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How to evaluate an analytics vendor: ten questions and a scorecard

Ten questions to ask any analytics or AI vendor before you sign, with a scorecard, whichever product you are considering.

The short answerTen questions to ask any analytics or AI vendor before you sign, with a scorecard, whichever product you are considering.

Ten questions to ask any analytics or AI vendor before you sign, with a scorecard, whichever product you are considering.

Every product here is good at what it is built for. The useful comparison is what each is built for, what it needs before it answers, and who does that work. Facts about each were checked on 24 September 2026 and are sourced at the end.

Ten questions

  1. What does it need in place before the first answer? A warehouse, a data model, a modelling language, a partner? Ask for the list and the typical weeks.
  2. Who does the setup, and who maintains it? Your team, the vendor, or a partner, and what that costs after year one.
  3. Does the AI calculate figures, or choose from computed ones? A language model that writes queries or code can produce a plausible wrong number. Ask what it is allowed to do.
  4. Does every total reconcile to a control figure? Ask to see a bridge that does not sum and what the product does about it.
  5. Can every figure be opened to its rows? An answer nobody can check becomes a debate in the meeting.
  6. What does it cost in the first year, all in? Licences, consumption, implementation, modelling and training, not only the seat price.
  7. How does data arrive, and who holds credentials? A file your systems already export, a scheduled drop, or a live connection with the vendor holding keys.
  8. What happens to the data, and where is it stored? Residency, retention, deletion, and whether names can be replaced with identifiers.
  9. Can we see it on our own data before we sign? A demonstration on a sample dataset tells you little about your own.
  10. What does the tool do when it cannot answer? It should say so. A confident guess does more harm than no answer.

A scorecard

Criterion Weight Option A Option B Option C
What does it need in place before the first answer?
Who does the setup, and who maintains it?
Does the AI calculate figures, or choose from computed ones?
Does every total reconcile to a control figure?
Can every figure be opened to its rows?
What does it cost in the first year, all in?
How does data arrive, and who holds credentials?
What happens to the data, and where is it stored?
Can we see it on our own data before we sign?
What does the tool do when it cannot answer?

How the kinds of tool compare

Kind Time to the first answer What it needs Who builds it
Enterprise data platforms Usually weeks to months: sources integrated, a data model or ontology built, then applications on top Integration work across source systems, a data model, and engineers who build and maintain it Data engineers, often with the vendor's own engineers or a partner
BI suites Usually days to weeks: a data model built, measures written in the tool's own language, reports designed A clean data source or warehouse, a data model, and someone who can write the tool's measures A BI developer or analyst, often in a central data team
Search and AI analytics Usually weeks: a warehouse connected and a semantic model built and tuned so questions resolve correctly A cloud warehouse, a modelled semantic layer, and a team to maintain synonyms, joins and definitions A data team maintains the model the questions are answered from
FP&A and planning platforms Usually months: models built, the ledger and other systems integrated, often with an implementation partner Model builders, integration with the ERP or general ledger, and an implementation project Certified model builders, internal or from a partner
Revenue intelligence Usually weeks: the CRM connected and activity capture set up A CRM kept up to date, activity capture, and sales operations to run it Sales operations with the vendor
Spreadsheets Hours, and the same hours again every month An analyst's time each period An analyst, by hand, every period
Covirage Minutes on a file you already export; set up for you within a week The exports your systems already produce. No warehouse, no modelling language, no data team We map the columns once and set the dashboard up for you

See every alternative page and head-to-head comparisons.

Sources

Facts about other products were checked on 24 September 2026 from the pages below. Product names are trademarks of their owners; Covirage is not affiliated with them.

Questions people ask

Which tool is best?

The one built for your situation. A platform for the whole organisation, a BI suite for a central data team, a planning tool for the budget, and a file-first tool for one desk's recurring question each suit different teams.

What should I ask before choosing?

What each needs before the first answer, who builds and maintains it, whether its AI calculates figures, and the first-year cost all in. [The ten questions](/blog/how-to-evaluate-an-analytics-vendor) are a good start.

Where does Covirage fit?

For the desk that needs to explain why its numbers moved, from the exports it already has, set up within a week, with every figure computed by our tools and checked.