AI search visibilityfor events and their sponsors.
Track visibility for brands like these, and the events they sponsor
AI Visibility Trends
% of AI responses that mention each brand vs. competitors
Competitor Ranking
AI visibility vs. key competitors this week
| Brand | Visibility | Sentiment | Position | |
|---|---|---|---|---|
| 1 | Nike | 74% | 81 | 1.8 |
| 2 | Adidas | 64% | 63 | 2.3 |
| 3 | Puma | 44% | 71 | 3.1 |
| 4 | Under Armour | 30% | 59 | 3.7 |
| 5 | New Balance | 24% | 76 | 4 |
| 6 | Reebok | 15% | 62 | 4.5 |
| 7 | ASICS | 11% | 69 | 4.8 |
Top Sources
Domains AI models rely on when generating responses about these brands
Source Type
| Domain | Used | Avg. Citations | Type |
|---|---|---|---|
 nike.com | 71% | 2.6 | Corporate |
 espn.com | 58% | 2.1 | Editorial |
 forbes.com | 47% | 1.9 | Editorial |
 sportspromedia.com | 41% | 1.7 | Editorial |
 adidas.com | 36% | 1.1 | Competitor |
 reddit.com | 24% | 0.6 | UGC |
 wikipedia.org | 19% | 1.4 | Editorial |
Recent AI Responses
Latest AI chat responses mentioning tracked brands
Understand how AI sees your event
See how an event appears in AI search, which sources those answers are built from, and what to change so the next answer reads better.
Attendees, fans, journalists, and buyers now ask AI assistants which events are worth their time, often before they ever reach a results page.
Source: TechCrunch, 2025The properties they buy have the same gap. Most events still describe their reach with impressions and gut feel instead of hard numbers.
Source: Digiday / Forrester, 2025Properties that actively manage how they appear in AI answers can lift their citation visibility by up to 40%.
Source: Conductor 2026 AEO/GEO BenchmarksContext Relevance Score
Which thematic contexts your event appears in, and whether the story you tell about it has landed in AI answers.
AI Mention Rate
How often your event is mentioned in relevant prompts, as a percentage across every AI search engine.
Sentiment Score
How your event is described when mentioned: positive, neutral, or negative, backed by real AI answer examples.
Formula 1: Formula 1 is the default recommendation for new motorsport fans, described as accessible, well documented, and easy to follow across markets.
MotoGP: MotoGP maintains a consistent but generic presence in answers about racing calendars, with broad but surface-level descriptions.
Formula E: Formula E is rarely surfaced unprompted in AI responses about top-tier racing series despite a full global calendar.
Share of Voice
Direct comparison with competing events: who dominates AI search, per engine and per market.
Know where your event stands in AI search, and what to change
Sponsoring an event rather than running one?
Your prompts.
Analyzed across every AI search engine.
Define the exact queries your target audience asks and see how each AI search engine responds. Who gets mentioned, how often, and in what context.
| Prompt | Visibility | Sentiment | Position | Mentions | Volume | Lang | Tags | |
|---|---|---|---|---|---|---|---|---|
| Which sports events are worth attending in 2026? | 74% | ≈4.1 | ≈ 1.8 | | 🇺🇸EN | Discovery | ||
| Quels sont les meilleurs événements sportifs en Europe? | 47% | ≈3.6 | ≈ 3.3 | | 🇫🇷FR | Discovery | ||
| Welches Sportevent hat die höchste KI-Sichtbarkeit? | 57% | ≈3.3 | ≈ 3 | | 🇩🇪DE | Competitive | ||
| Best marathon events for first-time runners? | 68% | ≈3.8 | ≈ 2.3 | | 🇺🇸EN | Running | ||
| How do I get tickets for the Champions League final? | 61% | ≈3.5 | ≈ 2.7 | | 🇬🇧EN | FootballTickets | ||
| Quali eventi sportivi seguire in Italia nel 2026? | 38% | ≈3.4 | ≈ 4 | | 🇮🇹IT | Discovery | ||
| Which leagues have the biggest global following? | 52% | ≈3.2 | ≈ 3.1 | | 🇺🇸EN | Competitive | ||
| Welche Laufveranstaltung lohnt sich für Einsteiger? | 43% | ≈3.9 | ≈ 3.6 | | 🇩🇪DE | Running | ||
| Which sports events lead on sustainability? | 33% | ≈3.7 | ≈ 4.2 | | 🇺🇸EN | Sustainability | ||
| Who are the official sponsors of the Olympics? | 27% | ≈3.1 | ≈ 4.6 | | 🇺🇸EN | OlympicsPartners |
Custom Prompts
Define the exact questions fans and buyers ask, tailored to your event or sport.
Multi-Engine Analysis
Each prompt runs across ChatGPT, Gemini, Claude, and Perplexity simultaneously, showing how the answers differ.
Market & Language
Run the same prompts across markets and languages to track visibility where your audience actually searches.
