Who does it serve and what problem does it solve?
Scores come from real human votes rather than AI, and voting earns free ratings, creating a mutual-rating loop
Target Audience
People choosing LinkedIn headshots, social profile pictures and dating app photos
How does it charge?
per itemFree (vote on others' photos to earn credits for your own ratings); $9 one-time for 40 credits, $19 for 100 credits (later tiers truncated in the input)
The above describes historical pricing. Check official website for current prices.
Where do users come from?
Direct 80.8%, search 17.8% mostly brand keywords (brand keywords 91.5%), with non-brand long tail such as "websites where women rate men" and "youtube profile picture size"; AI referrals 0.7% (Gemini, ChatGPT). Social is Reddit, YouTube and X. Returning users come back to vote on others' photos to earn credits and to test new photos.
Channel share, initial acquisition, and growth drivers are distinct; correlation does not imply proven causation.
What remains to be verified?
The following are research questions, not established market opportunities.
- What do target users actually pay for? Is there direct user feedback or paid interview evidence?
- Are these historical prices still active today? What are the conversion, retention, and fulfillment costs?
- Is the "SEO" channel still viable? What resources do indie devs need to test it?
- Whose needs are competitors failing to meet? Find specific evidence before deciding on your angle.