Startups, and SaaS ones in particular, have a unique set of key performance indicators (“KPIs”) that help investors track performance. There are a ton of resources online that explain the definitions / how to calculate these metrics, but I thought it would be helpful to build it out in a model where you could tinker the assumptions and see it materialize on corresponding graphs.
For the sake of completeness, I’ll hash out the interpretations / definitions for the attached metrics.
- Customer ACV (Average Contract Value)
- Sometimes maps to revenue but as a standalone metric, is quite meaningless
- B2B companies generally have a higher ACV (fewer customers)
- ACV * number of customers = good proxy for total revenue
- Gross Retention
- Conservative measurement of recurring revenue retention, calculating on an annualized basis at which a given dollar of revenue is retained from year to year without credits for upsells
- Includes deductions for cancellations, reductions and price cuts without adding new sales or upsells other than price increases for the same revenue cohort
- Net Retention
- Measure of overall change in the base of recurring revenue from one year to the next including upsell, downsell, and cancellations
- Probably the most used metric for retention purposes as it’s the most accurate
- Implied Lifetime Value & Total Customer Retention
- Customer retention rate is a measure of the % of individual customers or accounts retained in a given year
- Implied lifetime is the inverse of the customer retention rate, which as the name implies, is a measure of the duration of customer lifetime
- CAC (New Customers)
- Measure of how much it costs to acquire a new customer
- Generally just think about sales & marketing expense divided by the number of new customers in a given period
- Ideally decreases as sales channels become more efficient and organic sales increase
- Enterprise sales are generally much higher than SMB sales channels (but short sales cycles and sometimes high churn rates)
- APRA (Average Revenue Per Account) and hard to benchmark
- Difficult to find the right numbers (private companies), and hard to use as benchmark cross firms but great for intrinsic comparison purposes
- APRA for New Customers – Measure of how much each newly acquired customer spends on an annual basis
- APRA for All Customers – Measure of how much a customer spends on an annual basis
- Delta between APRA (new) and APRA (all) would shed light on the implied net retention / upsell capabilities. I.e. If APRA (all) is significantly higher, it suggests that net retention rates are high and there is a lot of room to upsell an existing customer
- LTV (Lifetime Value)
- Total cash flow a customer will generate over its lifetime (not discounted)
- Roughly, APRA * Margin / Churn rate
- LTV/CAC Ratio
- Probably most used metric as it gives a holistic view of all the components of unit economics, and size / sales model / industry agnostic
- Note: might fluctuate given seasonality i.e. higher CAC in lower sales quarters and lower CAC in higher sales quarters
- You can see this in the “LTV to CAC Graphs” tab, how Q3 and Q5 have marginally lower multiples (cyclical)
I’ve attached the model below. Note that the blue cells are where you should input your startup / company’s metrics. It can be hard to find them on a quarter by quarter basis but sheds light on how certain growth / sales assumptions can drive the metrics VCs look at to benchmark and compare companies across the board.
Excel Model: KPIs and Retention Rates
Nat's Corner 