GEO Tools in 2026: Comparing Claims, Coverage and Reporting Limits

What changed in 2026, and what GEO measurement still misses

Google announced its dedicated generative AI performance reports on June 3 and said they were available worldwide from August 31. The Search report covers impressions from AI Overviews and AI Mode, with breakdowns by page, country, device and date. A separate report covers generative AI in Discover. The Search report does not give teams a list of the prompts behind each impression or a separate measure of clicks and conversions attributable to those appearances. Google also notes that sites with insufficient impressions may not see the dedicated report.

That is a measurable step beyond treating all AI search activity as an invisible part of Web Search. It is not a complete attribution system. MOCOBIN’s broader on-page SEO guide addresses the fundamentals that remain necessary, while Google’s report documentation establishes exactly which Google AI metrics are available.

There is another relevant change. In its October 13 publication, Semrush reported different patterns of brand mentions and citations between the UK and US, and among ChatGPT, Gemini, Google AI Mode and AI Overviews. Semrush’s published methodology explains that the analysis is organised by market, month, industry and platform. It is vendor-produced research, not an independent audit of all AI responses. Its useful implication is narrower: a single global GEO score can hide differences worth investigating.

What this comparison can verify

The first distinction is methodological. A vendor’s documentation can establish what it advertises, its published subscription terms and the reporting controls it describes. It cannot establish that the product consistently captures accurate answers for a particular brand, language or country. That requires a reproducible test using an actual account.

Evidence and scope

This review checks the public descriptions and plan conditions for BuildSOM, Profound and Semrush, alongside Google’s own reporting guidance. It does not claim to have run prompts inside any of the three paid platforms. Product features and entitlements may change without notice, and a quoted price may depend on billing term, country, access level or negotiated contract.

The comparison therefore separates advertised capability from observed performance. Where a provider has not made a term sufficiently clear in accessible documentation, it is treated as a question for the sales or trial process, not filled in with an estimate.

BuildSOM, Profound and Semrush: what the public evidence shows

These are not scores for product accuracy. The descriptions are based on BuildSOM’s website, Profound’s published plans and Semrush’s toolkit documentation.

The cost comparison needs a common unit

The old article quoted USD 229 for BuildSOM, USD 665 for Profound and as much as USD 1,030 for Semrush. Those numbers were attributed to the unsubstantiated test and cannot be retained as comparable prices. In the public Semrush pricing view checked for this revision, the combined SEO and AI Search Starter plan was advertised at USD 165.17 per month when billed annually, with 50 custom prompts tracked daily and one domain for AI brand performance. The monthly billing rate and other plans differ.

Profound’s public pricing page, as viewed during this review, described a limited free trial and a custom-priced enterprise offer. BuildSOM publishes plan information, but the terms exposed through its public pages vary by plan and regional presentation. Neither should be assigned a universal price from an old screenshot or an unverified account configuration. Request the exact bill for the required prompts, languages, regions, brands, seats, exports and retention before comparing vendors.

Model coverage is not one yes-or-no feature

A platform may include an engine in its market-level research but not in a customer’s daily prompt tracking plan. Profound’s public trial lists ChatGPT, Gemini and Google AI Overviews, while its enterprise capability list includes additional engines such as Google AI Mode and DeepSeek. Semrush distinguishes its prompt database, brand performance reports and custom prompt tracking, each with its own platform coverage and update cycle. BuildSOM’s advertised platform list also needs to be checked against the subscribed tier.

Ask the vendor to show one actual report for the exact engine and location you need. A marketing page listing eight engines does not establish that all eight are covered for every subscription or that answers are captured with equivalent methods.

Location and language cannot be assumed from a platform list

Hong Kong is a particularly useful stress test because region, written Chinese, Cantonese-language use and English-language queries are not interchangeable settings. Two prompts that look like translations may imply different products, audiences or purchasing contexts. The same concern applies when reviewing Japanese and Korean campaigns: the relevant variable is how the prompt is issued and collected, not a general claim that one market is harder to optimise for.

If a vendor claims multilingual support, request a sample showing the actual prompt text, interface language, selected region, response timestamp and cited sources. A translated dashboard label is not evidence of native-language answer collection.

History matters only when it is auditable

The previous article stated that BuildSOM retained 360 days of data and ranked the vendors by historical coverage. That comparison is withdrawn because the plan-level evidence was not established. A useful retention promise specifies the number of days, the granularity of saved responses, whether screenshots or source URLs are archived, and what happens after a downgrade. Reports without the underlying response or collection date can be difficult to review when an AI system changes its output.

