Your Average Revenue Per Customer is Meaningless

A friend's startup experienced a significant increase in average revenue per customer, jumping from $230 to over $600, primarily due to acquiring a large client rather than changes in pricing or upselling. This situation illustrates that average revenue per customer can be misleading, especially in businesses where revenue follows a power law distribution rather than a normal distribution, as seen in datasets like the weights of pandas or SAT scores. Such businesses often see a small fraction of their customer base accounting for a large portion of their revenue, highlighting the importance of examining the overall revenue distribution rather than relying solely on averages. For companies whose revenue does not yet follow a power law, factors like a small customer base or suboptimal pricing models that fail to capture the full value provided could be at play. Businesses are encouraged to adopt value-based pricing to optimize revenue capture from high-value customers while recognizing that much of their revenue and customer interactions, such as support tickets and feature usage, may be concentrated among a few key clients. Understanding these dynamics can lead to better business strategies and decision-making.

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