Vampt Vintage Design
Vampt AI marketing & data clean-up
A vintage design store had a contact list it couldn’t safely email and a relocation to promote. I cleaned the data with AI, fixed the consent problem, and built an AI marketing pipeline that keeps learning from its own results.
- Outcome
- 10,000+ contact records cleaned, an ACMA Spam Act issue resolved, and an AI marketing pipeline that lifted sales.
- Role
- Adviser and hands-on builder: marketing, data and automation
- Team
- The owner and staff
- Timeline
- 2026 – present
- Methods
- AI-assisted data cleaning · consent recapture · Zapier and Mailchimp automation · analytics review
- Deliverables
- Cleaned contact list and consent process · AI marketing pipeline
- Skills
Data clean-up and consent
The store’s contact list had an ACMA Spam Act issue. I advised on the fix and did the work:
- Cleaned 10,000+ contact records with AI tools.
- Set up consent recapture, so the store could keep emailing the people who wanted to hear from it.
- Resolved the Spam Act issue, leaving a list the store can use with confidence.
An AI marketing pipeline
I built the pipeline on Zapier and Mailchimp. Each part feeds the next, and the results feed back into the content.
How the pipeline runs
- Brand-voice writing toolsTrained on the store’s long-standing tone
- Generated email graphics
- Automated send flowsZapier and Mailchimp
- AnalyticsWhat worked, and what didn’t
↺ Analytics feed back into the writing and graphics, so the content improves with each send.
The relocation
I also ran marketing for the store’s relocation and grew its audience along the way.
Reflection
Fixing the data came first: a pipeline is only as good as the list it sends to, and only legal if people have consented. With that in place, automation let a small store market consistently in its own voice.