The Complete Guide for How to Use Peec AI in 2026

Peec AI is an AI search analytics platform that tracks brand visibility, position, and sentiment across AI search engines like ChatGPT, Perplexity, Claude, and Gemini. You set up prompts, Peec runs them against those platforms using browser automation rather than APIs, and you get data on how often your brand appears, where it appears, and how AI describes it. This guide covers how the platform works, how to set it up correctly, and where it fits against alternatives.

How Does Peec AI Work?

Peec AI uses UI scraping and browser automation to query AI search engines exactly as a real user would. Most analytics tools hit platform APIs, which return sanitised or summarised data. Peec interacts with the actual UI, so the results reflect what a real person sees when they type your prompt into ChatGPT or Perplexity. That distinction matters because API responses and real UI responses don't always match.

The platform tracks three core metrics across every prompt you load:

• Visibility: The share of queries where your brand is mentioned in the AI's response.
• Position: Where your brand appears within the response relative to competitors named in the same answer.
• Sentiment: Whether the AI's language around your brand is positive, neutral, or negative.

Each metric is tracked over time, so you can see trends rather than one-off snapshots. The dashboard shows you whether your visibility is rising or falling week over week, which AI engines are naming you, and which competitors are appearing where you aren't.

Step-by-Step: Setting Up Your First Peec AI Project

Getting a Peec project producing useful data takes four steps: defining your brand, loading your prompts, tagging them for analysis, and scheduling runs. The setup itself is straightforward. The part most teams get wrong is the prompts.

Step 1: Define Your Brand Profile

Start by entering your brand name, website, and the competitors you want to benchmark against. Peec uses this to identify mentions in AI responses. Be specific with competitor names. If you list "HubSpot" but the AI consistently refers to it as "HubSpot CRM," you may miss matches. Check how each AI engine actually refers to your competitors before finalising this list.

Step 2: Load Your Prompts

This is where most teams underinvest. Peec lets you add prompts manually, but it doesn't generate them for you from search data. Teams that add 10 to 15 branded queries ("best [brand]," "[brand] review," "[brand] vs competitor") end up with tracking data that only measures awareness, not discovery.

The prompts that matter most are the ones where your brand should appear but might not: category queries, use-case queries, problem-solution queries. A useful prompt set covers at least six intent types:

• Category: "What is the best [your category]?"
• Use-case: "What [category] should I use for [specific job]?"
• Comparison: "How does [brand] compare to [competitor]?"
• Recommendation: "Can you recommend a [category] for [persona]?"
• Problem-solution: "How do I solve [problem your product addresses]?"
• Feature-specific: "Which [category] has the best [feature you own]?"

For statistical reliability, you need a meaningful number of prompts per topic-market combination. Below a sufficient threshold, the variation in AI responses makes your visibility scores unreliable. If you're covering multiple markets or languages, multiply that per market.

If building a prompt set from scratch is the bottleneck, BrandPrompts generates research-backed, pre-tagged prompt sets built from real search data. The output is a CSV formatted for direct import into Peec, which cuts the prompt research phase from many hours to a few minutes.

Step 3: Tag Prompts for Structured Analysis

Peec lets you organise prompts with tags. Use this. Tag by intent type, topic pillar, and market. Without tags, your data is one flat list and you can't isolate which topic areas are dragging your visibility down. With tags, you can filter to see that your category prompts show 60% visibility but your problem-solution prompts show 18%, which tells you exactly where to focus content work.

Step 4: Set Tracking Cadence and Markets

Peec supports tracking across multiple countries. Set your target markets before the first run. AI engines don't all behave the same across geographies. ChatGPT's responses for "best project management software" in English UK may differ from English US, both in brand mentions and in source citation patterns. Tracking one market and assuming it generalises is a common mistake.

Reading Your Peec AI Dashboard

The Peec dashboard shows visibility, position, and sentiment as trend lines over time, plus a competitor comparison view. Here's how to read each metric without over-interpreting it.

One thing to watch: AI responses are non-deterministic. The same prompt can produce a different answer on consecutive runs. Peec runs prompts repeatedly and aggregates, which smooths this out, but you need enough prompt volume to make the aggregate meaningful. A visibility score based on 12 prompts is a rough estimate. A score based on 150 prompts is something you can act on.

What Is the Difference Between Peec AI and Profound?

Peec and Profound both track brand visibility in AI search engines, but they're built for different use cases. Peec is a monitoring and analytics tool. Profound adds strategic recommendations and content creation features on top of the tracking layer.

Based on Profound's own published review of Peec: Peec is one of the most affordable AI visibility platforms at entry level, but its add-on structure can push costs up as you scale. Peec is designed for monitoring. If you want a tool that tells you what to do with what it finds and helps you create content to close visibility gaps, Profound does more of that work for you.

