Until recently, many startups have prioritized growth at all costs, using abundant venture capital to acquire users and dominate markets without regard for profitability or sustainability. However, recent market conditions have shifted toward “efficient growth,” balancing growth with profitability to create a sustainable path to scale.
As investors, we are laser-focused on identifying efficient growth early in the company’s journey. What are the early indicators of a startup’s long-term success and efficient growth? As we try to find the answer to this question, we use various analyses, some of which we cover in this article.
The flaws of using LTV/CAC — why we use cohorts to assess sales efficiency
Before hopping into our analyses, we want to cover why a commonly used metric could be misleading. Often, investors evaluate the go-to-market engine of a business with the LTV/CAC (lifetime value/customer acquisition cost) metric, but this metric is frequently immaterial for early-stage companies for a few reasons:
- There are too many ways to calculate LTV.
- The churn rate is not stable enough to accurately forecast customer lifetime. As an early-stage company, the rate at which a customer churns fluctuates as the company seeks to fulfill product-market fit. With a product improving over time by adding features that address customers’ needs, we would expect the churn rate to decline. Despite an improvement in a product, there are external factors beyond a company’s control, such as macro headwinds, that may encourage a higher churn rate.
- There is a time mismatch within the ratio: The LTV/CAC links today’s sales and marketing spend to the projected, discounted future cash flows of a customer, which is inherently an estimate. For example, using metrics collected during COVID-19 to predict the future would likely result in inaccurate forecasts.
As investors, we leverage cohort analyses to elucidate the mechanisms of growth, retention, and sales efficiency.
Given the various ways LTV can be calculated, the lack of steady-state churn rate data, and the estimated value of the LTV/CAC calculation, there may not be a true sense of what drives acquisition and retention of a company’s customers. Considering the shortcomings of the LTV/CAC calculation, we propose using a cohort analysis to plot how long it takes to pay back the initial sales and marketing spend to acquire each cohort.
What are cohorts, and why are they important?
A cohort analysis is a method to assess businesses by clustering customers into groups (cohorts) starting at different points of acquisition and observing how they behave over defined intervals of time. Tracked behaviors include the number of orders placed, amount of spend, and number of features used over periods.
One can apply this analysis to various business models, such as SaaS, fintech, and even marketplaces (back then, we used it to analyze a ride-hailing company). An analysis of cohorts is valuable because observing a particular variable over time allows one to understand the business narrative of revenue, acquisition costs, and churn over a single cohort and across cohorts.
Here’s how we conduct the analysis:
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