Creating a Customer Success Staffing Model

This is the third post in the series about Customer Success ROI. The first one discussed the wisdom of not doing ROI analyses. The second showed how to calculate benefits. In this post, we build a staffing model that can be used for ROI analyses and also to forecast headcount and test all manners of hypotheses and experiments. It requires a bit of work to set up, but you will use it for many years to come.

Let’s start with the magic formula to calculate Customer Success headcount:

headcount = effort hours / available hours

The denominator is straightforward: available hours are simply hours worked that are actually focused towards customer efforts. So vacations, meetings, or administrative email wrangling need to be taken out from the 40 hours a week or whatever figure you use for a full week’s worth. A typical utilization rate for CSMs is 75%.

Effort hours can be computed with a simple multiplication:

effort hours = # accounts * hours per account

For this, it’s best to work by customer segment (since larger accounts have more deliverables, hence more hours per account), and to separate onboarding from retention (in other words new accounts from existing accounts). So if you have 2 segments you may have 4 different calculations, for large new accounts, large existing accounts, small new accounts, and small existing accounts.

Here’s a sample staffing model for a single segment, separating onboarding and retention efforts.

Once the model is validated, you can use it to run experiments. For instance, let’s say you introduce self-service tools that decrease the number of onboarding hours to 2 per customer. You can see that the headcount can remain stable despite the growth in customers.

Or you can see what happens if you focus the program on just the large customers:

Do you use a Customer Success staffing model? Tell us about it in the comments. And if you need help creating yours, contact us.

 

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