How to Value a Company by Analyzing Its Customers

Of course, few companies will have such simple models and neat patterns as our meal-kit example. Our purpose here is to outline the general mechanics of the approach, as extensions of it follow naturally. Suppose, for example, that your firm has tiered pricing (it also offers a second plan that delivers twice as many meals a month for $189). In that case, you would need to account for variable ARPU from period to period. If the firm allows customers to skip deliveries or make discretionary purchases, you would need to track order frequency and average spend per order. If the firm pivots to sell meals à la carte instead of on a subscription basis, you’ll need to use a model that predicts how often customers will place orders. These extensions add complexity to the model, but the basic process to incorporate them would be the same as in the example above. If you want to extend the time horizon beyond month five, you can repeat the calculation for multiple months. That gives you a long-term revenue forecast, which is vital for corporate valuation.

For an in-depth discussion of the CBCV methodology in complex scenarios, see our academic papers “Valuing Subscription-Based Businesses Using Publicly Disclosed Customer Data” (Journal of Marketing, October 2016) and “Customer-Based Corporate Valuation for Publicly Traded Non-Contractual Firms” (Journal of Marketing Research, March 2018).

Looking at Customers from Inside and Outside

The richness of the insights that can be derived from CBCV depend on how much access the person performing the analysis has to internal company data. A corporate executive would have full visibility of all customer data. A private equity investor assessing an acquisition target would typically have access to transactional and CRM data. For subscription firms, that would include the length of contracts, periodic payments, and observable churn; for nonsubscription firms, it would include the timing and size of each individual purchase. Access to other behavioral data, demographics, marketing touchpoints, service interactions, and the like would further enrich the CBCV analysis.

For those on the outside looking in—hedge funds, Wall Street analysts, regulators, and others—detailed customer data might be impossible to obtain on a regular basis. They may, however, have access to the firm’s customer cohort chart, or C3, which tracks revenue by acquisition cohort over time and shows how total customer spending changes as each cohort ages. (For an example, see the exhibit “C3: A New Tool for Corporate Valuation.”) Many large, reputable firms (both subscription and nonsubscription) have begun to disclose their C3, among them Slack Technologies, Dropbox, Lyft, and luxury marketplaces the RealReal and Farfetch. A firm’s C3, along with the number of active customers and the total number of orders, is sufficient to give investors a good understanding of customer behavior.

If a firm can’t or won’t release its C3, investors should press it to reveal four key metrics: the number of active customers (in total and the percentage from tenured customers, or customers who have been with the firm for over 12 months); gross acquired customers over the most recent period; revenue (total and percentage from tenured customers); and the number of orders (total and percentage from tenured customers).

While we would strongly encourage firms to disclose more, having three or four years’ worth of these disclosures (from past filings) is enough to run a CBCV model and assess the overall health of a company’s customer base, albeit with greater uncertainty about future revenues.

Trending Toward Transparency

Few companies currently provide all the data outsiders need to perform CBCV, for a variety of reasons. First, disclosure of customer metrics is voluntary, and companies feel little to no pressure to make them available. Second, there is little consensus about which customer metrics are the most informative and how those metrics should be calculated and reported. And finally, policy makers and regulators have been largely silent about these issues, leaving disclosure to companies’ discretion.

Unfortunately, executives often have a “less is more” mentality regarding disclosure. They fear that additional disclosure, however aggregated the numbers may be, could put them at a competitive disadvantage or open them up to potential litigation or regulatory scrutiny. Successful firms worry about how investors will react if the metrics they’re disclosing start going in the wrong direction. And customer-level forecasting often remains siloed in the marketing department; managers in finance and related functions are unaccustomed to incorporating customer behaviors in their revenue forecasts and are more comfortable using traditional methods.

In the absence of investor pressure and regulatory standards, firms can arbitrarily choose which metrics to disclose, generally selecting those that paint an overly rosy picture for the investment community. The metrics are often defined improperly, based on faulty assumptions, or framed incorrectly.

Consider Peloton, which sells high-end home-exercise equipment and monthly subscriptions to streaming-video fitness classes. When it filed its pre-IPO S-1, in August 2019, it chose to disclose its customer lifetime value (CLV) per subscriber, boasting a CLV of $3,593 in its most recent fiscal year. To its credit, Peloton also disclosed the underlying formula it used to compute its CLV, but that formula left much to be desired. The most glaring problem was that it did not account for the time value of money, and instead simply added more than 13 years’ worth of future cash flows without discounting them. Applying even a modest discount rate would slash its CLV by more than 50%—a drop with significant implications for the health of the customer base. As more firms voluntarily disclose customer metrics, analysts must be vigilant about vetting data that may be misleading or is mostly window dressing.

Although Peloton’s metrics are far from perfect, they nevertheless represent an encouraging shift toward transparency around customers that will be good for shareholders, companies, and customers. Shareholders will increasingly rely on customer data to evaluate potential investments as more purchases are made online and traditional brick-and-mortar metrics, such as same-store sales, decline in relevance. Executives can use customer data to build the case for investing in activities that will generate long-term value for the firm and to communicate to shareholders the impact of those investments on CLV and other long-term metrics. Customers will be treated as strategic assets whose value should be cultivated over the long term. This mindset will be a welcome change from the status quo, in which shareholders, lacking the information needed to assess long-term customer profitability, compensate by pushing firms to hit short-term performance measures.

Until the CBCV revolution fully takes hold, what does all this mean for you? If you are an investor, don’t ignore the customer-related metrics that may be tucked away in financial reports; actively seek them out. If the data you need isn’t disclosed, demand it, or find alternative sources that can serve as effective proxies. Focusing on unit economics will almost certainly reveal opportunities you can exploit.

If you’re an executive and you aren’t currently disclosing your customer metrics, start thinking about the story they would tell if disclosure were required. If you would not be proud of your metrics as they stand, this is your golden opportunity to refocus on and improve the health of your customer base in the dark. It may not be long before market participants demand sunlight.