Changelog

Visibility tells you whether AI mentions your brand. It does not tell you what the model actually says about you. When an engine is asked about your category it does not just list brands, it describes them, and those descriptions are what buyers act on.

Brand Perception is out of early access and available to everyone. It keeps two questions apart on purpose. What AI associates you with gives each attribute an association score. Where you hold ground against competitors gives every brand a market prominence score. Both run 0 to 100 and they are not comparable, which is exactly what makes the gap between them useful: you can be described as fast constantly and still lose "fast" to every competitor in your market. The summary names your top attribute, your strongest against competitors, and the biggest gap of the two. Find it under Brand in the sidebar.

A new Ads page

ChatGPT shows sponsored ads inside some answers, so paid placement can sit in the same response as your organic mention. The Ads page shows every ad we captured on your tracked prompts: who is advertising, what they are promoting, which pages they send people to, and how often they appear. You also get advertisers in market, who is bidding on your branded and comparison prompts, and your ad coverage. A Partner column separates platform-bought placements from ads a brand booked directly. ChatGPT only for now. The docs walk through the page.

Brand Perception in the API and the MCP

Brand Perception data is now queryable through the Customer API and the MCP server. An agent can pull your attribute scores, your competitive ranks, and the sources behind each attribute, then turn them into a content brief or a monthly report without you exporting anything. Ask Claude what your category associates you with and where you are losing ground, and it reads the same numbers the page shows. Setup docs.

Sources in AI Shopping

The Shopping overview and each product page now show the domains and URLs behind the answer, the same source view you get everywhere else in Peec. When your product turns up in a carousel, this is how you find out which retailer or review page is doing the work, which is usually where the off-site brief starts.

The command palette is now generally available

Command or Ctrl plus K opens the palette from any page at any time. It came out of early access this window and picked up real depth on the way: you can drill from a prompt into the domains and URLs it cites without leaving the palette, and every list now pages all the way through instead of stopping at the first twenty results.

Early Access is now self-serve

Activate Early Access in your company settings to turn these on yourself. Prompt Builder is a guided setup that generates a prompt set for your brand and shows you the branded, non-branded, intent and persona split before you accept anything. New navigation regroups the left nav around how you actually work, so Results, Prompts, Sources and Brand each have a home. Crawlability history tracks how your robots.txt changed over time and lets you replay an earlier snapshot to see which AI crawlers you were allowing or blocking then.

When an AI engine answers one of your prompts, it quietly runs its own web searches first, then writes the answer from what it finds. Until now those searches were invisible, so you were optimizing for the answer without knowing what the model actually looked for to build it.

Query Fanouts is a new page that shows you exactly those searches. See the number of distinct fanout queries, filter them by type (Search, Shopping, Synthetic), and group them by topic or prompt. It surfaces which brands the engines name most often inside their searches and the word sequences that come up again and again, so you know what the models look for before they write. Find it in the sidebar.

AI Shopping in the MCP

AI Shopping is now in the MCP and Customer API. Ask Claude how one of your products performs in ChatGPT shopping and to rewrite its product page to close the gaps, or pull product visibility, win rate, ratings, and competitors into your own scripts. Alongside that, the star rating ChatGPT shows next to each product is now visible in Peec, the products table filters by brand, and the product detail view shows the shopping and web searches that surfaced each product.

Filter every chat by what it used

The all-chats view now filters by what a chat actually did: Web Search, Shopping, Product Comparison, Ads, and Map, per chat or aggregated per prompt, so you can answer questions like "which of my prompts trigger Shopping." Chat brand filters also gained AND/OR logic, with a "no brand mentioned" option to surface the answers where nobody in your set came up.

Branding and intent tags

Every prompt is now classified automatically: branded vs non-branded, and by intent (informational, transactional, commercial). Both are available as filters, so slicing your visibility by buyer intent takes two clicks instead of a manual tagging pass.

