Net revenue retention

Tova Feldheim

Hi CSM Community

I'd like to hear your perspective on who is responsible for NRR?

Do you feel this is a CSM team KPI or a companywide KPI? 

What is an ideal KPI %  for NRR and how much of that responsibility is the CSM team and other departments ( marketing, sales, support. product) 

Apologies if this was already discussed here

Thanks
Tova

Jeff Heckler

Hi Tova,

Nice to meet you.

If possible, everyone in the company should have a performance metric they are responsible for and measured on for NRR.

NRR is a company metric.

At a minimum, all members of revenue teams should carry responsibility.

The percentages will vary, however, they can be broken down both top-down and bottom-up.

Best regards,

Jeff

Ed Powers

I'm sure you'll get a range of opinions on this, @Tova Feldheim. In my view, the CEO is accountable for NRR. Customer Success, as well as all other functions, are responsible for doing their parts to improve it. As you suggest, customer retention and revenue growth are not exclusively an Customer Success concern, but are in fact, an enterprise-wide pursuit. 

So how can you develop KPIs for each functional area to do their share? The best way I've found is to first study why customers leave and why others stay and buy more. This can be done qualitatively through interviews immediately after customers make their decisions, providing deep, rich context. It should also be done quantitatively by classifying primary reason (or top three reasons) into categories: fit, features, support, cost, change in needs, financial struggle, etc. Then it's best to use Pareto analysis to show relative frequency and impact of the reasons on retention and NRR. You will quickly see that a few factors explain the vast majority, a set that varies for every company. The impact will be VERY big and highly motivating once you consider lost revenue, total cost, and most importantly, company valuations. 

Once the top customer churn, retention and growth reasons are known, then you must look upstream in the process for existing (or new) metrics that point to them. For example, if "fit for our needs" is a top-cited reason, how might you measure this? Chances are your solutions engineering or implementation team could give an objective rating (e.g. 1-5 score where 1=poor and 5=excellent) to evaluate how customer needs are aligned to solutions during the customer acquisition process. Do this for all the top reasons and start collecting data. Data then forms the basis for KPIs and determines where functional responsibility for improvement lies. Once you have data, you then can build predictive customer health scores using regression analysis or more sophisticated AI/ML techniques. Even better, your functional leaders can use the KPIs to drive continuous improvement in products, services, and processes, resulting in lower customer churn and higher NRR.

And perhaps most importantly, all of this must be led from the top down, which is why quality guru W. Edwards Deming said, "Quality begins in the boardroom." In you or anyone else is interested, I'm always happy to talk more about how to engage your C-level team and drive enterprise-wide change: [email protected].

Steve Bernstein

Spot on and thanks for the detailed contribution, @Ed Powers!  I suspect the reaction from many CS folks reading this might be
(1) "wow, that sounds like a time consuming effort" and /or
(2) "wow, this sounds like more trouble than it's worth." 

But you and I know from our tenure in this world that often it's better to slow-down-to-speed-up.  There are so many studies that show how data-driven decision making accelerates NRR growth. Sadly, many startups lack patience and suffer the consequences. 

Why don't more companies embrace evidence-based (data/insights) decision making, instead of decision-based evidence making?  I'm super-interested to hear from others in the community what they think about this and why such efforts to "do it right" often get blocked internally, or never even started...? 

On the other hand, it'd be equally wonderful to hear even more stories of companies running on data/insights, not the Hippos (HIghest Paid Person's Opinions).