Venture Capitalist at Theory

3 minute read / Apr 23, 2014 /

# Quantifying a SaaS Startup's Revenue at Risk

One of the key metrics that I don’t think gets enough notice when reviewing the health of a SaaS business is revenue-at-risk or RaR. For SaaS businesses with quarterly or annual contracts, each month some subset of the customer base’s contracts must be renewed. The RaR is the sum of the revenue from these customers in a given month or quarter. RaR is a useful measure because it captures the company’s opportunity to minimize lost customer revenue. Identifying customers at risk and proactively engaging them, cultivating a relationship and providing them account support can meaningfully improve a SaaS company’s churn rates.

I’ve seen two ways to calculate RAR: a probabilistic method and a customer-by-customer method. The probabilistic method multiplies the MRR by the historical monthly revenue churn rate. That figure is multiplied by 12 to annualize it.

`Probablistic_RAR = MRR x Revenue_Churn_Rate x 12`

The probabilistic RAR is top-down, so isn’t as accurate as the bottoms-up method. For example, some customers may have previously expressed a desire to renew, in which case their contribution to RAR should be excluded. The probabilistic RAR has a tendency to over-estimate the figure, but it’s useful as a back-of-the-envelope figure.

The more accurate method, customer-by-customer RAR, requires each account manager or salesperson to keep accurate records in a CRM about a customer’s likelihood to churn. If that data is accurate, calculating the customer-by-customer RAR involves summing the revenue of those likely-to-churn customers by month. Once RaR is measured, then the company can begin to measure RaR-save-rate, the fraction of RaR that is prevented from churning through the efforts of the customer success and/or sales teams.

`CbC_RAR = Σ Customers_Revenue_at_Risk`

It’s important to state that RAR isn’t constant throughout the year. RAR fluctuates depending on customer contract renewal schedules and fluctuations in sales teams bookings activity. Because of the variance throughout the year, understanding Revenue-at-Risk is important for four reasons.

First, RaR estimates help with cash-planning to ensure achievement of a target growth rate. Second, revenue-at-risk projections should be used to inform customer success staffing. Third, RAR-save-rate can be employed as a benchmark of a customer success team’s effectiveness throughout the year. Fourth, RAR is a tool to measure the effectiveness of the sales team in selecting the right customers to pitch.

Revenue-at-risk is an important metric to monitor for SaaS startups particularly as they scale. Initially, when churn rates are small, implementing the systems to measure RaR may seem excessive. But as revenues grow, sales teams swell and customer accounts multiply, SaaS startups must able to estimate and manage churn effectively.

For some code to generate a chart of Revenue-at-Risk, see this blog post.