The true cost of a churned customer is not just the loss of revenue, it’s the loss of the company’s reputation within that churned customer’s community.
If you churn 100 customers, you don’t just lose 100 customers - you’ve lost 100 communities.
If you churn enough customers, the aggregation of their respective communities can crowd out significant portions of your addressable market.
Churn can therefore exponentially narrow your total addressable market (TAM). Yes, you’ve lost revenue with churn, but more importantly, you’ve lost market opportunity.
Winning back a customer, in the same vein, means winning back your reputation within a community. Winning back communities means expanding the addressability of your market.
It’s easy when a company is small to grow through churn by simply acquiring more new customers. You can get comfortable adding net new customers every month as the company grows nicely. Churn doesn’t seem like a significant problem.
However, when the company grows to many times the size, what has also grown many times the size is the aggregate number of churned customers and commensurately the aggregate number of lost communities.
Then one day when the company is at a much larger scale, the remaining available market is deceptively small, and the company’s reputation is defined more by the aggregate lost customers than the current active customers. This is when companies that once grew aggressively reverse course and at best, become stagnant, and at worst, shrink in size.
Therefore, it is essential to mitigate churn in the first place, but secondly it is important to have dedicated resources and intentional efforts to win back churned customers. It is absolutely critical to develop the playbook to accomplish both when the company is smaller. The benefit of those efforts will meaningfully compound as the company scales.
Thinking about the patterns that generally occur at every major technology shift:
- bricks & mortar to e-commerce
- on-premise to cloud
- landline to mobile
- information age to artificial intelligence
- others…
Some recurring patterns that come to mind:
1. Operators embedded in the old model underestimate the impact of the new model.
2. While actual adoption of the new model is faster than the old model operators think, it’s slower than aspirational VCs think who start pouring capital in too early.
3. Capital flows to the new paradigm inflating multiples in the new model and deflating multiples in the old model, even if financial performance is comparable.
4. Market value erosion of old model companies happens quickly even if market adoption of new models is more moderate.
5. Certain companies/industries/even countries that were slower adopters of the old model skip it and jump to the new model.
6. Eventually, decades later, we realize we originally underestimated the level of change in how we live and work caused by each major technological shift.
Thoughts? What am I missing?