Specialisation
Is the company associated with the right problem and market segment?
AI Visibility for service businesses
Earn a place on the shortlist before a buyer sends the first enquiry.
We measure whether AI models connect your company with the right specialisation, how they describe your experts and why competitors are selected when buyers ask which provider to choose.
One specialisation, one market and the buyer questions that matter to sales. No guaranteed recommendation.
Service-business analysis
From buyer question to reason for selection
Buyer question
„Which company should we choose to implement ERP for a mid-sized manufacturing business?”
1Companies on the shortlist
2Specialisations attributed to each company
3Experts and relevant experience
4Sources supporting the answer
Every finding remains connected to its question, answer, model and measurement date.
„Which law firm handles shareholder disputes?”
„Who implements ERP for manufacturers?”
„Which software house understands fintech?”
Decision mechanics
For services, name recognition alone is not enough.
AI needs to connect a company to the problem, buyer type, location, experience and supporting evidence. A vague specialisation gives competitors a more convincing reason to be recommended.
Experts
Are people, roles and capabilities clearly described and verifiable?
Proof of work
Is experience presented concretely rather than through broad claims?
Sources
Where do models find information about your company and its competitors?
A shared logic
Law firms, clinics and software houses differ in their offers, not in the logic of selection.
Expert services
Specialisation, risk, experience and trust.
- law firms
- consultancies
- agencies
People-led services
Expert profiles, processes, qualifications and reviews.
- clinics
- training providers
- advisers
Technology services
Industry, technology, project type and delivery evidence.
- software houses
- integrators
- IT firms
Credibility
Every conclusion must lead back to data and the method used to analyse it.
Credibility comes from the system view, explicit methodology, evidence trail and clearly stated limits. Every public result should point to the sample, date and underlying source material.
the question, answer, model and date
definitions of mention and recommendation
a map of sources
criteria for when analysis is not useful
Problem signals
How to recognise that you are losing a place on the shortlist.
AI names competitors but omits your company
the model knows your name but misstates your specialisation
competitors receive credit for strengths you also have
expert profiles and proof of work are not used as evidence
category sources do not connect your brand to the subject
sales receives capability questions that your online presence should already answer
Process
From a real buyer question to a plan for improving visibility.
Intent map
Coverage across the buying decision
Active system structure
CohortQuestionCoded criteria
1Option discovery
Which solutions are worth considering?
category · alternatives
2Shortlist building
Which provider or product fits this use case?
segment · specialisation
3Comparison
Option A or B against these criteria?
differences · limitations
4Fit
What works at this scale and budget?
use case · budget
5Trust
Which option has the right experience?
evidence · sources
1. Buying situations
We capture problems, criteria, risks and the language buyers use before choosing a provider.
2. Baseline
We assess presence, descriptions, competitors, reasoning and sources.
3. Priorities
We separate gaps in positioning, content, proof and distribution.
4. Verification
We document the work and compare the next measurement wave against the same core sample.
Next step
Start with one specialisation where buyers compare providers.
We will first assess whether the category and decision value justify measurement.
FAQ
Questions before you decide
Does this work for local services?
It can, when location is a meaningful selection criterion, the purchase has sufficient value and buyers compare several options.
Do we need case studies?
They help, but they are not the only form of evidence. The analysis may show that expert profiles, specialist pages or third-party sources are more important.
Does AI Visibility replace SEO?
No. It relies on some of the same foundations but examines a different part of the decision: how models build an answer, shortlist and rationale.
Does it make sense for a long sales cycle?
Yes, when buyers use AI to discover providers, organise criteria or prepare a shortlist before speaking with sales.
Where should we start?
With one specialisation, one market and questions that matter to revenue. The initial category assessment only qualifies the right scope.