What is this tool?
This free checklist scores your brand’s visibility across the signals AI systems use to decide whether to reference, recommend, or cite a company. It covers 20 questions across five categories — brand entity signals, content and authorship, technical and structured data, authority and trust, and founder visibility — and gives you an overall score out of 100, a benchmark against similar brands at your stage, and a prioritised 30-day action plan.
How to use it
1. Select your business type and stage This unlocks your industry benchmark so you can see how you compare to similar brands. A pre-launch SaaS has different baselines than an established agency — the benchmark adjusts accordingly.
2. Answer each question honestly Use Yes, Partial, or No for each item. Partial is there for a reason — if you have an About page but it’s thin, or backlinks but mostly from low-quality sources, marking it as partial gives you a more accurate score than forcing a yes or no.
3. Read the tip under each answer Every item reveals a specific note when you answer it. These tell you exactly what the signal means and, if you’re partial or no, what the fastest fix looks like.
4. Check your benchmark Once you’ve selected your type and stage, the score panel shows where you sit relative to similar brands. This is useful context — a score of 55 means something very different for a pre-launch startup than for an established company.
5. Switch to the 30-day plan tab The plan tab organises your unchecked items into three phases by effort level. Week 1 covers quick wins you can implement in an afternoon. Week 2 covers medium-effort items. Weeks 3 and 4 cover longer plays that require outreach, content creation, or development work.
Why AI visibility matters for your brand
When someone asks ChatGPT, Perplexity, or Gemini about your category, your product, or a problem you solve — you want your brand to be part of the answer. That doesn’t happen automatically. AI systems build their understanding of brands from structured signals across the web: who wrote the content, when it was published, what external sources reference it, whether the brand has a coherent entity across multiple platforms, and whether real people are visibly behind it.
Most brands fail not because their product is weak but because their online presence is ambiguous. No author bylines. No structured data. No external mentions. Nothing that gives an AI system enough signal to confidently cite them over a competitor who has all of those things in place.
What the five categories measure
Brand entity signals assess whether AI systems can identify your brand as a distinct, verifiable entity — consistent naming, a clear About page, external references, and structured database listings like Crunchbase.
Content and authorship signals measure whether your content looks trustworthy to an AI — named authors, original research, publication dates, and direct answers to the questions your audience actually asks.
Technical and structured data signals check whether your site speaks the language AI crawlers prefer — schema markup, structured metadata, and consistent representation across directories.
Authority and trust signals cover the off-site evidence that your brand is credible — quality backlinks, third-party mentions, press coverage, and verifiable social proof.
Founder and team visibility is the category most brands overlook. AI systems increasingly cite people alongside companies. A named, publicly visible founding team is one of the fastest ways to build AI visibility, especially for early-stage brands that don’t yet have a large backlink profile.
A note on the scoring and benchmarks
The 20 questions are weighted based on their documented importance in Google’s E-E-A-T framework and published research on how large language models evaluate content trustworthiness. Higher-weight items (8–10 points) are the ones with the most consistent impact across all three major AI platforms. Lower-weight items (5–6 points) still matter but are secondary to the fundamentals.
The industry benchmarks are directional estimates based on observable patterns across brands at each stage and type. Think of them as a realistic reference point, not a precise measurement.