A note on confidentiality. This client is under NDA. The industry, scope, and outcomes are accurate. Names and identifying details have been changed.
The challenge
A grassroots community operation was running an 83,000-person Facebook community, an 11,000-subscriber newsletter, and 21,000 monthly website visits — entirely by hand. Every lead from a Meta ad was being manually copy-pasted from the ads dashboard to a spreadsheet, then to a personal WhatsApp conversation, then to a follow-up email thread. The bottleneck was the founder's time, and the cost was that high-intent people were being contacted days after they raised their hand, not minutes.
They did not have a CRM and did not want one. They had a team of volunteers, not a marketing ops function. The solution had to be invisible to the community itself and completely operable by non-technical people.
What we did
We built a lightweight pipeline entirely out of tools the team already paid for or could add for nearly nothing: Make.com + Google Apps Script + WhatsApp + Google Sheets.
Lead capture pipeline
- A Make.com scenario that listens for new Meta ad leads and writes them to a master tracker in Google Sheets within seconds
- Routing logic that tags each lead by campaign, interest, and language
- Automatic personalized follow-up messages sent to WhatsApp inside minutes, not days
Master tracker and governance
- A Google Sheets master tracker that functions as a lightweight CRM, with status logic, a dashboard, and COUNTIF-based reporting for the volunteer team
- Family/contact folder management in Drive, created automatically per new contact
- Multiple intake forms (open day, trial day, registration) feeding into the same master tracker
Handoff
- Full documentation for the volunteer team in plain language
- A runbook for when something breaks, written so a non-technical volunteer can fix it
The outcome
The manual work is essentially gone. Leads are contacted within minutes of raising their hand. The team's time is reinvested in the work that actually matters to the community, not the mechanical work of moving data between tabs. And the same pipeline was later reused when the organization applied for (and received) a grant, because the infrastructure was finally legible to an outside reviewer.
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