The first run targeted a D2C consumer category. Seeding Ninja identified 13 competitors, mapped their positioning, and pulled collaborator data across all of them. This is what 48 hours of automated research produces.
The system surfaced a pattern across every brand it analyzed: strip the top 5 posts from any influencer program and the median drops to 100 to 500 likes. A tiny cluster of creators drives disproportionate results. Find that cluster and you've found the real growth engine.
Cameron Brink, Jessica Pegula. 23% of posts generate 45% of engagement. Remove the athletes and the program is noise.
@page.soobin. One post. 1.08M likes. A single creator produced a quarter of the entire 2,000 post program.
@simlynail, @thenaillologist. 4.8% of posts, nearly 38% of engagement. A 921 person roster depending on two creators.
Seeding Ninja combines deep research with Modash API data to map any D2C category. Not a one-off analysis. A repeatable system.
Every analysis runs through structured adversarial review. The findings get challenged from four angles before anything ships. If the strategy breaks under pressure, better to find out here.
"If the brand story feels constructed, real customers can tell within two seconds. Does this pass the sniff test?"
"Established players have bigger distribution and deeper pockets. The strategy has to hold when they react."
"Beautiful brands die every quarter. Show cohort retention before showing the influencer plan."
"A strategy that only works for one demographic is a strategy that doesn't scale. Test it across segments."
Point it at a category. Get the competitive picture in 48 hours. Seeding Ninja identifies competitors through multi-source research, pulls their full influencer collaboration history through Modash, and surfaces which creators actually drive growth.