Changelog

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.

Brand Insights graduates from Early Access to everyone, in a dedicated Brand category in the nav. It gives you a per-brand deep dive on visibility, sentiment, position, and share of voice, with full time series and a heat map, so you can see how any brand moves over time and where it stands right now.

Pick any two of brands, topics, tags, or models for the x and y axes and outliers surface fast. The strongest-model and weakest-model highlights are the quickest way to decide where to focus: you can see at a glance which engine is carrying your visibility and which one is leaving it on the table.

Movers on Domains and URLs

Both the Domains and URLs pages now open with a bar chart split into Top, Trending, Losing, and New tabs, so you can see which sources are gaining or losing ground without scrolling the table. Click any tab for an expanded view of up to 50 entries. It is the fastest way to catch a competitor breakout or a sudden drop the moment it happens.

Custom URL and domain classifications

You can now create your own URL types and domain types and assign them to sources, on top of our default classifications. The whole taxonomy is available end to end in the Customer API and through MCP, so you can script your own classification scheme or wire it straight into an agent workflow.

A cleaner way to read chats

We rebuilt the chat detail view that opens whenever you click into a chat. The layout is cleaner, the hierarchy between answer, sources, and features is clearer, and you can now move from one chat to the next without closing the view. Reading through chats one after another is something a lot of you do, and this makes it much faster. The Prompts table also gained chat feature columns: web search is shown by default, and you can switch on the rest from the column picker to filter down to, say, only the prompts where the model actually went to the web.

More of your data through MCP and the API

Chat features are now queryable on individual chats and available as a filter on list_chats: ads, maps, product carousels, web search, image galleries, and shopping fanouts. You can ask Claude to "show me every chat where ChatGPT served an ad for my brand in the last 30 days" or filter the same way in your own scripts, and get_chat returns the full detail including ad payloads and map markers. Crawl Insights is now exposed the same way, so agent and bot crawler data is queryable end to end. We also added Personal Access Tokens you can create right on the API Keys page for use with MCP, and retrievals delta plus an onlyNew filter on the public source endpoints so you can pull just what changed in a period.

Chinese models

We added DeepSeek and Qwen, so you can track visibility across the Chinese AI ecosystem alongside the engines you already follow.

Early Access

Activate Early Access in your company settings to turn these on yourself.

• Gap Analysis is now its own page in the nav instead of a toggle inside Sources. Same feature, much shorter path to it.
• Source Bookmarks let you bookmark URLs and domains straight from the sources tables and filter to show only the bookmarked ones, so you can keep a curated set of references in view across reports.
• Command/Ctrl-K opens a keyboard-driven search palette from anywhere in the app, with nested search into prompts, domains, and URLs. This is the first version, with more coming.
• Instant Pitch Projects let agencies spin up a pitch project that runs 10 chats per prompt instantly, instead of collecting them over seven days, so you can have data ready for a pitch the next day.

When ChatGPT responds with local businesses, Peec now renders them on an interactive map directly inside the chat view. Each pin is hoverable so you can see the business detail. If you are tracking local visibility or city-level recommendations, you finally see the answer the way the user sees it, not as a flat list of names.

We also started parsing and rendering the ads that appear inside ChatGPT chats, with a clear "ads" tag so you can spot at a glance which chats contain advertising. It is a first step toward understanding paid presence in AI answers, alongside the organic mentions you already track.

MCP, now at bulk scale

You can now bulk create, update, and delete Brands, Prompts, Tags, and Topics through the Peec AI MCP, up to 50 at a time. Brand profile is now readable and writable, results are sortable, and URL-level opportunities and gap analysis are available directly through MCP and the Customer API. List endpoints return prompt volume and total counts so you can prioritize the work that actually matters. The same workflows you would run by hand, scripted at scale from Claude, Cursor, or any MCP client.

Early Access is now self-serve

A new Early Access section in your company settings lets you turn on beta features yourself, no need to ping us. Two features are live there today.

Synthetic Query Fanout predicts the follow-up queries an AI engine is likely to generate from a user's original search, so you can see how those branches play out for your brand. ChatGPT only today, more engines coming.

Brand Insights breaks down visibility, share of voice, position, sentiment, and rankings across AI models, topics, tags, and brands in a single view. Useful when you want to slice the same competitive question several ways without rebuilding charts.

Smarter prompt suggestions

Suggested prompts now factor in search volume and topic relevance, not just topic match. Higher-volume prompts and prompts closer to your topics surface first, so the suggestions you see are the ones most worth tracking. Less noise during setup, fewer low-value prompts to skip past.

Most AI visibility data tells you whether your brand appears in AI responses. Agent Analytics goes one layer deeper: it shows you what AI crawlers are actually doing on your site, which pages they visit, how often, and whether they can access them at all. Built on your own server log data, it gives a direct and objective view of how AI bots interact with your content. That helps you catch technical access issues before they affect your visibility and understand which pages AI models are most interested in.

