Services
Why are competitors recommended instead of you?
Find out when AI recommends you, when it recommends your competitors - and why.
Work built around one question your analytics cannot answer. We measure how often models mention, cite and recommend you across ChatGPT, Gemini, Claude, Perplexity and Google AI experiences - then work on the reasons behind the number.
Most of that work turns out not to be on your website. Models repeat what they read elsewhere more often than what a brand writes about itself, so the path usually runs through content, entities and the publishers your category is read from.
What it covers
- AI Visibility Audit as the starting point
- Prompt universe and continuous measurement
- AI Share of Voice and competitor benchmarking
- Citation and source analysis
- Brand and entity clarity
- Content optimisation and missing-content creation
- Digital PR into the sources models actually read
How it works
01
Measure where you stand
We build a prompt universe from how your customers actually ask, run it against the major models and store every answer with the sources it used. General and brand visibility are counted apart from the first run.
02
Find the reasons behind the number
For every answer where a competitor is named instead of you, we state what is missing: a fact that is nowhere on your site, a contradiction the model would not risk, or a source you are absent from.
03
Work on site and off site
Content, entities and structure on your site; Digital PR in the publications models actually read. Most of the gap usually sits in the second group.
04
Measure again, on a schedule
The same prompts, re-run over time. Movement, new competitors and drops are visible as they happen, not at the next audit.
What you get
- AI Visibility Audit with a prompt set you can reuse
- AI Share of Voice against competitors, general and brand reported separately
- Source map: the publications that decide answers in your category
- Content changes and missing content, written to be cited
- Digital PR placements in the sources models read
- Continuous measurement with alerts on drops and new competitors
What we measure
- Share of answers you appear in, against competitors
- Citations of your domain inside answers
- General visibility, kept strictly separate from brand-prompt visibility
- Sentiment and context of mentions
Why us?
AI visibility is a young discipline, which makes it easy to sell and hard to measure. This is what our work in it rests on.
- Altavia Kamikaze + K2 · 2024 - 2025AI visibility in client strategies since 2024Organic strategy across 12 international markets in which visibility in ChatGPT, Perplexity and Gemini was part of the plan, not an experiment on the side.
- aisearchinsight.ioWe built the measurement ourselvesBrand visibility reports across five AI engines and four markets, with an audit of how ready a site is to be cited. Every definition in the report comes from our own code.
- getscorra.comMeasured continuously, not onceThe same prompts on a schedule, movement over time, alerts on drops and on new competitors. It powers the measurement inside this service.
- Own researchFindings that changed how we countA fictional brand at 36% visibility that dropped to 0% once brand prompts were counted apart. Citations accounting for 35-48% of brand mentions. Merged name variants moving a share from 2.12% to 3.73%. The details are on our capability pages.