ChatGPT Visibility Audit: How to Check If AI Recommends Your Products

Most e-commerce brands have no idea how their products appear in ChatGPT shopping recommendations — because their analytics tools don't measure it. A ChatGPT visibility audit closes that gap, showing you exactly which products appear (and which don't) when shoppers use ChatGPT for product discovery.

Why does ChatGPT visibility matter for e-commerce?

ChatGPT is the most widely used AI assistant for product research and discovery. Surveys consistently show 30–40% of shoppers now use AI assistants for product research before buying — and ChatGPT leads in market share. For high-consideration purchases (furniture, electronics, fitness equipment, professional tools), the proportion is even higher.

If your products don't appear in ChatGPT's recommendations for your category's key shopping queries, you're invisible to a significant and growing portion of your potential customers. The visibility audit quantifies exactly how invisible — and where the gaps are.

What does a ChatGPT visibility audit involve?

A structured ChatGPT audit tests four prompt types per product:

1. Category recommendations: "What are the best [product category] options?"
2. Use-case matching: "What [product type] is best for [specific use case]?"
3. Attribute queries: "Which [product type] has [specific feature or specification]?"
4. Comparison prompts: "How does [your brand] compare to [main competitor]?"

For each prompt, the audit records: was your product mentioned? At what position? In what context? What competitors were mentioned instead? The pattern of misses and hits reveals the specific content gaps causing your invisibility.

How does OpKart run a ChatGPT visibility audit?

OpKart automates the full audit — 25 prompts per product, run across ChatGPT, Gemini, and Perplexity simultaneously. Connect your Shopify or WooCommerce store (or upload a product CSV), and OpKart generates visibility scores for each product within minutes. The results show which products are invisible, which prompt types they're failing, and what content enrichment would address each gap.

What do you do after the audit?

The audit output is a prioritised content improvement roadmap. Products with low scores on use-case prompts need better use-case coverage in their descriptions. Low scores on attribute prompts indicate missing or buried specification data. Low scores on comparison prompts suggest positioning gaps. Each gap type has a specific fix — and OpKart's enrichment tool generates the improved content directly from the audit results.

Conclusion: your first audit takes minutes and reveals your AI revenue gap

Most brands that run their first ChatGPT visibility audit are surprised by how low their scores are — and by how large the gap is between their most and least visible products. That gap is the AI revenue opportunity. The audit makes it concrete, the enrichment closes it, and the monitoring tracks whether it stays closed.