Feature adoption rate feature stickiness

Features used by customers are scored for adoption rate to identify must-have vs niche.

CA clean typed decision with low volume or low value, or too vague to act on.3.29

Key facts

Vertical
Software & tech
Function
Other
Status
Seen in the wild
Volume
occasional
Value
meaningful
Risk
moderate
Evidence
described plan
Flags
check-fit

Source: https://www.getmonetizely.com/articles/understanding-churn-prediction-a-critical-metric-for-saas-success

Build this with a classifier

Define a typed decision with a bounded answer, then evaluate it on examples.

{
  "decision_type": "choice",
  "question": "Does this input match the decision in “Feature adoption rate feature stickiness”?",
  "input": "<input to classify>",
  "output": "one label from a fixed list"
}

Related use cases

Cite this

Copy a link in your preferred format.