At launch, Agent Analytics includes two tools: Crawl Insights and Crawlability. Log ingestion connects via Cloudflare Workers or CSV/CLF file upload. Support for additional hosting providers is on the roadmap.

Crawl Insights

Connect your server logs and see which AI bots visit your site, which pages they hit, how often, and with what result. The overview shows aggregate trends across bots, status codes, and traffic volume. The details view lets you drill into specific pages, filter by bot type or time range, and see how retrieval data from your tracked prompts sits alongside your actual crawl activity. That combination is directional and useful for finding where to investigate, not a direct cause-and-effect relationship.

Crawlability

Check which AI bots are allowed or blocked by any domain's robots.txt instantly, without needing server access. You can also test individual URLs against the current rules to catch accidental blocks before they affect how AI models reach your content.

You can now use your Peec AI data directly inside the AI tools you already work in with the new Peec AI MCP. Ask Claude, Cursor, VS Code, Windsurf, and other MCP-compatible tools questions about your visibility, competitors, sources, prompts, and trends using your real Peec project data.

This makes Peec AI more than a dashboard. Instead of switching between tools, exporting reports, or pulling screenshots by hand, you can get answers where the work is already happening. That makes it easier to build reporting workflows, run competitive analysis, and turn AI visibility data into action faster. To make setup easier, you can now find Peec AI MCP directly in partner connector directories (Anthropic & Cursor) and connect with a single click.

More of your data is now available inside MCP

The MCP server now gives you deeper context when you ask questions. You can pull source URL content for analysis, see YouTube channel names and Reddit community names in source reports, access Peec AI recommendations directly through MCP, and inspect available AI models without guessing valid model IDs.

MCP now supports more complete workflows

You can now go beyond read-only analysis. We shipped native prompt workflows for faster repeated tasks, added write tools so you can create, update, and delete key Peec AI entities from MCP clients, and improved the server instructions so AI tools are better at choosing workflows and recovering from errors on their own.

Your topics and prompts are only as good as what Peec knows about your brand. Brand Profile gives you one place to describe your brand, market, and target audience. When you update it, Peec automatically regenerates your suggested topics and prompts so your tracking reflects how your brand actually shows up in AI responses, not a generic approximation.

We also redesigned the Brands page. It now uses a table layout with inline editing for display names and brand colors, and a cleaner flow for managing domains. Less friction across the board when you're setting up or updating your competitive landscape.

Pause and resume projects

You can now pause any tracking project and resume it whenever you are ready. Your setup stays intact, and credits stop being consumed while paused. Useful if you are winding down a campaign, handing off to a client, or want to free up credits without losing your configuration.

New brand filter

The brand filter is now multi-select and grouped into "Your brand" and "All brands" with search. Keep your own brand as the anchor point and choose exactly which competitors to compare against. The Top 7 Brands card on the overview updates with your selection.

Custom domain selection on source charts

You can now pick up to 5 specific domains to display on the source chart. Colors match your brand configuration. Useful if you want to focus on the domains that matter most instead of seeing the default top results.

You can now click into any URL from the Sources page to see the full picture: retrievals over time, citation rate, retrievals by model, which prompts retrieve it, which brands appear alongside it, and the actual chats. All with the same filtering you are used to (date range, model, country, topic).

This was one of our most requested features. Until now, you could only see aggregated data at the domain level. You'd know "reddit.com cites you 50 times" but couldn't see which specific threads drive those citations or how individual URLs trend over time. The URL detail page closes that gap.

Source metrics restructuring

We restructured the metrics in the Sources tables to make them clearer. The old "Used" column was confusing because values could exceed 100%. The new metrics form a funnel: reach, depth, impact.

Retrieved shows the share of chats where a source appeared, always 0 to 100%. Retrieval Rate shows the average number of source appearances per chat as a decimal. Citation Rate shows how often a retrieved source gets explicitly cited.

We also added Citation Rate to the gap analysis view.

Separate Domains and URLs pages

We split the Sources section into dedicated Domains and URLs pages in the sidebar. Previously, URLs were hidden behind a tab that most users never found. Now each view has its own entry point, making it much easier to navigate.

New model selector

Models are now grouped into Active, Inactive, and Available categories. Inactive means deprecated or disabled models that still have historical data. The available models list also shows which models use scraper-based tracking vs API-based tracking.

Manage your credits and prompts the way your team actually works. On the Projects page, agency users can now choose which AI models each project tracks and how many prompts it gets. Shift resources as priorities change: focus your budget on the projects and models that matter most.

Brands can also now select which AI models they want to track, so you only pay for the coverage that's relevant to your market.

Keyword import for prompt suggestions

Upload a keyword list and we automatically cluster them into topics and generate ready-to-track prompts. New projects get smarter topic and prompt suggestions from the start. We build a profile for your brand so suggestions are tailored to your business. Combined with keyword import, you can go from zero to full coverage in minutes.

