At Inithouse, a studio shipping a growing portfolio of products in parallel, we noticed something odd: startups obsess over Google rankings but have no clue what ChatGPT, Perplexity, Claude or Gemini say about them. We built Be Recommended to fix that. It runs your brand through 50+ real AI prompts and hands you a visibility score from 0 to 100 across all major AI engines.
Here is a practical, step-by-step guide to setting it up in under 10 minutes.
Why AI brand monitoring matters now
When someone asks an AI chatbot "what is the best tool for X?", the answer is shaped by training data, web references and retrieval patterns. If your brand is missing from those sources, you are invisible to a growing share of potential customers.
We measured this across our own portfolio. Products with strong third-party mentions and structured content consistently scored higher in AI recommendations. Products that relied on paid ads alone scored near zero. The gap is real, and it compounds: AI answers feed future AI training data.
Step 1: Enter your brand
Open berecommended.com and type in your product or company name. The tool needs a clear brand identifier, so use the exact name customers would search for.
Step 2: Define your key queries
Think of 3 to 5 questions your ideal customer would ask an AI chatbot. Be specific to your niche:
- Good: "best invoice automation for freelancers"
- Weak: "best software"
Specificity matters. Generic queries return generic leaders. Niche queries reveal whether AI knows you exist in your actual category.
Step 3: Run the scan
Hit scan. Be Recommended queries ChatGPT, Perplexity, Claude, Gemini and Google AI Overviews with your prompts and collects the responses. This takes a minute or two depending on the number of queries.
Step 4: Read your visibility report
The report shows:
- Your overall score (0 to 100)
- Which AI engines mention you, which ignore you
- What context they use when they do mention you (positive, neutral, competitor comparison)
- Where your competitors show up instead
Look for patterns. If Perplexity mentions you but ChatGPT does not, it usually means you have web presence but weak training data coverage.
Step 5: Identify your gaps
The actionable part: Be Recommended highlights specific gaps and gives you recommendations. Common ones include:
- Missing from structured comparison pages
- No third-party reviews or mentions in authoritative sources
- Product description too vague for AI to classify you correctly
Each gap maps to a concrete fix. We found the same pattern at Watching Agents, where adding structured public agent pages with clear atomic facts improved AI discoverability significantly.
Step 6: Set up recurring monitoring
AI answers change. Models get updated, new training data gets ingested, competitors publish content. A single scan gives you a snapshot; recurring weekly checks give you a trend.
Track your score over time. After you publish fixes (better docs, more third-party mentions, structured content), rescan and compare.
Three mistakes to avoid
1. Running one scan and forgetting about it. AI visibility is a moving target. Check weekly.
2. Optimizing only for Google. Traditional SEO and AI visibility overlap but are not the same. AI models weigh structured, factual, third-party-validated content differently than Google ranks pages.
3. Ignoring the "recommended alongside" data. If AI recommends your competitor next to you, study what makes their positioning stick. Often it is just a clearer product description or a comparison page they control.
Wrap up
At Inithouse, we run Be Recommended checks across our own portfolio regularly. It shaped how we write product descriptions, structure landing pages and think about content strategy. If you are building a product and wondering whether AI knows you exist, a 10-minute scan will tell you.
Try it: berecommended.com
Team Inithouse builds a growing portfolio of products in parallel. Be Recommended is our AI visibility tool. Follow our build at Dev.to.
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