Which product might fit the workflow?

BuildSOM: consider it for a bounded multilingual pilot

BuildSOM’s product positioning makes it a candidate when the immediate question is whether a set of branded and commercial prompts can be monitored across the desired AI services. It should enter the shortlist only if the relevant plan supports the exact locations and languages. There is no verified basis here for calling it the most accurate, cheapest or best-performing product.

Profound: consider it when evidence must travel across teams

Profound’s enterprise proposition is more relevant when several teams need to review shared response records, manage access and export data into internal reporting. Its published trial can help assess the interface, but the restricted duration and scope should not be mistaken for proof of long-term consistency across regions. Enterprise terms need a written proposal.

Semrush: consider the cost of the entire search workflow

Semrush is worth evaluating when an organisation already uses its keyword tracking, competitive research and site audit functions. Its AI reports may reduce the friction of bringing new metrics into an established process. Yet this is a workflow argument, not proof that Semrush measures every AI engine more accurately. Check which AI-specific features sit inside the proposed Semrush One plan and which require another subscription.

There is no responsible overall winner from documentation alone. A purchasing decision needs evidence about the intended market and a repeatable way to inspect errors.

A practical test before committing to a GEO subscription

I would begin with the reporting question, not the vendor demonstration. Decide what an editor or client must be able to answer at the end of a month. Is the priority whether Google AI features display a page, whether a brand is mentioned in ChatGPT, whether a competitor is recommended, or whether AI referrals convert? These are separate measures and may require different tools.

Set the comparison conditions first

• Define a small, fixed set of prompts from genuine customer questions, including branded, unbranded and comparison intent. Keep the exact wording.
• Record target country, language, engine and whether the test uses an account or personalisation. Do not mix environments within a single comparison.
• Require the vendor to explain response collection, freshness, duplicates, citation matching and how unavailable results are handled.
• Compare export format, response-level evidence and retention rather than dashboard appearance alone.
• Price the total requirement, including additional regions, users, domains, prompts and access to older data.

Run repeated observations, then reconcile the disagreements

Use the same prompt set on comparable dates across trial accounts, preserving raw outputs or screenshots when permitted. Compare the presence of brand mentions, linked sources, recommendation context and false attributions. When a platform flags a citation that a manual check does not show, record the mismatch instead of treating one reading as conclusive. No particular minimum such as 15 prompts per region is an established industry benchmark; sample size should follow the decision and the available budget.

Keep collection timestamps. Some differences will be caused by the systems changing between checks, rather than by a faulty tool. The objective is to learn whether a vendor’s data is sufficiently repeatable and inspectable for the decision you are making, not to certify the answers as permanently stable.

What should change on the website itself?

Google’s May 15, 2026 generative AI optimisation guidance describes GEO and AEO as industry labels while stressing that ordinary Search best practices remain the foundation of visibility in Google’s AI features. Google does not require an AI-specific schema type, an llms.txt file or specially chunked text to appear in AI Overviews or AI Mode. Pages still need to be indexed and eligible for a Search snippet to serve as supporting links.

Fix factual and access problems before chasing a mention score

For a product comparison or services page, that means keeping claims traceable, dates and terms accurate, important text accessible and commercial relationships clear. These steps improve the page for visitors and make an inaccurate AI summary easier to diagnose. They do not guarantee that a model will cite the page, and a rise in citations should not be presented as a verified ranking factor or direct conversion gain.

When a tool reports an omitted brand, check whether the source page is accessible and whether the requested information is actually there. Then compare the answer against independent references. Adding repetitive definitions or dozens of prompt-targeted pages without distinct user value is not a substitute for resolving those problems.

The reporting decision that remains open

A site with useful Google AI Search Console data may not need a commercial tool just to learn which of its pages received AI impressions. Conversely, Google’s report cannot measure a brand’s appearance in ChatGPT or Perplexity, or explain which competitor was recommended for a particular prompt. That is the gap a specialist service may help fill. It still needs independent checks before its scores guide significant spending.

For multilingual teams, inspect one market at a time

Before aggregating an English, Cantonese, Japanese or Korean dashboard into one executive chart, verify that each observation represents the intended market and language. Otherwise, a movement in an overall score may reflect a change in the prompt mix rather than a change in what audiences actually see.

The next sensible action is therefore a measurement specification: define the engines, prompts, markets, response evidence and business outcomes the team needs. Only then request matching demonstrations and quotes. A more expensive dashboard without verifiable records is not a stronger GEO strategy.