AVS analyzes individual e-commerce product pages to identify what may prevent AI platforms from understanding, comparing, and recommending your products. Get a product-level readiness score, uncover content and technical gaps, and receive prioritized recommendations to improve your AI visibility.
Hey Product Hunt š
We built Agentic Visibility Score (AVS) around a question we kept coming back to:
If a shopper asks an AI assistant what product to buy, is your product page giving that AI enough information to understand and recommend it?
Great SEO tools already exist, and a growing category of platforms tracks brand visibility across AI. But we saw an opportunity at the individual product/SKU level.
So we built AVS.
Give AVS an e-commerce product URL, and it analyzes the product's AI readiness across buyer-prompt coverage, product content, structured data, technical signals, imagery, and other recommendation-readiness factors.
You get a 0ā100 AVS score, platform-specific readiness insights, gaps, and prioritized improvement recommendations.
One thing that's important to us: AVS does not claim that a high score guarantees an AI platform will recommend your product. The score measures how well prepared the product is against the signals AVS can evaluate.
This is also just Step 1 of what we're building. Next, we're working toward tracking actual AI visibility across prompts, competitors, and citations, followed by ongoing monitoring and business-impact measurement.
We'd love the Product Hunt community to try AVS with a real product page.
In particular, we'd love feedback on:
⢠Does the score make sense?
⢠Are the recommendations actionable?
⢠What would you want AVS to analyze next?
Thanks for checking it out! š