Scoring 302 Meta ads with Jev across 9 dimensions
A team scraped 2,000 ads from 8 beauty brands and used Jev to grade 302 of them across 9 dimensions including hook, CTA and claim risk, for a total cost of $0.0167.
We just cracked how to make a great Meta ad using Jev ( a classifier model from TypeSafe AI. ) We pulled around 2,000 real ads from 8 beauty brands off Meta’s Ad Library and graded 302 of them with Jev across 9 dimensions: hook, format, funnel stage, CTA, claim risk and boldness. Jev is an AI evaluation tool from TypeSafe AI that lets you run the same structured review across hundreds of inputs. The best ad in the entire set was a drag performer climbing 300 stairs to see if her makeup survives, for e.l.f. Cosmetics. She puts the makeup to the test by climbing the stairs, and that’s the ad. Jev scored it 3.86 out of 5 on boldness, the highest of all 302. UGC and testimonial-style ads like that one came out on top across the whole category too, averaging 1.63 out of 5. Catalog and generic-style ads sat at the bottom, averaging 0.48. Same brands ran both kinds in many cases. The format was doing most of the work. We scraped everything with Apify ( free 5 usd plan ) , ran each ad through Gemini ( free tier ) so we could read the creative instead of only the caption, then judged it with Jev. 2,718 judgments total. Cost us $0.0167. If you’re running ads for anything in e-commerce, you could run this process on your own category before your next shoot. Grading 302 ads by hand would take a week. This took an afternoon and less than two cents. At @shoposai, we help hundreds of brands make their performance-marketing stack agentic. DMs are open if you want a free consultation.
This post quotes another post: “ChatGPT co-inventor releases Jev, a model built for decisions rather than text”