Most ecommerce owners lump "AI shopping" into a single category, but Perplexity, ChatGPT, and Claude each have meaningfully different architectures for how they find and recommend products. Understanding those differences matters because optimising for one does not automatically optimise for the others.
Perplexity: The Real-Time Search Engine
Perplexity is the most search-like of the three. When a user asks a shopping question, Perplexity runs a live web search, scrapes the top results, and synthesises an answer with citations. Its Perplexity Shopping feature goes further — it aggregates product listings, prices, and reviews from pages it has indexed.
The key implication for ecommerce stores is that Perplexity responds strongly to real-time signals. If your product pages are crawlable, have clear prices and availability, and are recently indexed, they can surface in Perplexity Shopping results even if your brand is relatively new. Structured data (specifically Product schema with offers and price) is particularly valuable here because Perplexity's parser uses it to extract key facts without needing to interpret your full page layout.
Blocking PerplexityBot in your robots.txt is a direct exclusion from this surface. Many stores do it accidentally via catch-all rules.
ChatGPT: Training Data + Live Browsing
ChatGPT operates differently depending on which mode a user is in. In standard chat (no browsing), it draws on its training data — which has a knowledge cutoff and reflects what GPTBot was able to index before that date. In browsing mode, it can fetch live web pages via OAI-SearchBot, similar to Perplexity but with different crawl behaviour.
ChatGPT's shopping mode (available in some regions) pulls product data from a combination of structured sources, including merchant feeds submitted via Bing and Google Shopping, and its own crawled data. If your store is not listed in these feeds, your chances of appearing in ChatGPT's dedicated shopping view are lower regardless of how well optimised your product pages are.
For ChatGPT, the highest-leverage action is often being present in Google Shopping — because that data flows into ChatGPT's product recommendations.
For general product queries in chat mode, having clear, factual product descriptions that have been crawled by GPTBot is what matters. The model draws on whatever it learned during training. If GPTBot was blocked from your site or never crawled your key pages, your products are essentially unknown to the model.
Our free audit checks your AI crawler access, structured data, and llms.txt — all the signals that Perplexity, ChatGPT, and Claude use to evaluate your store.
Run Free Audit →Claude: Context-Driven Recommendations
Claude's approach to shopping queries is more conversational. It is less focused on pulling live listings and more focused on giving considered recommendations based on what it knows — from training data and, when web access is available, from crawled pages.
Claude prioritises clarity and confidence. If your product pages are ambiguous about what the product actually does, who it is for, or what makes it better than alternatives, Claude will either skip your brand or caveat its recommendations heavily. Well-written product copy, clear category positioning, and a good llms.txt file all increase the likelihood of a confident recommendation.
Anthropic's ClaudeBot crawler respects robots.txt. If your store blocks it, Claude's knowledge of your products comes only from indirect sources like reviews, press mentions, and data scraped before the block was in place.
What to Optimise For All Three
Despite their differences, there is a core set of optimisations that improve your visibility across Perplexity, ChatGPT, and Claude simultaneously:
- Allow all AI crawlers in your robots.txt — GPTBot, OAI-SearchBot, PerplexityBot, ClaudeBot
- Add Product schema with price, availability, and brand — Perplexity and Google/ChatGPT both parse this directly
- Write a clear llms.txt file — gives all three assistants a fast, authoritative summary of your store
- Maintain Google Shopping feeds — this data flows into ChatGPT's shopping surface
- Write specific, factual product descriptions — vague copy hurts your visibility across all AI recommendation surfaces
- Get your pages indexed — submit a sitemap and ensure crawlers can reach your key product and collection pages
Frequently Asked Questions
Which AI assistant drives the most ecommerce traffic today?
Perplexity currently drives the most measurable shopping traffic for most ecommerce stores due to its dedicated shopping surface and search-like behaviour. ChatGPT is growing rapidly, especially in regions where its shopping mode is available. Claude is less shopping-focused by default but increasingly used for considered purchase decisions in categories like electronics, software, and home goods.
Do I need to do different things for each AI assistant?
The core foundations — crawlability, structured data, clear content, llms.txt — apply to all three. The only AI-specific action worth taking separately is maintaining a Google Shopping feed, which feeds ChatGPT's shopping mode. Beyond that, a single set of well-executed optimisations improves visibility across all three.
Can I track how much traffic is coming from each AI assistant?
Referral traffic from Perplexity appears as perplexity.ai in your analytics. ChatGPT traffic appears as chatgpt.com or openai.com. Claude referrals typically appear as claude.ai or anthropic.com. You can segment these in Google Analytics under Traffic Source > Referral.
Find Out How Your Store Appears to AI Shopping Assistants
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