Solutions
Eye for Commerce
Track how answer engines recommend products, categories, and retailers—then close the gaps with citation-driven insights.
Outcomes teams care about
Eye turns model behavior into visibility, citations, and concrete next steps you can validate.
Win product recommendations
Measure mentions and relative position in product and category prompts.
Understand retailer visibility
See which domains and sources get cited when models recommend where to buy.
Spot competitor advantages
Identify the brands and narratives that consistently outrank you.
Validate content & site changes
Re-run prompt sets after updates to confirm lift and stability.
What you’ll actually do in Eye
Use a small set of repeatable workflows that keep the depth while staying easy to act on.
Build a purchase-intent prompt set
Cover comparison, “best for”, availability, and price-related questions.
Track citations by domain
See which sources influence recommendations and where citations concentrate.
Find gaps by query
Surface where competitors appear and you don’t, and prioritize by impact.
Monitor sentiment & claims
Catch inaccuracies about pricing, features, or availability early.
Export for teams
Share findings with content, SEO, PR, and ecommerce teams.
Use Prompt Lab to test positioning
Try different product narratives and see how models respond.
See the depth you get—without the clutter
Drill down from charts and tables into evidence, sources, and changes across runs.
Platform comparison
Compare recommendation behavior across engines for the same purchase-intent prompts.
Share of voice
Track how often you’re recommended vs competitors across platforms.
Sources driving recommendations
See which domains models cite when recommending products and retailers.
Competitive matrix
Spot pressure by competitor and topic, then drill into evidence.
Ready to see how AI represents you?
Create a project, add prompts, and start measuring visibility across answer engines in minutes.