01What RadarKit Is and How It Works

RadarKit is a tool that tracks how often your website or brand gets mentioned in answers from AI models like ChatGPT, Perplexity, AI mode, AI overviews, and Copilot. It is built by an SEO team with 10 years of experience. They use their own browser automation and partner with proxy companies to get real, location-based data.

Instead of using an API, RadarKit runs actual browsers from different countries. For example, someone in the UK can see what ChatGPT answers to a user in Germany or Japan. This gives you the true answer a real user in that location would see.

The tool buys mobile proxies from providers like MyPrivateProxies and WebShare to get access to more than 50 countries.

02Main Features of RadarKit

RadarKit has several powerful features that go beyond simple tracking. Here are the main ones:

  • Multi-platform tracking: It works across ChatGPT, Perplexity, AI mode, AI overviews, and Copilot. It does not track Claude because Claude is mostly B2B focused.
  • Query fanout extraction: When you enter a prompt, RadarKit goes into the network tab of the browser and pulls out the actual keywords the AI model searches for. For example, for "best CRM software," it might show "best CRM software 2026" and "small business enterprise comparisons."
  • Brand Kit: You can add your brand positioning, target customer, differentiators, awards, and facts. RadarKit uses this to control how your brand appears in AI-generated content.
  • Outreach agent: This agent finds domains that get cited often, finds their emails, sends outreach messages, follows up, and even negotiates pricing for backlinks or mentions.
  • Content creation with GEO metric: The tool creates articles optimized for both search engines and LLMs. It uses a metric called GEO to include facts, percentages, and data that AI models prefer.

03How to Set Up RadarKit: Step by Step

  1. Add a project. Go to RadarKit and create a new project for your brand or website.
  2. Connect Google Search Console. You can link your GSC account so RadarKit can read your impressions data.
  3. Let the agent suggest prompts. Use RadarKit’s agent to automatically suggest prompts based on your existing impressions.
  4. Add your prompts. You can manually enter, or accept the agent’s suggestions. These are the questions you want to track across AI models.
  5. Set up Brand Kit. Fill in your brand name, positioning, target customer, key differentiators, awards, and any approved facts.
  6. Wait for citation data. Let RadarKit run for a few days to collect which sources are being cited by AI models for your prompts.
  7. Use the outreach agent. Select the prompts you want to improve, choose domains that get cited often, set follow-up frequency and negotiation percentage, and let the agent start outreach.

04Using RadarKit for Tracking and Content Creation

Once your project is set up, you can track citations daily. Go to the citation data tab to see which types of content influence results. For example, for Zoho, listicle articles influence 43% of AI answers.

For Zois (an AI video generator), product pages influence 34%, and social platforms like YouTube and LinkedIn influence 24%.

To create content, look at the query fanout tab. Pick a fanout term, click "create content," and choose a format: listicle, blog post, or comparison page. RadarKit will pull baseline articles from both SERPs and citation data.

It then creates an outline based on query fanouts, entities, NLP terms, and PA questions. The article includes an image, FAQ section, and outgoing nofollow links. You can change paragraphs, add schemas, and publish directly to WordPress.

The brand page radar feature lets you track a specific published page. It shows how many times that page was cited in AI answers in the last 30 days and for which prompts.

05Results, Tests and Comparisons Shown in the Episode

RadarKit’s team ran a test on the keyword "best UseHall alternative." UseHall went bankrupt, so there was search demand. The team took a 360-degree approach: they created a LinkedIn post, a YouTube video, a Reddit post on their own subreddit, and a blog article. After that, RadarKit's own tool showed that their content became the number one alternative mentioned inside AI overviews for that query.

In terms of comparison, HubSpot is doing very well with AISEO. They are buying backlinks from any site that ranks for their prompts. HubSpot even reached out to RadarKit to get mentioned in a blog post, and they gave RadarKit two links in return.

HubSpot also runs many pseudo channels like YouTube channels and LinkedIn posts to dominate AI mentions.

RadarKit’s team also noticed that many funded AI tools are going bankrupt. UseHall and UseBear (backed by Y Combinator) are examples. The team believes these tools failed because they build on top of APIs, and API costs are high when you run thousands of prompts.

06Tips, Limits and Mistakes to Avoid with RadarKit

Sample size matters. If you want to optimize for AI visibility, do not look at a single answer. You should track at least 100 responses over seven days. Then analyze which answers repeat and which citations are preferred.

Understand temperature. AI models use a concept called "temperature" – randomness in answers. ChatGPT sets temperature automatically. Because of this, the same question can give different results each day.

That is why you need data over time.

Focus on web search percentage. For your prompts, run 400 queries and see how many times a web search was performed. If the percentage is above 70%, the AI is doing a web search each time, and you can influence the answer by ranking in those search results. If it is below 50%, the AI is using its training memory, and you may need to wait for the next model update.

Do not just find fanouts. Many people ask ChatGPT for fanout keywords, but that is not accurate. RadarKit extracts them from the actual network tab, showing what the LLM really searches for.

07Who Should Use RadarKit and Why It Matters

RadarKit is for SEO professionals, content marketers, and brand managers who want their brands to appear more often in AI answers. It is especially valuable for anyone targeting B2B or B2C niches where AI models like ChatGPT and Perplexity are used by customers to find solutions.

It matters because AI-driven answers are becoming a major source of traffic and brand visibility. Unlike traditional search, AI models change responses frequently and rely on web searches and training data. Tools like RadarKit help you see what the AI actually does behind the scenes – the real searches it performs, the sources it trusts, and how your brand is positioned.

By using the outreach agent and content creation module, you can take direct action to improve your AI presence without waiting for slow organic changes.