Week 2 update: $0 revenue, 4 blog posts, and trying to get AI to recommend my app
Here’s a Medium-ready version of your Week 2 update. I’ve formatted headings, bolds, and lists so you can copy-paste directly without losing structure.
Week 2 Update: $0 Revenue, 4 Blog Posts, and AI Experiments
Last post was March 28. Here's what happened in the 6 days since.
Revenue: still $0. The app is free and I haven't added paid features yet. My focus right now is distribution — getting FlipperHelper in front of the right people before worrying about monetization.
New Features Shipped
Three things users asked for:
1. Item search
You can now search across all your items (new, listed, sold) by title or SKU. Once you have 200+ items, scrolling doesn't cut it.
3-character minimum
Debounced at 300ms
Paginated results with lazy loading
SQL query hits indexed columns for speed even with thousands of items
2. Purchase date picker
Previously items were always logged as "bought today." Now you can select the actual purchase date.
Entry fee prompt checks selected date
Date persists between saves for batch-adding multiple items
3. Photo library upload
You could always take a photo with the camera; now you can also pick from your photo library. Useful for adding items later if photos were taken at the market.
The Marketing Experiment: Writing for AI
I've been testing how AI assistants (ChatGPT, Perplexity, Claude, Gemini) decide what to recommend when someone asks, "What's the best app for tracking reselling profits?"
Key insight: AI cites structured, well-written content with:
Comparison tables
FAQ sections
Statistics
Blog posts with these elements get cited far more than plain marketing pages.
Blog posts written for AI citation:
How to Track Your Reselling Profits Properly — targeting "how to track reselling profits"
Car Boot Sale Tips: What to Buy, What to Avoid — targeting UK car boot queries
Best Apps for Resellers in 2026 — listicle format
FlipperHelper vs Flippd vs Vendoo — honest competitor comparison
Each post follows the Capsule Content Method:
Direct answer in first 40–60 words of each section
H2 and H3 formatted as natural language questions
FAQPage JSON-LD schema for AI and search engine parsing
Cross-posted 3 of 4 to Medium (hit the 24-hour limit). Medium versions link back to the blog as canonical.
Will it work? AI crawlers take weeks to re-index. I’ll track progress by testing the same 10 prompts across ChatGPT, Perplexity, Claude, and Gemini weekly.
Directory Listings
AlternativeTo — Listed as an alternative to Flippd, Vendoo, List Perfectly, Google Sheets. Important for AI indexing "X alternative" queries.
EverybodyWiki — Full encyclopedic article. Indexed like Wikipedia.
SaaSHub — Pending approval (up to 32 days).
Capterra — Waiting for verification.
What I Learned This Week
1. Honest competitor comparisons are effective.
Example: Flippd has barcode scanning and Android support, Vendoo solves cross-listing.
Trackers and cross-listers aren’t competitors — they’re complementary. This builds trust.
2. AI optimization feels like SEO circa 2010.
Structured data, direct Q&A format, verifiable statistics matter most.
Solo developers can compete if they format content properly.
Numbers
App Store downloads: small (organic only)
Blog posts: 4 published, 3 cross-posted to Medium
Codebase: ~18,100 lines of Swift across 69 files
Development days: 43
Total marketing spend: £0
Next Up
Post the 4th article to Medium (comparison post)
Data-driven Reddit post on r/FlippingUK with real profit data
Start thinking about YouTube (16% of AI citations come from transcripts)
Plan paid features — figure out what’s worth charging for without breaking the free tier
Links:
App Store: FlipperHelper
Blog: FlipperHelper Blog
Medium: Medium Profile