The practical difference comes down to how your team operates. If you have content strategists and SEO specialists who can interpret tracking data and act on it independently, Peec gives you clean monitoring data at a lower starting cost. If you need the platform to surface recommendations and produce content briefs, Profound covers more of that workflow.

Neither tool solves the prompt design problem upstream. Both assume you arrive with a prompt set. That's the gap BrandPrompts is built to fill for teams using either platform.

Is Peec Easy to Learn?

Yes. The core workflow is simple: add prompts, run them, read the dashboard. Most marketing teams can get their first meaningful data set within a day of signing up. The UI is clean and the three-metric structure (visibility, position, sentiment) is intuitive for anyone with a background in SEO or brand tracking.

The learning curve isn't in the platform. It's in understanding what the data means for your GEO strategy. Knowing your visibility score is 34% tells you something. Knowing which prompt categories are dragging it down, which AI engines are the gap, and what content changes would move the number requires GEO knowledge that sits outside the tool itself.

Teams that get the most out of Peec pair it with a structured prompt research process and a content response plan. The tool is the measurement layer. The strategy around it is what drives results.

What AI Engines Does Peec Track?

Peec tracks visibility across the major AI search engines. Coverage includes ChatGPT, Perplexity, Claude, Gemini, and Google AI Overviews. Each engine behaves differently. According to data in our knowledge base, there is only 11% citation overlap between ChatGPT and Perplexity. That means 89% of citation opportunities are platform-specific. A brand that looks strong on ChatGPT may be nearly invisible on Perplexity, and vice versa.

This is why tracking one engine and extrapolating is a mistake. Peec's multi-engine view is where it earns its place in a GEO workflow. You can isolate which engine has the visibility gap and focus content and earned media efforts accordingly rather than treating "AI search" as one monolithic thing.

For context on why this matters at scale: ChatGPT had 900 million weekly active users as of February 2026. Perplexity passed 100 million monthly active users by April 2026. These aren't edge channels. Brands without tracked visibility across both are missing a large and growing portion of discovery traffic.

Building a GEO Workflow Around Peec AI

Peec is the measurement layer of a GEO workflow, not the whole workflow. Here's how to structure the work around it.

Start with prompt research. Use real search data (keyword volumes, People Also Ask patterns, competitor analysis) to identify what people actually ask in your category. Build a prompt set that covers all six intent types across your target markets. If you're building for multiple markets, generate prompts in local language patterns rather than translating from English.

Import that prompt set into Peec, tagged by intent and topic. Run the first round. Establish your baseline visibility, position, and sentiment scores across each AI engine. At this stage you're not trying to improve anything. You're finding out where you actually stand.

Then identify the gaps. Which topic pillars show low visibility? Which AI engines are consistently not mentioning you? What are competitors doing that you're not? Map the gaps to content and earned media opportunities.

Execute against those gaps. Publish content that answers the specific queries where you're invisible. Build earned media coverage on the platforms AI engines pull from most heavily. For ChatGPT, that means Bing-indexed pages. For Claude, Brave Search indexing. For Gemini, Google's own index plus YouTube and Medium. For Perplexity, Reddit and niche forums matter more than most brands expect.

Re-run your Peec tracking monthly to measure what moved. That loop is the GEO workflow. Peec makes the measurement step repeatable. BrandPrompts makes the prompt research step repeatable. The content and earned media work in between is where most of the effort goes.

Frequently Asked Questions About Peec AI

How does Peec AI work technically?

Peec AI uses browser automation and UI scraping to interact with AI search engines exactly as a real user would. It doesn't rely on platform APIs, which means the data reflects actual user-facing responses rather than API-only outputs. This is important because API and UI responses can differ in which brands get mentioned and how.

Is Peec AI easy to learn for non-technical marketers?

Yes. The core platform is accessible for marketers without technical backgrounds. Adding prompts, reading the visibility dashboard, and comparing performance against competitors doesn't require coding or deep technical knowledge. The complexity sits in knowing how to interpret the data and build a GEO strategy around it, not in operating the tool itself.

What is the difference between Peec AI and Profound?

Peec is a monitoring tool that tracks visibility, position, and sentiment across AI engines. Profound adds strategic recommendations and content production features. Peec is the more affordable starting point for teams that can act on tracking data independently. Profound does more of the strategic and content work for teams that want that built into the platform.

How many prompts do I need to get reliable data in Peec?

You need a meaningful number of prompts per topic-market combination. Below a sufficient threshold, the non-deterministic nature of AI responses creates enough variation to make your visibility scores unreliable. Most teams start with too few prompts, which produces data that looks clean but doesn't represent what's actually happening across your category queries.

Which AI engines does Peec AI track?

Peec tracks across ChatGPT, Perplexity, Claude, Gemini, and Google AI Overviews. Tracking all of them matters because visibility varies greatly by engine. Research shows only 11% overlap in citations between ChatGPT and Perplexity, so a brand visible on one can be nearly invisible on the other. Multi-engine tracking is the only way to see the full picture.