API: Share of Voice and advanced filtering

The API now includes Share of Voice as a metric. You can filter results by topics, tags, models, brands, domains, and URLs, giving technical teams more flexibility for custom dashboards and automated workflows.

Timezone picker redesign

Finding and selecting your project's timezone is now simpler, with better usability on smaller screens.

One of the most requested metrics since late 2024, Share of Voice (SoV) tells you what slice of the AI conversation your brand owns compared to all the competitors you track. Unlike Visibility, which measures whether you're mentioned at all, SoV counts every mention per response, so a brand referenced five times in one chat scores higher than one referenced once.

We also added sorting by absolute values and trends across all four scores (Visibility, SoV, Sentiment, Position), making it easy to spot which brands moved the most in any direction.

Topic and prompt suggestions now incorporate your full company profile, which means they come out more specific and relevant. The Suggested tab auto-classifies prompts with tags, so you can filter suggestions immediately without manual cleanup.

You can also upload a CSV of your own keywords: we'll cluster them into topics and generate ready-to-activate prompts in minutes, making it a lot faster to get a new project off the ground.

Filter Sources by domain type

On the Sources page, you can now filter the URL list by domain type: owned, earned, UGC, paid, or unknown. This makes it faster to answer the questions that matter most: like how much of your AI visibility comes from your own content versus third-party coverage. Clicking a bar in the domain type chart jumps directly to the filtered URL list.

Actions now show recurring themes and a new Site Crawlability check

Each action card now surfaces the most common themes from the sources behind it. This helps you see at a glance what content topics are driving each recommendation. We also added a new Site Crawlability action: it scans your robots.txt file and flags if major AI crawler bots are blocked.

Much faster for longer time frames

Charts previously struggled with data beyond 30 days. Now you can pull all-time data without issues, and aggregate any chart on a weekly or monthly basis, especially useful if you're on a weekly tracking plan where daily charts looked noisy before.

We also added a bar chart showing the average for the selected time frame on the Overview page.

Shopping fanout queries are now visible

On chat detail pages, you can now see the shopping queries that AI models run behind the scenes to populate product results, particularly interesting for e-commerce brands.

For API users: fanout and shopping fanout queries are now available through our API.

Microsoft Copilot is now trackable

Copilot has been on the roadmap for a while and frequently asked about by customers: it's now fully supported.

Source Gap Analysis shows where competitors appear but you don't, turning competitive intelligence into clear next steps.

Organize large-scale tracking and identify exactly where to improve. Topics let you group prompts by theme and navigate through topic-based views instead of scrolling through long lists.

Fanout queries and chat-level intelligence

See the multiple sub-searches AI platforms perform when answering questions. Fanout query aggregates on Prompt Details show which related searches AI platforms run when they process your prompts.

The terms mentioned reveal which topics and brands are most closely associated with your prompts. The redesigned Chat Details page provides better insights into individual chats.

YouTube transcripts and expanded monitoring

YouTube transcript analysis searches for brand mentions in video content. The "Only" filter provides one-click filtering for models and tags. We expanded to 24 new countries including 5 MENA markets and the Philippines.

Team collaboration and permissions

The Project Viewer role provides read-only access to visibility data. Competitor aliases let you track variations of competitor names under a single profile. Shopping widget indicators show when prompts trigger shopping research in ChatGPT.

Import your entire prompt library with tags in seconds using CSV upload. The redesigned interface loads faster and displays more data. We renamed Workspaces to Projects for clearer terminology.

URL and domain classification

See which content types drive your visibility. URL classification identifies articles, listicles, product pages, comparisons, how-to guides, and discussion threads.

Domain classification sorts sources into UGC, Editorial, Corporate, Reference, Institutional, and Other.

Advanced filtering and data export

Prompt filtering is now simpler with AND/OR toggle logic for tags. Track prompts tagged "product" AND "comparison" or either "enterprise" OR "SMB" segments without building complicated filter combinations.

Multi-select filters work across all tables. The rebuilt Looker Studio connector and expanded API endpoints give technical teams programmatic access to all visibility data for custom dashboards and automated reporting workflows.

We launched Peec AI to help marketing teams track brand performance across ChatGPT, Perplexity, and Google AI Overviews. You can now see three key metrics: Visibility shows how often your brand appears in relevant conversations, Position reveals where you rank when mentioned, and Sentiment analyzes how AI models describe your brand.

AI Overviews tracking helps you monitor how your brand appears in Google's AI-generated summaries alongside chatbot responses.

Custom date ranges and IP localization

Compare performance across any time period you choose. Track campaign impact week-over-week, review quarterly trends, or analyze year-over-year changes.

Run prompts from specific geographic locations so your visibility data reflects what users in each market actually see.

Model-level source attribution

Trace mentions back to specific URLs, domains, and content types. Understand which content drives your visibility in each AI platform.