Brand-mention filters on Sources

The Domains and URLs tables now filter by which brands are mentioned, with the same AND/OR logic as chats. It is the quickest way to find pages that talk about you and a competitor together, or pages citing a rival but not you.

A redesigned members view

Managing access is now one company-wide members page with role-based access, plus search and CSV export. If you run many seats across projects, seeing who has access to what is a lot easier.

Shoppers now ask ChatGPT what to buy and trust the answer more than any search result or paid listing. You can see your Google rankings and your conversion rate, but when a shopper asks an AI what to buy, you have no idea which of your products it recommends, where it sends the buyer, or whether your visibility is growing or quietly slipping. For most e-commerce brands, AI commerce is a blind spot.

AI Shopping Analytics closes it. Bring your catalog and Peec gives you SKU-level visibility into AI shopping: which products get picked, why they get picked, and where AI sends your buyers. Today it tracks ChatGPT, where the shopping experience is most advanced, with other engines to follow. Go to Shopping in the sidebar to connect your catalog.

Every product scored

Your catalog becomes a table, one product per row, each with the metrics that decide whether you win the recommendation. Visibility is the share of AI shopping answers where your product appears. Win rate is the share of those answers where it lands first. Position is where it ranks when it shows up. Mentioned price is what the engine quotes for your product, checked against your catalog price so you catch anything stale or wrong. Attributes are the dimensions ChatGPT uses to compare products in your category, ranked by how often each one comes up.

The full picture on every product

Click into any product and you see where AI sends buyers when it recommends you, whether that is your store, a marketplace, or a retailer. You see how ChatGPT compares you against competitors and where your product descriptions fall short of the dimensions it actually weighs. You see which products are gaining placements this week and which are quietly bleeding them. And you see the exact prompts driving your visibility, alongside the ones you are not showing up for yet. The prompts you lose are your clearest list of what to fix.

A brand-level overview

The Overview rolls every product up to the brand level and answers the first question most teams ask: in my category, which brands and products show up most in AI shopping answers, and where do I rank? You get visibility, position, share of voice, and win rate over time for you and your competitors, the top performers at a glance, and the shopping queries driving those answers, including the ones gaining traction and the new ones just appearing. Those queries overlap heavily with Google Shopping search, so they double as a feed for your wider search and merchandising work.

Connect your catalog in minutes

Three ways to bring products in: paste your Shopify store domain and Peec pulls the catalog from your public product feed, upload a Peec CSV for non-Shopify catalogs, or connect an existing Google Merchant Center feed. Your products go live in minutes, organized by category and filterable across the Shopping overview, and they are matched against the last 30 days of chats so your metrics start with history instead of from zero. The docs walk through each option.

Chats are the raw evidence of how AI engines answer on your topics. Finding the ones that matter used to mean scanning them one at a time, with no way to filter by what was retrieved or who got mentioned.

It is out of preview now. You can filter chats by brand, see mention and source counts as sortable columns (citations are off by default to keep the view clean), and remove chats with a delete toggle. Pending chats are back in the table, it loads noticeably faster on large workspaces, and chats from deleted or archived prompts no longer appear, so what you see reflects your live prompt set. Sort by mentions or sources to surface the chats worth opening first.

Three new ways to connect your logs to Crawl Insights

Crawl Insights tracks how AI crawlers like GPTBot and ClaudeBot move through your site. Without a dedicated integration, getting your log data in meant manual file uploads, an ongoing effort that was easy to let slip. You can now connect through a WordPress plugin, AWS CloudFront, and Google Cloud, on top of the Vercel, Akamai, and generic webhook options from earlier. Point your logs at Peec once and AI crawl monitoring runs on its own, wherever your site is hosted. The setup docs walk through each option.

Bulk tag editing for large workspaces

Structuring a big workspace used to mean creating and fixing tags one at a time, which got tedious after a large prompt upload. You can now create up to 50 tags at once, and select multiple tags in the table to recolor or delete them in one go.