In early 2017, Gartner’s Todd Berkowitz announced the impending death of the MQL. Most B2B marketers were sympathetic to the idea but unable to change. After fifteen years of using the MQL as the primary demand-gen KPI, marketers weren’t ready for an alternative model. More to the point, in 2017, alternative models didn’t exist.
Even so, it was clear that things needed to change.
Berkowitz called out the problem of scale that’s intrinsic to the MQL-centric model. If sales targets grow 2x, the MQL target also has to grow 2x to keep up. Unfortunately, since the marketing budget doesn’t automatically double when sales targets do, demand generation marketers are forced to try to generate more MQLs at a lower cost per lead (CPL).
The results of this upside down equation: MQL quality suffers, MQL-to-close conversion rates go down, and then the MQL target increases to try to compensate for poor performance. It’s a painful, no-win cycle that every demand generation marketer knows only too well.
Gartner was not alone in their prediction of the MQL’s demise. Also in 2017, Kerry Cunningham and Terry Flaherty at SiriusDecisions introduced the Demand Unit Waterfall, a demand generation model that shifted focus away from the traditional MQL. They identified two major trends driving this shift:
A MOVE TOWARD DEFINING “THE BUYER” MORE ACCURATELY
The Demand Unit Waterfall approach recognized that the lead-centric model, which is limited to one individual within a target company, was inherently inaccurate. Most large purchases involve multiple individuals within an organization. Based on this reality, the “demand unit” represents the B2B buying team, which includes everyone participating in the research, evaluation, and purchase of a solution.
Experienced BDRs and sales reps often describe an MQL as an invitation to begin prospecting into an account. It’s a tentative starting point. In many cases, the MQL is only an influencer rather than a project champion, technical decision-maker, or the person who actually has the power to make a deal. Because of the complexity involved, MQL-to-opportunity conversion rates are very difficult to measure accurately with a CRM system that is unable to account for all the players or their relationships to one another.
INCREASED ABILITY TO TRACK AND ANALYZE “PRE-MQL” ACTIVITY
A lot happens before someone in an account becomes an MQL. The evolution of sophisticated software tools gave marketers the ability to track and understand pre-MQL buyer activity much earlier in the sales process and at a much greater level of detail.
These superior data, analytics, and monitoring tools opened the door to new possibilities:
• What if marketers could understand who was in buying mode and researching a solution similar to their own?
• What if marketers could track when 3 or 4 people from a particular company visited their website and consumed a lot of content without converting on a form?
As marketers gained access to this wealth of information, they realized there was no reason to wait to tell sales. Timely insights about an account moving into buying mode helped salespeople hone in on the highest-value opportunities
so they could prioritize their prospecting efforts and start focused research to find the right contacts in those companies.
Waiting for prospects to generate sufficient behavioral data to trigger the creation of an MQL results in a critical delay that puts sales one step behind the competition. In addition, by limiting themselves to an MQL model focused on individuals rather than teams, marketers are unable to uncover the signals that tell sales an account is in the early stages of the buying cycle.
In addition to those two primary drivers, other trends influencing marketers’ shift away from the MQL lead-gen model include:
1. MQL CONVERSION:
BDR and sales teams have found that MQL conversion rates to SQLs or meetings (usually in the mid-single digit percentages) are only marginally better than unqualified leads.
2. MARKETING FOCUS ON REVENUE:
Marketers are shifting more focus to opportunity and revenue goals, which requires access to more accurate leading indicators of success than MQLs.
3. BETTER GO-TO-MARKET MODELS:
Better go-to-market models have emerged. Whether it’s the Demand Unit Waterfall from SiriusDecisions or one of several ABM (account-based marketing) models, each of these new methodologies is better aligned with how companies buy today.