The OmniGro AI Visibility Assessment is a free diagnostic that shows how a brand currently appears in AI-generated recommendations. It runs structured prompts across ChatGPT and Google AI, scores each result, and maps where the brand appears, where it is missing, and which sources may be shaping those outcomes. This walkthrough uses ABC Hotel as a fictional example to show what clients receive and how to read each section.
What the Report Is Actually Measuring
This diagnostic measures AI visibility: whether your brand is recommended, mentioned, or missed when someone asks an AI a relevant question.
It is not measuring brand reputation or product quality. A lower score reflects how strongly the brand is represented in the tested AI scenarios.
Each response is scored across four dimensions:
- Brand mention presence (40 pts) — Does the brand appear?
- Position and prominence (30 pts) — Is it a top recommendation or a passing mention?
- Sentiment (20 pts) — Positive, neutral, or negative?
- Context quality (10 pts) — Is the brand described accurately and in a relevant context?
For ABC Hotel, the diagnostic returned an overall AI Visibility Score of 35% across the analysed responses. That score reflects real unevenness: the hotel appeared prominently in some queries and was entirely absent in others.
The Prompts — and Why the Mix Matters
AI visibility is rarely uniform. A brand can appear strongly in one type of query and disappear in another. That is why OmniGro tests a deliberate mix of prompt types rather than a single set.
For ABC Hotel, prompts covered four angles: direct brand queries ("Is ABC Hotel a good place to stay?"), category-level searches ("Best boutique hotels in the city?"), attribute-specific queries ("Hotels near the business district with meeting facilities"), and decision-stage comparisons ("ABC Hotel vs [competitor] for a corporate event"). Each type surfaces a different stage of the buyer journey.
Four types of prompts are used across every diagnostic:
- Broad — Early discovery queries, wide category searches
- Targeted — Specific location, audience, or use-case queries
- Niche — Distinct brand strengths or positioning angles
- Comparison — Direct evaluation queries where buyers choose between options
This mix shows where the brand wins, where it drops out, and which specific areas have the clearest opportunity.
The diagnostic shows 12 to 15 prompts per brand. That is intentional: enough to surface meaningful patterns without overwhelming the report. In a full engagement, OmniGro runs hundreds of prompts over time, built around the brand's specific category, audience, and competitive context.
What the Results Section Shows
Each prompt result is recorded separately for ChatGPT and Google AI, with a score, a mention status, and a sentiment rating.
For ABC Hotel, a direct brand query returned a score of 93% on Google AI. A broad category query returned 0% on ChatGPT. Both tests ran on the same day, for the same brand.
That is the typical pattern: uneven visibility across query types and platforms. For ABC Hotel across 26 responses:
| Metric | Value |
|---|---|
| Mention rate | 50% |
| Positive mention rate | 69% |
| Not mentioned rate | 50% |
| Average score | 35% |
Half the tested queries produced no brand mention at all. That gap, between strong performance on direct queries and weak performance on category queries, is where the clearest opportunity sits.
Example AI Responses
The report includes verbatim snapshots of what the AI actually said.
A strong mention looks like this (Google AI, Score: 100%):
> "Yes, ABC Hotel is considered a top-tier destination for business travellers in the city, known for its well-equipped meeting facilities, central location, and attentive service. It operates as a full-service property..."
A missed mention looks different. When asked "Which hotels in the city are best for corporate events?" ChatGPT returned a list of competing hotels with no mention of ABC Hotel at all.
The scores show the pattern. The verbatim snapshots make it concrete.
Citation Source Analysis
This section shows which outside domains AI platforms drew on when generating answers in the category.
For ABC Hotel, competitors appeared across review aggregators, travel publications, and directory listings. ABC Hotel's own website appeared as a cited source on Google AI but was absent from ChatGPT citations.
This matters because AI platforms do not rely only on a brand's own content. According to Chen et al. (2025), University of Toronto (arXiv:2509.08919), AI engines cited third-party sources in 63 to 95 percent of recommendation responses. That figure varies by platform but holds consistently high across all four major models. Brand-owned content alone is rarely sufficient.
