AI & Data Startups (5–30 employees) typically run kpi dashboards as a recurring process. The pain points below are the patterns we see across this audience — not every shop, but the common shape.
What's typically painful
- Metrics live in a dozen tools and have to be combined manually
- The 'live' dashboard is actually a stale screenshot in a slide deck
- Definitions drift between teams (what counts as MRR, when does a deal 'close')
- Drill-down requires bouncing between source systems
Tools you might use
- Amplitude — Analytics
- BigQuery — Data Warehouse
- ClickHouse — Data Warehouse
- Cluvio — BI
- Databricks — Data Warehouse
- Domo — BI
- Dremio — Data Warehouse
- Fathom Analytics — Analytics
How automation usually works here
- Pull metrics into a shared warehouse on a schedule
- Define metrics once with explicit logic instead of letting each tool do it differently
- Auto-refresh dashboards so the latest numbers are always one click away
- Alert on threshold breaches without anyone having to check a dashboard manually
What you can measure
- Decisions made on actually-current data
- Less time hand-aggregating numbers for status meetings
- Consistent metric definitions across teams
- Faster identification of trend reversals
Need help automating this?
Purcell Analytics builds custom KPI Dashboards automation for AI & Data Startups. Schedule a consultation to discuss your specific stack and process.