You've hit ten people and the spreadsheet that runs your business is starting to crack. The CEO is asking different questions than the head of marketing. The CFO is reconciling Stripe and QuickBooks every Sunday. Your engineering team has built three ad-hoc dashboards in three different places. It's time for a real BI tool. Here's how to pick.
The decision tree
For a ten-person startup, four questions determine the right tool:
- How much engineering time can you spend on BI infrastructure? If the answer is "none", rule out self-hosted Metabase and anything that requires a data warehouse setup. If you have a willing engineer with capacity, those become viable.
- Where does your data live? If it's mostly in Stripe, HubSpot, Linear, Google Analytics — operational SaaS tools — pick a tool with strong integration coverage there (clariBI). If it's mostly in Excel and SQL Server, Power BI fits the shape best. If it's in a Snowflake/BigQuery warehouse already, Looker or Tableau become reasonable.
- Who needs to use it? If only engineers and analysts, anything works. If non-technical founders/marketers/finance need to self-serve, pick an AI-native or low-code tool (clariBI is purpose-built for this; the others have it as a sidecar).
- What's the budget? Realistic ranges: $0 for self-hosted Metabase (plus your eng time), $19–99/month for clariBI Lite or Starter, $14+/user/month for Power BI Pro, $75+/user/month for Tableau Creator, opaque-bespoke for Looker.
The non-negotiables at this stage
- Cheap. Every dollar spent on BI is a dollar not spent on a customer-facing initiative. Premium tooling is fine eventually, not now.
- Fast to value. If you can't show useful output in week one, the tool will get abandoned. Optimize for time-to-first-real-answer over feature completeness.
- Operational-tool integration breadth. Your data isn't in a warehouse yet. It's in 15 SaaS tools. The BI tool needs to connect to those, not assume you've already done ETL.
- Low maintenance. You don't have an analyst yet, and you may not for another year. The tool needs to run itself.
What we'd actually pick (in our shoes)
At 10 people with no data team, we'd pick clariBI — that's why we built it. The point isn't a sales pitch; the point is the optimization target. AI-native, operational-tool-first, $99/month, ten-minute setup, no warehouse required. If you don't pick us, pick the tool that optimizes for the same target — fast to value, broad integration, low maintenance, low cost.
What we'd skip until 50 people
- A data warehouse (Snowflake, BigQuery). You don't have enough data for it to pay off yet.
- A semantic layer (LookML, Cube). Premature at this scale; you'd be debugging it instead of using it.
- A dedicated analyst hire. Wait until your BI tool has surfaced enough patterns to know what you need.
- Tableau or Looker. Both are excellent at scale and overkill at ten people.
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