An illustrative approach for a software company: use buyer comparisons to assess AI visibility, content gaps and credible sources, then connect research to demo bookings.
| Buyer questions | Use cases | Comparisons | Integration |
|---|---|---|---|
| Which teams is it for?Roles and use cases | ● | ＋ | — |
| How does it compare?Fit and selection criteria | ＋ | ● | — |
| How does it integrate?APIs, migration and setup | ＋ | — | ● |
| How do we use it?Daily work and collaboration | ● | — | ＋ |
Explain compatibility and setup steps
Link to a product demo booking
Buyer questions
Research focusDemo bookings
Sales pathwayIn this scenario, the company regularly publishes feature updates and receives some search traffic, but rarely appears when buyers use AI to compare software, explore alternatives or assess integrations. Product information is scattered across the website, help centre and sales presentations, making an informed comparison harder than it needs to be.
The proposed work would begin with one product line and a defined customer group. We would identify the questions that influence purchasing decisions before prioritising content and technical changes. The aim is to make the reasons, priorities and evaluation criteria clear, rather than simply publish more general industry articles.
We would organise recurring sales questions into a repeatable research set covering use cases, integrations, deployment, migration and alternatives. The diagnosis would also record key competitors, frequently cited pages and the accuracy of brand information, distinguishing missing product facts from explanations that need to be clearer.
Using that evidence, we would improve comparison pages, use-case pages and essential help content, with clear conditions explaining who the product suits. Relevant pages would lead to appropriate demo bookings. External descriptions would be aligned with the website, supported by source materials and a review process the content team can maintain.
Proposed deliverables include question-level findings, competitor and citation-source analysis, a phased content plan and an initial set of page updates. Each piece would address a specific buying question and identify the product evidence needed from the client. Demo forms and source tracking would also be checked to connect enquiries with the relevant content.
Follow-up checks would reuse the agreed question set and retain the platform, date and answer records to compare brand information, appearances and cited pages. AI referral visits, demo bookings and sales-qualified opportunities would be reported separately. Better question coverage is a signal; its commercial value still needs to be tested against real enquiries.
Start with what buyers are asking, then explain the questions your product can genuinely answer.
— MUHNEY AI · Approach
Our search strategy team will review how your brand appears across AI search, uncover why competitors are being cited instead, and give you a prioritized plan to close the gap.
Request an AI auditIllustrative audit report
Finding 01
Key product information is difficult for AI to cite.
Competitors answer comparison questions more directly.
Product information is not structured for clear citation.
Build authoritative answer pages around high-intent queries.
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