Automated Re-runs
Schedule prompts to run daily or weekly so you always have fresh data without manual effort.
From data to action. Every score comes with the fix behind it.
A dashboard tells you the answer is wrong. Spectera tells you which source made it wrong. We track what each model reads when it describes your event and hand back a ranked list of what to correct first, from your own programme pages to the listings and databases you never think about.
The loop
Measure, correct, prove it moved
Measure
Your prompts run daily across ChatGPT, Gemini, Claude and Perplexity. Every answer is stored together with the sources the model leaned on.
Correct
You get a ranked list instead of a dashboard: which source is outdated, wrong or missing entirely, who owns it, and which answers it is shaping right now.
Re-measure
The next period puts the new numbers next to the old ones, so you can show what changed rather than claim you caused it.
What you actually receive
A ranked correction list
Your programme page still shows last edition dates
Three engines answer schedule questions with the previous calendar.
Federation database carries the former event name
Cited in 6 of 10 answers about the series, so the old name keeps resurfacing.
No partner is named anywhere in your programme text
Models have nothing to read, so sponsors never appear in partner questions.
Ticketing listing has no venue or capacity data
Attendance-intent prompts route to a competing event with a fuller listing.
We handle the research, the analysis and the prioritising. Publishing stays with your team, because your programme, your voice and your press relationships are yours.
Events are read from different sources than products.
Generic AI visibility tools cluster citations into product pages, listicles and forum threads. When a model describes an event, it is reading somewhere else entirely. These are the source types we track and rank for you.
Programme & schedule pages
Dates, format, venue and the one-line description models reuse verbatim.
Ticketing & event listings
Third-party listings that answer "can I still attend" long before your own site does.
Federation & results databases
Structured records that models trust more than marketing copy, and that nobody updates.
Trade press & reference entries
The coverage and encyclopaedia entries that quietly set the tone of every answer.
Sponsors get the same list, split into what they can correct themselves and what sits with the property.
One event. A different answer in every market.
Track AI answers market by market and language by language. See how ChatGPT describes your event in Tokyo versus New York, which markets still get an outdated version of your story, and where your sponsors drop out of the answer entirely.
Basketball
Marathon
Football
Surfing
Alpine Skiing
TennisTurn AI search data into a task list. See which sources the answers are built from, correct the ones that are outdated or missing, and watch the next edition move. Then show every partner where they appear in the same answers.
2,000+
AI queries tracked daily
4
AI search engines monitored
200+
Events & partners tracked
real-time
visibility updates
Frequently asked questions
Everything you need to know about the platform.
We monitor responses from ChatGPT, Gemini, Claude, and Perplexity. Our system sends hundreds of relevant prompts daily and analyzes how each model describes your event, your property, and the competitors you are measured against.
No. Most organisers start with their own visibility: how often and how accurately their event, league, or federation is described across ChatGPT, Gemini, Claude, and Perplexity. Sponsor reporting is a module you can switch on whenever partners are attached, not a requirement.
We send a curated set of relevant prompts to each LLM and measure how often your event is mentioned in the responses. The rate is expressed as a percentage, e.g. 'mentioned in 6 out of 10 relevant queries'.
Yes. Measurement on its own does not move an answer. Spectera tracks which sources each model draws on when it describes you, from your own pages and programme data to schedule listings, federation databases, press coverage and reference entries, and flags which of them are outdated, wrong, or missing entirely. You get a ranked list of what to correct first, and the next measurement period shows whether it moved. We handle the research, the analysis and the prioritising. The publishing stays with your team, because your programme, your voice and your press relationships are yours.
Yes. Every edition of your event is tracked as its own period, so you can put this year's mention rate, sentiment, and share of voice directly next to the last one and see whether your content, PR, and website work actually moved the answers.
It shows which thematic contexts your event appears in when LLMs respond to user queries. For example, whether your event is described as the leading industry gathering, as a regional fixture, or only in connection with a specific venue.
It analyzes the tone of LLM responses when your event is mentioned: positive, neutral, or negative. Each score is backed by real example quotes from the models so you can see exactly how your event is being described.
Yes. The Share of Voice metric gives you a direct, side-by-side comparison of your AI search presence against competing events and properties, broken down by LLM, market, and query category.
Yes. Once partners are mapped to your event, Spectera produces partner-specific reports showing mention rate, share of voice against their competitors, and the exact AI passages that reference them. Many organisers use those reports as an argument in renewal and package negotiations.
The same measurement, from the other side. Every event in your portfolio is tracked as its own object, so you can compare the properties you fund against each other on identical prompts, see which ones are actually present when your category comes up, and then see how your brand ranks inside each of those answers against the other sponsors.
More than most brands assume. You cannot change the event, but you do control your own newsroom, partnership pages, campaign content and the trade coverage of the deal, and those are exactly the kind of sources models read. Spectera splits the findings into what you can fix yourself and what sits with the property, so the second half becomes a specific, evidenced request you can take to your partner instead of a general complaint.