Membership Save Agent
Catches members drifting toward cancellation before they actually cancel.
Every week, this agent pulls your membership visit data and flags two kinds of risk: members whose visit frequency has quietly dropped off (a weekly washer who hasn't been in for three weeks) and members whose payment just failed. For usage-drop members, it drafts a warm, specific check-in — not a discount blast, a genuine "haven't seen your car in a while, everything okay?" For failed payments, it drafts a friendly card-update reminder before the account auto-suspends. Both go to you or your manager to review and send. What used to be "we noticed our member count dropped again" becomes a weekly list of specific people to reach while there's still time to keep them.
What this agent takes off your plate
- Usage-drop members get a personal check-in before they quietly cancel, not after
- Failed-payment members get a friendly reminder before auto-suspension, recovering revenue that would otherwise just vanish
- A weekly, specific list of at-risk members instead of a monthly surprise in the churn report
- Win-back messages that read as genuine care, not a discount-code blast
- A running log of save attempts and outcomes so you know what's actually working
The stack
Real costs & ROI
- Claude Pro or ChatGPT Plus$20/moneeded for the weekly automated run plus normal day-to-day use
- Make.com Core plan (or Zapier Starter)$9/mothe free tier's ~100 tasks/month is tight for a weekly multi-step flow across a few hundred members; Make's Core plan starts around $9/mo
- Email or SMS sending (OpenPhone, Mailchimp free tier, or your POS system's built-in messaging)$0–10/momany membership/POS platforms already include messaging at no extra cost
The math
Losing a member costs more than it looks like on paper — a $25/month member who cancels is $300/year gone, and replacing them costs real marketing spend to acquire a new one. Pull your own churn number from your platform and split it into "cancelled on purpose" and "card failed and nobody caught it" — the second bucket is usually bigger than owners expect. If a 500-member site is losing even 15 members a month to failed payments alone, that's $375/month in revenue disappearing for a reason that has nothing to do with whether the member wanted to stay. Catching even half of those failed payments before auto-suspension recovers $180+/month — more than covers the $20–40/mo cost of running this agent, before counting any usage-drop saves on top.
Build steps
Define what "at risk" actually looks like for your site
Before automating anything, decide what counts as a usage drop worth flagging. This alone clarifies who you should be worried about today.
Data you need
Pull your last 90 days of member visit data if your POS/RFID system tracks it — member name, tier, typical visit frequency, and visits in the last 30 days.
I run a car wash with an unlimited membership program and I want to define what "at risk of cancelling" actually looks like using my real data. My membership tiers and typical visit patterns: [DESCRIBE — e.g. "Basic members average 2 washes/month, Plus members average 4, Premium members average 6"] Here's a sample of recent member visit data: [PASTE OR DESCRIBE — member, tier, visits in last 30/60/90 days] Please help me define: 1. **A usage-drop threshold per tier** — e.g., a Plus member (usually 4x/month) who drops to 0–1 visits in 30 days is at-risk; a Basic member (usually 2x/month) has a different threshold 2. **A "new member grace period"** — members in their first 30 days shouldn't be flagged the same way; they're still forming the habit 3. **A seasonal adjustment note** — winter/rain-heavy months naturally reduce visits; the threshold should account for expected seasonal dips, not just raw numbers 4. **A payment-failure risk category** — separate from usage drop entirely; this is about a failed charge, not disengagement 5. **A weekly risk list format** — member name, tier, risk type (usage drop / payment failure), days since last visit or payment attempt Save this as my risk-definition reference — every future prompt will use these thresholds.
Connect your membership data feed
Give the automation a weekly pull of visit and payment status data to work from. Be realistic about the source first: none of the main car-wash membership platforms has a self-serve Zapier or Make app, so this is a CSV-to-Google-Sheet feed, not a live integration. Source → Sheet → Trigger: - Rinsed: the closest thing to a live integration. It already syncs member and billing data from DRB and Sonny's and has its own declined-card and usage-drop lists. If you're on Rinsed, export those lists weekly (or just use them directly) and skip straight to drafting in Step 3. - DRB (Patheon / SiteWatch): run the member activity and recurring-billing reports, export CSV. Some setups can schedule the report to email; ask your DRB rep. Their API is partner-only, not something you wire up yourself. - Sonny's / ICS: same story — member usage and declined-payment reports export to CSV; no self-serve API. - WashCard: reports export to CSV from the back office. - Sheet: paste or upload the CSV into one Google Sheet tab named "members" with columns member, tier, visits_last_30, last_visit_date, payment_status, last_charge_date. If your platform emails the report, a Gmail "New Attachment" trigger plus Formatter "Import CSV" (Zapier) or a Gmail "Watch Emails" + "CSV Parse" module (Make) can load it automatically; otherwise it's a 5-minute Monday paste. - Trigger: Schedule by Zapier "Every Week" (Monday 6am) or Make's Scheduler, then Google Sheets "Get Many Spreadsheet Rows" (Zapier) or "Search Rows" (Make).
Data you need
You'll need back-office access to your membership platform's reports, a Google Sheet, and a Zapier or Make account. The manual part is honest: on DRB, Sonny's, and WashCard, someone exports a report once a week.
Agent Pack
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