. Or someone downloads an eBook from your website, but your team is unsure whether or not that counts as a “buying” signal. Or an integration breaks and leads go stale before it’s identified and fixed. And so on. Things like these happen everywhere, all the time, with everyone (present company included).

Beyond the MQL

This isn’t to say that MQL/SQL/Opp is a useless framework. At least I don’t think it is, despite the recent tirade against it. I think that having some framework is an improvement over no framework, but I also think that it can be reductive.

Before we go further, let me just say that the proof is in the pudding. If this framework works for your organization, by all means, keep pressing forward. But I’m assuming that if you’ve read this far, its apparent weaknesses resonate with you at some level.

So, how do you measure marketing’s contribution, if not MQLs? Here are two ideas:

Conversion-ready (CoRe) leads

Dave Ewart, Oracle’s head of digital marketing and demand generation was told by the SVP of Sales at Oracle that he didn’t want his team working on qualifying MQLs because it was a waste of valuable time.

Though Dave was new to Oracle at the time, he made a counter-offer: “How many conversation-ready leads would you accept?”

To this, the SVP of Sales said: “100%”

Over the next few years, Oracle re-tooled its GTM processes to focus on the newly termed conversation-ready (or CoRe) leads, distinguished from non-core leads as “qualified responses with intent to have a conversation”. The result? Oracle reduced the amount of leads they sent over to BDR and the sales team while increasing results in terms of opportunities, pipeline acceleration, and conversion rates.

Of course, you don’t have to call them CoRe leads. In fact, perhaps your existing definition of MQL already includes that key qualifier, i.e., intent to have a conversation. In which case, congrats on being a step ahead of the curve.

Marketing-influenced revenue

While conversation-ready leads are an improvement over the standard definition of MQLs, which often factor in an internal scorecard of checks instead of the readiness of the buyer—it fails to provide a holistic picture of marketing’s contribution to the revenue pipeline. Why? Because CoRe would, much like MQLs, give you a number.

This is where marketing-influenced pipeline and revenue come in. By tagging deals or opportunities and customers that are sourced by marketing, marketing teams can track their revenue contribution through the entire lifecycle of the business. Showing this impact can give marketing the leverage to ask for more resources and invest more in channels where the revenue is coming from—not just where MQLs are coming from.

I’ll sum it up by saying that, unlike sales, generating revenue is not the only job that marketing has. By necessity, marketing teams have to work on things that don’t always scale and can’t always be measured, this is just the nature of the beast. But at the end of the day, revenue is the lifeblood of any business. For mature B2B companies, with good product-market fit and marketing-sales alignment, a 25-30% marketing-contributed/influenced pipeline is an often-quoted benchmark.

If you start measuring this today, you may realize you’re not quite there. Maybe you’re at 5% or 10%, but since you can only improve what you measure, the first step is to have adequate processes and controls in place to start the measurement process.