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Churn Prevention

Checked
coreyhaines31·vlatest·marketing·MIT

Predicts customer churn by analyzing data, enabling proactive interventions to retain valuable clients and reduce business losses.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add coreyhaines31/marketingskills --skill churn-prevention -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

coreyhaines31

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned coreyhaines31/marketingskills at dda3841f0b.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
dda3841f0b
Manifest
skills/churn-prevention/SKILL.md
Scanned
4 files, 1,205 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

The churn-prevention skill helps identify and address factors that may lead to customer attrition. It analyzes user behavior, engagement patterns, and feedback to predict potential churn risks and suggests targeted interventions such as personalized offers or outreach strategies.

When to use it

  • When analyzing customer retention metrics to spot early signs of churn.
  • To develop proactive campaigns aimed at re-engaging disengaged users.
  • During quarterly reviews to assess the effectiveness of current retention efforts.
  • When preparing for product launches and identifying at-risk segments.

Key capabilities

  • Predictive analytics based on historical user data
  • Segmentation of customers by churn risk level
  • Generation of actionable insights and recommendations
  • Integration with CRM systems for targeted outreach

Example prompts

  • "Identify the top 10% of users most likely to churn in the next quarter."
  • "Generate a retention strategy tailored to disengaged SaaS users."
  • "Analyze recent user feedback to detect common reasons for attrition."

Tips & gotchas

  • Ensure your data includes sufficient historical engagement metrics for accurate predictions.
  • Combine this skill with other marketing tools for a holistic customer retention approach.