ecommerce-customer-retention
Skill846 starsChanged 7 months agoMITView on GitHub
Increase customer retention and repeat purchases for e-commerce businesses. Email flows, loyalty programs, subscription models, customer segmentation, and win-back strategies. Ask your AI agent: Structured recommendations with actionable steps, benchmarks, and platform-specific guidance. Built by Nexscope — AI-powered e-commerce tools for sellers worldwide.
In this repository141 other files it gives its agents.
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- The first 60 shown.
The file
We split this skill into the rules it gives an agent
1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 24
Ask your AI agent:
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
E-Commerce Customer Retention
Increase customer retention and repeat purchases for e-commerce businesses. Email flows, loyalty programs, subscription models, customer segmentation, and win-back strategies.
Capabilities
- Customer retention metrics and benchmarking (by industry)
- Post-purchase email and SMS flow design
- Loyalty and rewards program setup
- Subscription and auto-replenishment models
- Customer segmentation: RFM analysis
- Win-back campaign strategy for lapsed customers
- Review and referral program integration
- Customer lifetime value optimization
Install
npx skills add nexscope/ecommerce-customer-retentionUsage
Ask your AI agent:
- "Build a customer retention strategy for my Shopify store."
- "Design a loyalty program for my beauty brand."
- "Create win-back email flows for customers who haven't purchased in 90 days."
Output
Structured recommendations with actionable steps, benchmarks, and platform-specific guidance.
Built by Nexscope — AI-powered e-commerce tools for sellers worldwide.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
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Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

