Updated 5 October 2026.
A product demonstration should establish whether your team can use the measurement in its day-to-day work. This checklist covers acceptance before purchase. For a broader product comparison, use our main guide to AI visibility monitoring tools.
Semly publishes this guide and provides one of the products a buyer may evaluate. This is a proposed evaluation process, not an independent performance ranking.
Define the acceptance conditions before the demonstration
Write down the questions, market, language, AI systems and brands your team needs to analyse. Record which conditions are essential and which are optional. A broad topic database and monitoring your own questions support different tasks; compare their measurement methods separately.
Ask the supplier to demonstrate the agreed scope in the plan you would actually buy. Do not infer availability from a generic product page.
Check evidence, not only a score
For one sample result, ask to see:
- The question, date and measurement settings.
- The full answer or the evidence made available by the product.
- How the brand and competitors were recognised.
- Any linked sources, with mentions and citations distinguished.
- The handling of missing or failed observations.
A dashboard should let the reviewer understand what a metric counts. If the underlying evidence is not available, record that limitation rather than assuming every classification is correct.
Check history and changes to the sample
Ask what happens when you rename a brand, add a competitor, change a question or switch a market. Establish whether historical results are recalculated, retained or separated. Find out how long the plan retains evidence and whether you can identify gaps in collection.
Treat a change in the measurement configuration as a change in the sample. It should not silently become a claimed improvement in visibility.
Check exports and team handover
Test a small export and a handover to a second reviewer. Assess whether another person can understand the scope, dates, definitions and evidence without attending the original demonstration.
Confirm user access, responsibility for approving updates and the destination of any content prepared by the platform. A saved draft, a generated article and a published page are different deliverables.
Record cost and acceptance
Use a simple decision table:
| Area | Requirement | Evidence from the demonstration | Decision |
|---|---|---|---|
| Coverage | Agreed questions, markets and systems | Settings and sample observations | Accept / clarify / reject |
| Evidence | Inspectable answer and classification | Opened sample result | Accept / clarify / reject |
| History | Documented retention and configuration changes | Demonstrated history | Accept / clarify / reject |
| Handover | Usable export and team access | Reviewed sample export | Accept / clarify / reject |
| Cost | Same scope and billing terms | Current written offer | Accept / clarify / reject |
This is a proposed checklist. It does not claim that every platform implements these features.
Compare current costs for the same brands, questions, markets, systems, users, history and content workload. Include taxes, billing periods, additional usage and cancellation terms. Do not rely on old prices quoted in a ranking.
Before acceptance, list unresolved requirements and an owner for each. Buying a monitoring tool does not guarantee that an AI system will recommend the business.