The citation analysis shows which external signals need strengthening and where competitors may have built an advantage.
Platform-Level View
A brand often performs differently across platforms, and the report breaks this down.
For ABC Hotel, Google AI returned a 54% mention rate. ChatGPT returned 46%. The positive mention rate was higher on ChatGPT (46%) than Google AI (23%). Google AI tended to cite the brand in a more neutral, informational way. ChatGPT included more direct recommendations when it mentioned the brand.
That split shapes where to focus first.
Competitors Analysed
The report identifies which competitors appeared in AI responses to your tracked prompts, and how often.
For ABC Hotel, one competitor appeared in 73% of responses across both platforms. A second appeared in 62%. ABC Hotel appeared in 50%.
This is useful for two reasons. First, it shows where the gap sits relative to brands competing for the same AI recommendations. Second, it shows what strong AI visibility looks like in practice. Competitors with high mention rates have built strong third-party presence, the right content structure, and the entity signals AI platforms draw on. That is where ABC Hotel needs to close ground.
The competitor section also shows which external links those brands are being cited through. That points directly to where stronger third-party presence is needed.
This Diagnostic vs. Full GEO Monitoring
The free diagnostic is a snapshot: a selected set of prompts run once to establish a starting picture.
OmniGro's full GEO reporting goes significantly deeper. It covers hundreds of prompts on an ongoing cadence. Brands track visibility across query categories, platforms, and competitors over time. They can see where they stand today and how that changes week to week.
In a full engagement, OmniGro works closely with the client to drill down their target niche. The prompts, competitive set, and optimisation work are built specifically around that brand's category, audience, and key decision moments.
For a full explanation of what citation tracking measures, see What Is AI Citation Tracking.
What Comes Next
Pilot: OmniGro can start with a focused pilot targeting the highest-opportunity areas from the diagnostic. Initial movement in priority areas can appear within 2 to 3 weeks.
Ongoing reporting: Some brands begin with GEO reporting first. This gives a continuous view of visibility trends, competitor movement, and persistent recommendation gaps across hundreds of prompts over time. It is a useful way to understand the full picture before committing to a larger optimisation programme.
FAQs
Is the OmniGro AI Visibility Assessment free?
Yes. The diagnostic is a free snapshot. It covers a selected set of prompts across two platforms to establish a starting picture of how the brand currently appears in AI-generated recommendations.
How many prompts does the diagnostic cover?
The diagnostic covers 10 to 15 prompts per brand, tested across ChatGPT and Google AI. The full OmniGro monitoring programme covers hundreds of prompts on a continuous basis.
Why does a brand appear in some AI answers but not others?
AI visibility is query-dependent. A brand may be cited when someone asks a direct question about it but absent when someone asks a broader category question. Structured third-party presence, content format, and entity signals all affect which queries produce a citation. See why some brands do not appear in AI answers for a detailed breakdown.
Does the diagnostic tell me why I am missing from AI answers?
It identifies where visibility gaps occur and which citation sources are influencing outcomes. The Brand Visibility Audit goes further, covering 200+ prompts with a full authority gap analysis and a prioritised GEO roadmap.
What is the difference between the diagnostic and the full audit?
The diagnostic is a free starting point, covering a targeted prompt set run once. The full Brand Visibility Audit covers 200+ prompts across ChatGPT, Claude, and Gemini, with accuracy scoring, authority gap analysis, and a prioritised action plan.
Do AI answers change over time, and how does that affect the report?
Yes. AI platforms update their models, index new sources, and shift citation patterns over time. A single snapshot reflects that moment. That is why OmniGro's continuous monitoring runs prompts on a regular cadence. Prompting periodically over weeks and months averages out one-off variation. It gives a much more accurate picture of where a brand consistently stands.
Conclusion
The OmniGro AI Visibility Assessment shows where a brand stands in AI-generated recommendations today. The score, prompt results, example responses, citation sources, and platform breakdown combine into a clear, actionable starting picture. For most brands, the finding is uneven visibility across queries and platforms. That is the gap the diagnostic makes visible and the programme is designed to close.