Predict customer churn risk and generate retention plans with timelines.
npx skills add https://github.com/huifer/Shopilot --skill churn-predictor
Please help me install this Agent Skill. Skill: churn-predictor Source: https://github.com/huifer/Shopilot/tree/main/skills/churn-predictor Command: npx skills add https://github.com/huifer/Shopilot --skill churn-predictor
This skill helps businesses predict customer churn, analyze root causes, and prescribe actionable retention strategies to reduce churn and increase lifetime value.
Given a single customer's data, output 90-day churn risk, main reasons, and a tailored retention plan.
High-intent search queries and answers about installing and using this skill.
To predict customer churn risk, input purchasing activity, interactions, satisfaction, and competitor signals to generate a 0-100 risk score, risk category, probable reasons, and recommended retention actions with timelines.
Early warning signals of customer churn include reduced purchase frequency, lower engagement, and unresolved complaints. Analyzing these signals helps detect risk trends and prescribe proactive retention strategies.
Yes, you can apply batch risk scanning to analyze multiple customers simultaneously. This process profiles datasets to output individual 0-100 churn risk scores, categories, and tailored retention recommendations.
Calculating a 90-day churn risk score requires customer data integration covering purchasing activity, interactions, satisfaction levels, and competitor signals to accurately forecast risk and generate retention plans.
Root cause analysis for customer retention identifies and prioritizes the specific reasons behind churn risk, such as unresolved complaints or reduced engagement, enabling targeted short, medium, and long-term retention actions.
The best way to prioritize retention actions is by using the generated 0-100 churn risk score and category to evaluate ROI, prescribing tailored short, medium, and long-term actions based on probable churn reasons.
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