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churn

4 articles

Retention Isn't a Feature Problem
Opinion retention churn

Retention Isn't a Feature Problem

Retention isn't a feature problem. It's a context decay problem that AI product teams solve by building persistent user memory, not by shipping more capabilities.
Robert Ta's Self-Model
Robert Ta's Self-Model
· 8 min read
How Churn Prediction Misses Belief Drift
Research churn retention

How Churn Prediction Misses Belief Drift

Traditional churn prediction models track behavioral signals like login frequency and feature usage. They miss the deeper signal: belief drift. The slow erosion of a user's confidence that the product understands and serves them.
Robert Ta's Self-Model
Robert Ta's Self-Model
· 14 min read
Why AI Products Churn Faster Than SaaS
Opinion churn retention

Why AI Products Churn Faster Than SaaS

AI products lose users 2-3x faster than traditional SaaS. The reason is not feature gaps or pricing. It is that AI products promise intelligence but deliver amnesia, and users leave when the product never learns who they are.
Robert Ta's Self-Model
Robert Ta's Self-Model
· 12 min read
Why Your AI Forgets Users After 90 Days
Deep Dive personalization retention

Why Your AI Forgets Users After 90 Days

Most AI products lose user context within 90 days, driving churn. Self-models create persistent memory that compounds over time instead of decaying.
Robert Ta's Self-Model
Robert Ta's Self-Model
· 14 min read

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