Repeat-channel economics
The effect an automated interaction has on whether the customer will choose automation again — the future-facing half of AI customer service ROI that session metrics miss.
Repeat-channel economics asks what this contact did to the probability that the customer will choose automation again. A failed automated interaction can change the channel a customer picks next time. If it does, the cost of that failure is not the cost of one bad conversation; it is every future contact that now goes to a more expensive channel.
This is why a chatbot can be borrowing from the next interaction: the apparent saving today is financed by a weaker channel tomorrow.
In practice
Treat it as the second horizon of the ROI model, next to session economics. Measure it with the return-to-automation rate, watch it when automation scope expands, and let it justify giving up earlier when a case is unlikely to succeed. That deliberate escalation is channel preservation.
An ROI model that has no memory of what happened last time will keep rewarding interactions that hurt the next one.
Read more in Your chatbot is borrowing from the next interaction.
Related terms
Session economics
The cost and outcome of a single customer contact with an automated channel — what this interaction cost and what it resolved. It is the narrow, current-contact half of AI service ROI.
Return-to-automation rate
The share of customers who choose the automated channel again after an earlier automated interaction — a measure of how today's experience affects tomorrow's automation choice.
Channel preservation
Escalating or declining an automated interaction early, on purpose, to protect the customer's willingness to use the automated channel again — treating escalation as protection, not failure.