The
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Posted by: ClickZ
Posted on:  3/30/2020

I was recently asked to participate in a webinar called “True Confessions of a CMO,” and the topic was MQLs.

Well, here’s my true confession: I’ve never cared about MQLs.

It’s not that I don’t care about MQLs because I’m some kind of marketing genius. Honestly, it was quite the opposite: I stepped into a marketing role from sales, and because MQLs never did anything for us in sales, I just fundamentally didn’t get the hype around them. But not caring about MQLs has proven to be a huge advantage for me as a CMO.

I’ve always wired my marketing teams to look at the revenue plan and then convert it into pipeline targets. This requires knowing things like cycle time, win rates and average deal size in order to build “pipeline quotas.”

For marketers, setting your sights on opportunities, pipeline and revenue ensures better alignment with your revenue team peers in sales and customer success.

That shifts us away from MQLs, which are still the lifeblood of many marketing teams. While MQLs can still be a possible leading indicator, they’re fraught with issues:

The 3 scenarios of MQLs

A good portion of the B2B buying journey happens in the dark. What I mean is most B2B buyers tend to remain anonymous — preferring to do their own research — until very late in the sales cycle. MQLs typically require a hand raise or website form fill in order to provide enough information to qualify the lead.

This creates three likely scenarios:

Scenario 1

Buyers from target accounts don’t fill out our form because they know exactly what will happen next, and they’re just trying to do some independent research.

Our “content gate” sends them right into the arms of the next site listed in their Google search results, where they can gather plenty of content without the hassle. For some reason, we’re fine letting them be educated by our competitor.

Scenario 2

We get a form fill on our gated content and it’s a consultant, job seeker, company in Slovakia we can’t support, or [email protected]. These “leads” get routed and answered, and then clog up the system with junk or — heaven forbid — slip through to sales. It becomes a colossal waste of time and possibly damages our credibility.

Scenario 3

We get a form fill from an actual buyer at an actual target account. Blessed by the MQL gods, we anoint it a “hot inbound.” That’s when we discover we’re just one of several vendors under consideration. Or, the buyer has already done most of their research and are finalizing their “list.”

This is WAY TOO LATE to properly educate the buyer and meaningfully influence the opportunity. We missed the ideal time to engage, all in the name of the elusive MQL.

Subjective MQLs miss the mark

We know B2B buyers buy in teams, often involving six to 10 people in a complex B2B purchase decision. But MQLs keep marketers stuck thinking about leads or contacts, not buying teams.

This creates a split between sales and marketing and is a missed opportunity for marketing to surround and engage all the buying team’s members to build REAL pipeline.

Add the subjective nature of MQLs (and SQLs for that matter). The slightest change in criteria can create a windfall or pipeline gap and further divide your sales and marketing teams.

Despite our best efforts to make “lead scoring” a scientific process, it remains a largely rules-based exercise built upon subjective human judgment.

At this point, I hope many of you are nodding along. I’m also guessing you might be rather anxious. After all, how can you understand the impact of what marketing is doing if you’re not tracking MQLs? How in the world are you going to measure the top of the funnel? How can you ensure appropriate leads are followed up on and “worked” properly?

Transitioning to an account based strategy

Good marketing has always been about segmentation and targeting; we’ve always known and strived for this. Today’s ABM platforms, however, give us the means to measure our effectiveness — not for credit or as an end goal, but as a way to optimize campaigns and budget.

Measurement is taken not in the number of leads but rather in account engagement, and more specifically account engagement of your ideal customer segments. If you have great segmentation capabilities, you can segment your ICP for a given product line, a certain industry or current customers.

Then it’s all about running campaigns that drive great engagement against those segments. Some campaigns are large and target hundreds of accounts, while others may only have 10 accounts.

But EVERY program ties out to a campaign, and we measure cost versus increasing or decreasing account engagement, open opportunities and pipeline on the campaign.

This lets us adjust when things don’t perform, benchmark our overall performance over time, and evaluate the top programs.

My team applies the Jack Welch method to our adjustment model: every six months, we stack rank our programs and cut the bottom-performing 10%. It helps us make sure everything we do is directed toward making campaigns better.

Transparency builds trust within our teams, too. We give our sales and customer success teams full access to our results.

For each account, they can see which marketing campaigns have increased engagement and the exact programs we’re using to warm accounts or nurture deals. It prevents bad blood between sales and marketing and replaces a subjective MQL with a data-backed decision.

Instead of depending on the handraise an MQL requires, we can play offense and go after leads where they are. With an ABM platform measuring account engagement, we get a clearer picture of who’s ready to buy and then can send them the most tightly-honed campaigns to move leads into our pipeline and beat our goals.

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