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Adoption rate

As explained in Natural Language Processing in Action, Second Edition

Feature adoption rate is the proportion or number of users who use a particular product feature.

Feature adoption rate measures how many users use a particular feature. In chatbot analytics, it belongs to HEART’s adoption family and relies on trackable user events. section 12.7.3

Evaluating a new chatbot feature

A math tutor chatbot can track how many students use a new question-answering or LLM capability. Comparing that usage with the feature’s maintenance cost provides an approximate A/B test without randomized feature switching. section 12.7.3

Choose the event that represents meaningful use rather than counting every signup:

  • Count students who proceed through several chatbot messages when interaction matters more than subscription. section 12.7.3
  • Use event tracking to record starts, questions, thanks, or feature interactions, depending on the improvement target. section 12.7.3

How Natural Language Processing in Action, Second Edition covers it

How deep it goes
Defines the metric, distinguishes meaningful interaction from signup, and connects usage tracking to approximate A/B testing.
Examples
Uses math tutor chatbot signups, message interactions, and a new question-answering or LLM feature.
What it assumes
Assumes trackable user events and teaches why signups may be weaker evidence than interaction.
What you can do after
Evaluate feature popularity and maintenance value by selecting meaningful events and comparing resulting usage.
How it connects
Connects adoption metrics with HEART, event tracking, chatbot analytics, and A/B testing.

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This explainer was generated by Manning's knowledge graph from the text of Natural Language Processing in Action, Second Edition. The section links point to the parts of the book it draws on.