Why Marketers Need to Love the Opportunity Cohort

The opportunity creation cohort is one of the key cohorts for marketers.  The handoff in effort from marketing to sales begins at this point.  It is also the point where you can start to measure revenue impact from marketing efforts.  It is the one of cohort you need to love, nourish, and be 100% in tune with the sales team on.  This is the one cohort that can avoid all the way too common sales and marketing drama. 

The opportunity cohort is a measure of the opportunities created in a given month or time period and the disposition of these opportunities over time.  The disposition of opportunities is generally won or lost.  Each disposition can then have greater details depicting why a deal was won or lost.

This is where the revenue rubber hits the proverbial road. Opportunities and deals, and what is driving them.  If you can’t figure this out, you don’t know where to drive (continuing the rubber and road analogy).


Hence tracking the source of the opportunities is as important as tracking the disposition.  Sources of opportunities could be marketing leads, partners leads, sales rep prospecting, or unknown bluebirds.  The challenge with bluebird opportunities is that you can’t reproduce an opportunity if you don’t know where it came from. Tracking the percentage of unsourced opportunities is critical and should be kept to as small a number as possible by sales management.

Tracking opportunities created back to marketing leads can help drive overall demand generation strategy as well as providing a good indicator to the length of time required for a lead to ferment from initial contact to opportunity. 

Looking at the disposition of the opportunities is important to determine overall win rate, but also the timing of the wins.  Out of each cohort, a percentage of opportunities created will close over a fairly predictable time frame based on the actual sales cycle.  Of course opportunity creation is impacted both the seasons and by management oversight.  The key is to track opportunity creation year over year by month and quarter to get a good feel for its velocity.

Since opportunities created drive the total pipeline size for the company, there should be an opportunity creation goal for each month.  This number should be based on the required total pipeline to meet revenue objectives. Most sales leaders do basic math for pipeline to close ratios.  This can get the company into trouble however.  But looking at opportunity creation and closing as a cohort, revenue prediction should improve.

See the chart below.  Assume that the company has a stable 15% opportunity close rate.  Assume the close rate is 8% for opportunities created in that month, 4% of the opportunities created close one month later, 2% two months later, and 1% three months later. The January row below is an example. Look at the row for January and you see that by April, 15 of the opportunities from January have closed for yield of 15%.  Of course, if yield is this stable for prior months, you also see in the January column that 15 deals will also close. But this is only from 8 deals created in January, the rest are from deals created in prior months, but closing in January.



If you model the opportunity creation cohort this way, you should be able to predict future revenues.  Indeed, let’s assume that March is unusually strong in opportunity creation, if the same in month close rates hold, with 200 opportunities created, you would expect to get 8%, or 16 closed deals.  The strong March would also provide stronger follow on months if the yield curve held. The yields for February and March are less than expected since more deals will close from those cohorts in April, May and June. Month to month variations in close rates and creation rates are to be expected.

Next up- the nurture cohort.



Published by bryansemple

During the day, I work at a leading technology juggernaut. At night, I apply my early career experience as a submarine officer where we measured everything to the art of sales and marketing where we don't measure enough.

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