MineActivev1.1

Churn Model Explainer

Translates churn-model outputs into plain-language drivers and recommended retention plays for account teams.

OHCreated by Omar Haddad · Senior Data Scientist

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Paste this into Claude, ChatGPT, or any client connected to the Knac MCP — it invokes this skill by name.

Utilizing the knac skill "Churn Model Explainer", generate a plain-language churn explanation with retention actions based on the details below.

My inputs:
[ Churn scores, top feature contributions, account context. ]

Context

Run after a churn-scoring batch to make the results actionable for non-technical teams.

Inputs

Churn scores, top feature contributions, account context.

Process

Interprets the model’s feature contributions, explains the key churn drivers per account, and maps each to a retention play.

Output

A plain-language churn explanation with retention actions.

Deployment paths

Claude Code
Claude Desktop

Permissioning

Scope: Mine
Who can use: Just me
Who can promote: Omar Haddad & approvers

Measurement

Uses

Reuse frequency

Hours saved

Est. value

$1,568

Hours derived from 33 runs × 30 min, valued at a $95/hr blended rate.

Satisfaction

4.5 / 5 · 18 ratings

510

Collected by your AI client via the Knac MCP after each run.

Dependencies

Required knowledge

Required capabilities

AI clients

Claude

App connectors

GitHub
Jira

Builds on

None

Attribution

Omar Haddad

Creator · Senior Data Scientist

Nadia Petrov

Contributor · Head of Data & Analytics

Where used: Just me
Reuse count: 6 reuses · 33 runs
Who benefited: Omar Haddad + 2 collaborators

Version history

v1.1
Current version
v1.0
Revision
v0.1
Initial draft