Coverage isn’t just a Sales thing
Anyone who’s worked in RevOps long enough knows the ~thrilling~ activity that is calculating pipeline coverage.
All jokes aside, it truly is a simple and effective way to predict bookings.
That’s great for sales, but did you know marketers can also leverage the concept of coverage to make sure they are on track for hitting their own OKRs?
*DISCLAIMER: Coverage should never be used as an OKR. Measuring targets on coverage encourages artificial inflation of likelihood to close, and/or close dates on open opportunities being set earlier than they should be. Similarly, the following metrics should be used for KPIs only.
The Basics: Calculating Pipeline Coverage
Hot take: marketing doesn’t create pipeline, and they certainly don’t close it. And yes, this is coming from someone who spent the past decade sitting in and adjacent to marketing teams. Sure, we have LOTS of influence on whether leads become “qualified” enough to get in front of sales. We’ve proven that marketing engagement both increases opportunity close rates and decreases time to close. But the actual sales activities on those opportunities? They belong to sales. And quite frankly, they can have them!
With our MarTech and CRM stacks increasingly collecting and processing more information every day, we have a gold mine of predictability at our fingertips. As a refresher, here’s how to calculate pipeline coverage:
There are ways to get a more accurate coverage ratio, but that’s another article for another day.
This calculation returns a coverage factor. For example, if you have $1,000,000 in pipeline coverage with a quota of $500,000, you’re 200% covered. You can calculate the minimum coverage ratio you need to predictably reach quota, but again, that’s another article for another day.
Marketing Coverage: Ummm what?
Sales leadership relies on coverage to understand progress towards revenue targets - specifically, to get a sense on whether or not they’re going to meet them. If things look bleak, they’ll know early and adjust their strategy accordingly. As a marketer, wouldn’t it be great to have red flags, and green flags (is that a thing??) early? Why should sales get all the fun!
Here’s how marketers can take a similar approach to know if they’re on track to reach their goals.
Step 1: Model your lead lifecycle.
Yes, this is easier said than done. Let’s assume you already have a lifecycle mapped out, and you’re measuring it somewhere: in a CRM, MAP, Excel… if you have the data, you can use the data. (P.S. don’t have a lifecycle model? Hit me up!)
Step 2: Calculate your stage-to-stage conversion rates.
If you happen to have Marketo, this is easy. Just go to your Success Path Analyzer.
If you don’t have Marketo, don’t fret. The calculation is simple:
Note that this is not a cohort analysis, but is a quick-and-dirty way to get baseline metrics.
Step 3: Calculate your stage-to-stage conversion velocity.
Similar to the step above, we need to figure out how long it takes your leads to convert through each stage. Again, easy if you have Marketo’s Success Path Analyzer. If you don’t, just calculate “Stage 2 Date” - “Stage 1 Date” and average it out for everybody who actually made it to Stage 2 (you can do this in Salesforce or Excel).
Step 4: Put it all together.
You may have already done all the other steps. Funnel velocity and conversion are metrics all marketers should keep an eye on, regardless of funnel coverage. But they’re also key factors in calculating funnel coverage. Because marketing starts so early in the lifecycle, we need to start coverage projections ~2 sales cycles ahead of target.
Here’s an example for calculating SQL Coverage:
Target: Take your current quarter SQL target.
Inventory: Apply the conversion rate from Step 2 to see how many contacts you need to currently have in the previous stage. Example: if the stage before SQL is SAL, see how many SALs you have right now.
Velocity: Apply your conversion time from Step 3 to see how long it takes your SALs to convert to SQL. Now, see how many of your SALs have been in the SAL stage for close to that length of time - and how many will be by the end of the quarter.
Finally, multiply it all together:
This is your SQL coverage.
Do this for every stage in your funnel. And use that information to answer:
Am I covered for this quarter, for the stage immediately prior to pipeline?
Am I covered for future quarters, for early stages in the funnel?
And that’s it! As you start regularly measuring funnel stage coverage, you’ll notice trends and get a sense for what your coverage numbers are telling you.
Stay tuned for more as we dig into:
Finding how much funnel coverage you actually need to hit your OKRs.
Back-calculating stage-by-stage targets based on historic coverage performance.
