AI Analytics Reporter
marketing-specific analytics; Reporting Agent goes broader
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AI Reporting Agent
Pulls data from across the business - sales, customer success, finance, operations - and turns it into the reports your team, your board, or your investors actually read. Less dashboard, more narrative. Reads the numbers and tells the story they tell.
What this agent does
The job description
- Pulls data from defined sources: CRM, billing, product analytics, finance tools, project tools
- Reconciles cross-source inconsistencies (sales says X, billing says Y) and flags them honestly
- Builds weekly internal digests: what moved this week, what changed, what to watch
- Builds monthly business reports: revenue, retention, pipeline, capacity, key metrics with commentary
- Builds quarterly board or investor updates with narrative and supporting data
- Generates ad-hoc reports on request: "show me retention by acquisition channel", "what is the trend on average deal size"
- Maintains a source-of-truth report library so historical reports stay reproducible
Skills
What this agent is good at
Reading multiple data sources and reconciling themTranslating numbers into narrative without losing accuracyRecognising when a number is meaningful versus when it is noiseKnowing the difference between a board-ready summary and an operational dashboard
Integrations
Where this agent plugs in
Spreadsheets (Google Sheets, Excel)Data warehouses and BI toolsCRM, billing, product analyticsDocument tools for report deliverySlack or Teams for digests
Custom integrations to other tools are scoped during discovery.
"Monthly board pack is ready for your review. Headlines: revenue up 12% month over month, retention flat at 92%, pipeline coverage at 3.2x quota for next quarter. The one number I want to flag honestly: average deal size is down 8%, driven entirely by two larger-than-usual deals last month creating a high baseline. The trend over six months is actually flat. I have included that context in the commentary so the board does not draw the wrong conclusion. Two reconciliation gaps: a small mismatch between Stripe and the CRM on three deals, both flagged for finance to resolve."
Who hires this
Who this fits
- Founders running on vibes who need to start running on numbers
- Small teams without a dedicated data or finance person
- Businesses preparing for board meetings, investor updates, or due diligence
Honest limits
What this agent does not do
- Does not change settings, run experiments, or modify data in any source system
- Does not present numbers without traceability to source
- Does not spin bad numbers as good news
- Does not build dashboards (those are someone else's job); produces narrative reports
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