Build an AI-Powered Data Analysis Dashboard
Connect your business data sources to an AI layer that automatically interprets trends, generates weekly narrative reports, and alerts you to anomalies, without requiring a data analyst.
Download workflow config (JSON)How the data moves
This is a handoff plan, not an automatic integration. Review outputs before the next step. Unlabeled arrows show order, not a verified data format. Use the capability links to explore tool substitutions.
Step 1
Connect Your Data Sources
Use Make to pull data from your key sources: Google Analytics, your CRM, Stripe, or any tool with an API. Schedule pulls weekly or daily and store raw data in a Google Sheet or Airtable base.
Step 2
Define Your KPI Dictionary
Work with ChatGPT to write clear definitions for each KPI you track, what it measures, what 'good' looks like, and what a meaningful change threshold is (e.g. >10% week-over-week).
Step 3
Run Anomaly Detection
Use Claude to compare current period data against the previous period and your baselines. Prompt it to flag any metrics that changed by more than your defined threshold and explain possible causes.
Step 4
Generate the Narrative Report
Feed flagged anomalies, trend data, and KPI definitions into Claude. Ask it to write an executive summary in plain English: 'What changed, why it likely changed, and what we should do about it.'
Step 5
Visualize in Looker or Sheets
Use the analyzed data to auto-update a Google Sheets or Looker Studio dashboard. The AI narrative appears as a text block at the top of the dashboard above the charts.
Tools
No catalog tool specified
Step 6
Alert and Distribute
Use Make to email the full narrative report every Monday to stakeholders and post the top 3 insights to Slack, tagged with up/down emoji based on the trend direction.
Time Required
5–7 hrs setup / 0 min weekly
Expected Result
A living dashboard that automatically produces a narrative data summary every Monday morning, highlighting KPI changes, anomalies, and recommended actions.
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