AI visibility for E-commerce
Get recommended when shoppers ask AI what to buy
Shoppers increasingly open ChatGPT or Perplexity instead of Google to find products. If your store isn't cited in those answers, you don't exist in the purchase moment. Citedly tracks the product-discovery prompts your customers actually ask and shows you exactly where you rank — and which competitor the AI picked instead.
The prompts your customers actually ask
These are the question patterns that drive AI recommendations in e-commerce. Track them and you'll see exactly when you're in the answer — and when you're not.
- Best [category] under $[price]
- [product] alternatives to [competitor]
- Is [brand] worth it vs [competitor]?
- Where to buy [product] online with fast shipping
How Citedly works for E-commerce
- 1Audit. The free deterministic audit checks the factors engines rely on in e-commerce — llms.txt, schema.org, entity consistency, crawlability and content structure. No AI cost.
- 2Track. Paid plans run your e-commerce prompt set across ChatGPT, Perplexity, Gemini and Claude daily, recording mention, citation, position and sentiment per answer.
- 3Win. Watch share of voice against the competitors you name, get alerted when your position drops, and prove the lift with reports.
E-commerce FAQ
Do AI engines cite online stores?
Yes — especially when asked for product recommendations. ChatGPT and Perplexity link to stores with clear product pages, pricing, reviews, and structured data (Product schema). Citedly measures whether your store appears and is cited for the prompts that matter.
What makes a store more likely to be cited?
Clean product pages with Product schema, visible pricing, review signals, and an llms.txt that describes your catalog. Citedly's free audit checks all of these deterministically.
How often should I track?
Daily on Pro. Product recommendation answers shift as engines update their knowledge and as competitors publish new content.
See where your e-commerce brand stands
Run the free audit on your domain, or generate a spec-compliant llms.txt in 30 seconds.