shop-retention-report
Analyze auto-repair shop CRM, customer, invoice, and service history for retention, repeat visits, customer cohorts, recency/frequency, average repair order or revenue per visit, declined-work recover
Files3
View on GitHubSKILL.md.claude/skills/shop-retention-report/SKILL.md
GitHubShop Retention Report
Find where existing customers create durable value and where the shop is quietly losing repeat business.
Workflow
- Establish exact reporting period, history window, customer deduplication rules, invoice status definitions, and available fields.
- Clean identity carefully before cohort analysis. Account for duplicate customer records, multiple vehicles, shared households, changed phone/email, and canceled/voided invoices.
- Build core cohorts where data supports them:
- new vs returning customers
- one-and-done customers
- 2+ visit repeat customers
- dormant/lapsed customers by recency bands
- tire-only vs service-only vs mixed customers
- declined-work cohorts
- Analyze economics:
- completed visits/jobs
- revenue and average revenue/repair order where valid
- visits per customer
- time to second visit
- repeat revenue share
- service/tire category mix
- Analyze retention behavior over comparable cohorts rather than raw repeat-customer counts alone. Recent cohorts may not have had enough time to return.
- Audit declined work and follow-up when available: value declined, age of opportunity, eventual recovery, and categories most likely to convert later.
- Look for operational leakage: duplicate CRM records, missing contactability, poor follow-up, capacity delays, inconsistent recommendations, or review-request gaps.
- Tie actions to measurable outcomes such as second-visit rate, reactivation rate, recovered declined work, visit frequency, ARO/revenue per customer, and review conversion.
- Read
references/report-contract.mdand follow its output structure.
Rules
- Do not call a new customer "lost" before a reasonable return window has elapsed for the service category.
- Do not use revenue alone as retention proof; mix and price changes can move revenue without better retention.
- Separate customer-level, vehicle-level, and invoice-level metrics.
- Never expose unnecessary customer PII in the report.
- State deduplication assumptions because duplicate CRM records can materially distort retention.
Useful triggers
Examples: "run retention", "how many customers come back?", "audit declined work", "which customers are going dormant?", "is tire traffic turning into service customers?"