GEO Analysis Report

Fictional example report for Sample & Sons.

Executive summary

Sample & Sons can be understood from its public service content, but a prospective buyer's pricing question remains unanswered in the saved GEO test. The most useful next investment is clearer, supportable answers about engagement scope, pricing approach, and proof. Crawlability and structured data help systems access and interpret the site; they do not guarantee an AI recommendation. Use this report to improve what an answer can accurately say about the business, rather than chasing a score without reviewing the underlying citations.

Business context

A fictional B2B consultancy helping growing service businesses improve operations and customer experience. The primary goal is qualified consultation bookings. The target audience is operations leaders at growing service businesses.

Evidence and findings

Finding 1

Access is a foundation, not evidence of recommendation. All four audited pages are reachable, the sitemap contains four URLs, and the saved robots evidence shows no blanket AI crawler block. This removes an obvious access obstacle within the sampled pages. It does not establish coverage of every crawler or prove that a public AI service has indexed, cited, or recommended Sample & Sons. For an owner, the practical next question is whether the accessible content answers a buyer's decision-making questions correctly.

Finding 2

The saved answerability examples show a specific content gap. The test can answer 'What does Sample & Sons do?' using services evidence. It cannot establish 'How are engagements priced?' from the saved pages. A vague statement such as 'contact us for more information' leaves both visitors and answer systems without a useful explanation. If pricing varies, describe what determines a proposal, what the consultation includes, and when an estimate is provided. A variable-price service does not need an invented fixed fee to provide a clear answer.

Finding 3

Existing attribution should be strengthened with substantive proof. The current crawl already detects an author and publication date on the case study, unlike the baseline. The improvement opportunity is to make the evidence useful: explain the starting problem, the intervention, the context, and how the outcome was measured. Identify the author's relevant role and review the material when it changes. Permissioned, supportable details are more valuable than unsupported superlatives. The report does not establish that authorship alone increases citations or that every page needs a named author.

Finding 4

Service identity can be clearer without changing the underlying offer. Organization schema is present on the homepage; Service schema is not detected in the sampled pages. The current services page also has an FAQ, which is a useful place for concise answers. Add appropriate Service markup only for information visible and accurate on the page. Structured data is an aid to interpretation, not a substitute for clear copy and not a promise of special search-result treatment or AI visibility.

Recommended next steps

1. Priority 1 · Service owner + writer · First week: Publish an approved consultation and pricing-process explanation on services. Suggested structure: who it is for, what will be discussed, what the prospect receives, how scope affects a proposal, and the next step. Keep any timing, fees, and deliverables accurate to the real offer; the example report cannot supply those business facts.
2. Priority 2 · Case-study owner · Weeks 1–2: Retain the existing author and publication date, add relevant expertise and a review date where appropriate, and strengthen the case-study problem and evidence. Link useful claims to their supporting material. If a result cannot be substantiated or disclosed, explain the process without manufacturing a quantified success story.
3. Priority 3 · Developer + content owner · Weeks 2–3: Add valid Service structured data matching the visible service description. Rerun the saved question set after content changes and inspect the generated answer and cited passage, especially the previously unanswered pricing question. Correct inaccuracies before expanding the test to more buyer questions.

Sources and reporting window

• Baseline audit: September 1, 2026, with GA/GSC data from August 4–31.
• Current audit: September 29, 2026, with GA/GSC data from September 1–28.
• Saved services performance and snapshot.
• Saved GEO evidence.

These equal-length, 28-day windows compare two completed audits across the same four pages.

Applying this to your business

List the questions a customer asks before choosing your business: suitability, service area, process, price, evidence, and how to get started. Check whether each has a direct, current, quotable answer on an accessible page. A clinic might explain appointment eligibility; a supplier might explain minimum order requirements. GEO analysis is most useful when it identifies missing or misleading answers you can improve for people as well as systems.

Confidence and limitations

The measurements support the direction of change, not a causal claim. Booking events do not establish revenue or lead quality. Seasonality, channel mix, and measurement changes can affect the comparison. All numbers, business details, and findings are authored examples rather than a live assessment.

How to validate progress

Repeat the same questions against the next saved audit and review answer accuracy, coverage, and whether citations support the claims. A pricing-process answer can be successful without stating a fixed price. Track live AI referrals separately if measurement is available; this controlled answerability test does not measure actual exposure or bookings from AI services. Maintain the content and schema as the offer changes.

Use Chat to ask follow-up questions against the saved report and audit evidence.