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Why Qualified Marketing Pipeline Is ‘True North’ for the Modern CMO

4 min

MQLs are insufficient for the modern marketer’s needs. To drive revenue, you must begin with the end in mind.

Few CMOs would disagree that revenue is the true measure of marketing’s success. Yet most marketing teams still work hard at generating MQLs — marketing qualified leads. In fact, according to a forthcoming 6sense survey, 70% of marketers believe that MQLs are either an “extremely” or “very” important metric for measuring performance.

So why are most marketing teams overly driven to produce MQLs, rather than revenue contribution? 

For far too long, marketers have been trained to play the “batting average game” — focus on producing more leads and improving conversion rates so enough of them convert to sales opportunities (i.e. pipeline).

MQL methodology is what they’re familiar with and even if they wanted to try something different, virtually every marketing application is designed around delivery of sufficient leads and not pipeline. 

Apart from being suboptimal from an efficiency standpoint, the MQL approach puts marketing and sales teams at odds with each other. Sales teams are measured on bookings target or quota attainment, not lead conversion. So when sales can’t meet its quota, they often complain that “marketing isn’t generating quality leads.”

Naturally, marketing responds that “sales isn’t following up on their leads.” Research shows the average sales team ignores 50% of marketing leads and only 7% believe that leads received from marketing are of high enough quality. 

So is this a sales and marketing alignment issue? Yes, but that’s just an unfortunate symptom of the real problem. The underlying issue is that marketers don’t track the most critical metric. In their pursuit of MQLs, marketers are ignoring delivery of pipeline — or qualified pipeline to be more precise

True North for Marketing Is ‘Qualified Pipeline’

Sales operates on the basis of near-term pipeline coverage: Do we have enough real pipeline (e.g. 3x) for this quarter and the next to meet our quota? However, marketing needs to have a forward-looking pipeline plan: Can we ensure we’re producing enough “real pipeline” so sales can achieve their quota in future quarters?

And while we’re on the subject, what is “real pipeline,” anyway? It’s when the MQL is converted to an opportunity or when sales has qualified that opportunity with a real value and close-date that everyone trusts to be true.

For sales and marketing to have genuine alignment, marketers must plan and track qualified pipeline as their core metric for success, and they must do it in a forward-looking manner. 

Their qualified pipeline plan must account for…

  • Actual sales cycles
  • Deal sizes
  • Conversion rates

…and they must do this for every go-to-market segment, sales territory, and product category. It’s a completely new way of thinking about marketing’s role in generating revenue, and it works.

So how do most marketers currently create their pipeline plans? And what are the shortcomings of the current process? 

Marketing Pipeline Planning Today

Most CMOs start with a corporate bookings plan that has been agreed at the executive and board level and usually maintained by the CFO. They determine the type (e.g. new vs. upsell) and proportion (e.g. sales vs. channel vs. marketing) of the total corporate pipeline that marketing is responsible for.

And then they make three key assumptions for inputs needed to create their marketing pipeline plan: 

  • Conversion rate, which determines the rate at which leads will convert to opportunities 
  • Opportunity size, which determines the number of opportunities needed to achieve the pipeline plan
  • And sales cycle, which determines when the opportunities need to be generated to ensure that the corporate bookings goals are met

By using assumptions for these three inputs, CMOs estimate their pipeline plans for every go-to-market segment (e.g. account size and industry), sales territory, and product category. The latter can add a fair bit of complexity to the marketing pipeline plan, if you have a complex go-to-market structure.

These pipeline plans are often maintained in spreadsheets by a team of analysts.

So apart from being manually time intensive, what’s wrong with this approach? 

Key Pipeline Planning Challenges

Quite simply, the marketing pipeline plans are often based on incorrect input assumptions

We’d challenge any CMO to compare their assumptions for conversion rates, opportunity sizes and sales cycles with their actual historical data (assuming it’s available) for each go-to-market segment.

Most would find a fair degree of variance between actuals and assumptions. In short, your marketing pipeline plan is likely to be based on assumptions which are more often wrong than right. That’s a scary thought if your entire marketing motions are also designed to deliver on that plan.

This is partly why many CMOs are not confident that their marketing efforts will definitively result in the revenue outcomes that are expected of them. In short, they’re flying blind.

Thankfully, there’s a better way.

6sense: A Better Approach to Pipeline Planning

6sense’s Pipeline Intelligence capability solves this problem by enabling CMOs to not only track and forecast “qualified pipeline” as their core KPIs. but also enable them to analyze actual conversion rates, opportunity sizes and sales cycles for every go-to-market segment and sales territory. CMOs can:

  • Use these actual KPIs (e.g. for the previous 8 or 4 quarters) for pipeline planning
  • Examine their conversion rates by time cohorts
  • Measure the open marketing pipeline from previous quarters to get more headroom for hitting their plans
  • And more

So whether you’ve already completed your marketing pipeline or are in the middle of planning it, talk to us. We can help you build a marketing pipeline plan so you can execute with confidence. We’ll share related insights on forecasting in a future blog post. Watch this space!

The 6sense Team

6sense helps B2B organizations achieve predictable revenue growth by putting the power of AI, big data, and machine learning behind every member of the revenue team.

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