Monthly tracking of where your brand appears across every major AI platform, how models describe you, and which competitors are gaining ground — with the uncertainty stated honestly rather than hidden behind false precision.
The standard approach is to open ChatGPT, ask a question, screenshot a favourable answer, and paste it into a slide. That proves nothing. Models return different answers to the same question asked twice, vary by account and region, and change with every update.
Proper monitoring means running a consistent prompt set on a fixed schedule, across every platform, recording structured results, and reporting the trend rather than any single output. It also means being honest that this data is noisier than rank tracking, and saying so rather than presenting a screenshot as evidence.
We run this as a standalone service as well as inside retainers, because plenty of teams execute their own AI SEO and simply need a reliable measurement layer they didn't have to build.
A meaningful share of our monitoring clients do their own optimization work. That's a legitimate arrangement and we price it accordingly.
Best for: Teams running their own AI SEO who need reliable measurement without building tracking themselves.
Best for: Teams who want the measurement and the execution capacity from one place.
Four measurement streams, run monthly. Together they answer whether you're gaining ground, and against whom.
Across a fixed prompt set, how often your brand is named in the answer, per platform. The headline number, tracked consistently so movement means something.
What models say about your category, products, and positioning — and where that's wrong. Errors here often cost more revenue than absence does.
Who else is being cited for your prompts, whether their share is growing, and what they appear to be doing differently.
How stable each result is across repeated runs. A citation that appears in one run of ten is not the same as one appearing in nine, and we report the difference.
Structured measurement, honest reporting, and an analyst who explains what changed rather than shipping a dashboard link and disappearing.
Building the benchmark question set from your real query data, sales conversations, and competitor positioning — reviewed and approved by you before anything is tracked.
Running the full prompt set across six platforms on a fixed monthly schedule, with multiple runs per prompt so variance is measured rather than ignored.
Systematically capturing how each model describes your brand, catalogues your products, and positions you against competitors, flagging factual errors.
Tracking up to five named competitors across the same prompt set, so your share is always reported in context rather than as an isolated number.
A written report with the numbers, what moved, what didn't, what we think caused it, and what we'd prioritise next — not an automated dashboard export.
The underlying dataset, yours to keep and re-analyse. We don't hold measurement data hostage to the retainer.
The most valuable finding differs by category — and it's frequently not the headline citation number.
The highest-value finding is usually which competitors get named alongside you in comparison prompts, and whether models describe your pricing accurately.
Product recommendation prompts matter most, and stale availability or pricing in model responses is a common, costly, and fixable finding.
Whether you're named when models are asked who to hire, and whether your specialism is described correctly rather than genericised.
Description accuracy usually outweighs citation share. Large brands are cited anyway; the risk is being cited with outdated or wrong information.
A fixed monthly cycle. Same prompts, same platforms, same methodology, so the numbers are comparable across months.
We build the benchmark question set from real query data and sales conversations, then you review and approve it before tracking begins.
The first full run establishes your baseline across every platform, including competitor share and description accuracy, documented in week one.
The same set runs on a fixed schedule with multiple runs per prompt, capturing variance rather than treating a single output as truth.
A written analyst report on what moved, what didn't, likely causes, and recommended priorities — plus the raw data export.
A dashboard nobody acts on is an expense, not an asset. Every report ends with a specific recommendation, and we'd rather tell you something isn't working than pad a report with favourable noise.
The questions clients ask us most before starting. If yours isn't here, ask us directly on a consultation call.
Reliably enough to act on, yes — but less precisely than rank tracking, and anyone claiming otherwise is overselling. Model outputs vary between runs, differ by account and region, and shift with updates.
We handle that by running each prompt multiple times per cycle and reporting both the result and its variance. A citation appearing in nine of ten runs means something different from one appearing once, and the report says so.
From your existing query data, the questions your sales team actually hears, and how competitors position themselves — then translated into how people phrase things conversationally, which differs substantially from search queries.
You review and approve the set before tracking starts, and it stays fixed so month-over-month comparisons are valid. We revisit it quarterly rather than changing it ad hoc.
ChatGPT, Perplexity, Google Gemini, Claude, Microsoft Copilot, and Google AI Overviews as standard. We can add others where there's a genuine reason.
Perplexity and AI Overviews usually show movement earliest since they lean most heavily on live retrieval.
Yes. It's deliberately available standalone, and a real share of our monitoring clients run their own optimization work internally.
Standalone monitoring typically runs in the low four figures monthly depending on prompt set size and competitor count.
Several tools now track AI mentions and some are decent. The difference is prompt set design, variance methodology, and the analyst layer — a tool gives you numbers, not an explanation of why they moved or what to do.
If you have strong internal capacity to interpret the data, a tool may genuinely be sufficient, and we'll say so rather than selling you a service you don't need.
It happens, and it's exactly why continuous monitoring beats a one-off audit. We flag it in the report, distinguish platform-wide shifts from changes specific to your brand, and adjust priorities accordingly.
Distinguishing 'everyone dropped' from 'you dropped' is one of the more valuable things consistent tracking gives you.
Yes, and it's often the more valuable stream. Being cited with outdated pricing, a discontinued product, or a wrong capability claim can cost more than not being cited at all.
Every report includes description accuracy findings with specific errors flagged and traced to probable sources where we can identify them.
Standalone monitoring typically starts in the low four figures monthly, scaling with prompt set size, competitor count, and how many markets or languages are in scope.
Within a full retainer it's included rather than billed separately. Detail is on our pricing page.
We'll build your benchmark prompt set, run it across six platforms, and show you exactly where you stand — and who's standing where you want to be.
No commitment · 45 minutes · Immediate value