AI Search

Be the answer when your customers ask AI.

Ark measures how your brand appears in ChatGPT, Google AI Overviews and other answer engines, then turns the gaps into a practical program to improve visibility.

Discuss AI Search

How discovery is changing

Search results are becoming answers.

A customer can now move from question to shortlist without visiting a results page. The work is to understand what shaped that shortlist and improve the evidence behind it.

01
Ask
The commercial questions your customers put to AI.
02
Compare
The brands mentioned when an answer narrows the field.
03
Cite
The pages and publishers used to support the response.
04
Act
The changes that make your brand easier to understand and recommend.

What the work covers

Measure the answer. Fix what shapes it.

The work stays grounded in real prompts and visible sources. We agree the scope before any large data run.

Prompt-led baseline

We build an agreed set of real customer questions and measure where your brand appears, where it is absent and how the answer frames it.

Brand and competitor visibility

See which organisations are mentioned across the prompt set, how often they appear and the topics where they lead.

Source analysis

Trace the pages, publishers and evidence that shape each answer, then separate useful signals from noise.

Content and technical implementation

Improve the pages and supporting evidence that answer engines need to understand the brand and use it with confidence.

The program

A measurement loop tied to real decisions.

The baseline is a starting point. Each cycle should show what changed, what stayed flat and where the next piece of work belongs.

Define the questions

Agree the prompt set, priority markets and competitor group before measurement begins. The baseline should reflect the decisions customers actually make.

Measure the answers

Capture brand mentions, recommendations and cited sources at prompt level. Every finding stays tied to the answer that produced it.

Prioritise the gaps

Rank the opportunities by commercial value and the work required. This turns a large set of possible changes into a clear order of play.

Improve and repeat

Ship the highest-value changes, watch how the answers move and use the next measurement cycle to decide what earns further investment.

What you receive

A clear baseline and an order of play.

The output is designed for action. Findings trace back to the prompt and source evidence, so teams can see why each recommendation exists.

Visibility baseline

A prompt-level view of where the brand appears, how it is described and which competitors lead the answer.

Source map

The domains and pages shaping the category, with clear evidence for why each source matters.

Prioritised roadmap

The content, authority and technical changes ordered by expected value and effort.

Measurement system

A repeatable way to track the agreed prompt set and show whether implementation is changing the answers.

Questions

It is the work of helping a brand become a useful, trusted source when answer engines respond to customer questions. The work starts with measuring real prompts, then improving the evidence those systems can find and understand.

They overlap, but the unit of measurement changes. SEO often starts with rankings and clicks. AI search also looks at brand mentions, recommendations and the sources used inside an answer. Strong technical foundations and useful content still matter in both.

The scope is set around where your customers are likely to ask questions. That can include ChatGPT, Google AI Overviews and other major answer engines. We agree the engines, markets and prompts before the baseline is run.

Yes. The work can stop at the audit and roadmap, or continue into content, technical changes and ongoing measurement. The delivery model is shaped around the gaps the evidence reveals.

Start with the questions