#report

Reporting and dashboards

Reports that build themselves. The Monday report pulls pipeline, cash, tickets and orders from where they live, posts itself at 8:00 and links every number to its rows. Dashboards refresh from HubSpot, Sheets, Stripe and your shop on a schedule, not when someone remembers. Before any chart is built, every metric gets one written definition and one source, which is the part that makes the numbers agree.

Our numbers never match. They match once each metric has one definition and one source. That is the first week of every reporting project, and it is written down before a single chart exists.

Typical deliverables

  • Weekly report posted on Monday
  • Live dashboard from HubSpot and Sheets
  • Cash-flow and finance report
  • Marketing report across channels
  • Metric definitions written down
  • Alerts when a number moves

Tools

  • Google Sheets
  • Excel
  • HubSpot

Point of view

How we decide what to automate

Where a wrong number could reach a customer, the AI checks and a person decides. Where the work is only tedious, we automate it fully. Some things stay manual.

Automate fully

  • The Monday reportpipeline, cash and tickets pulled from the sources, posted at 8:00
  • Refresh the dashboards every hour from HubSpot, Sheets and Stripe
  • Flag any number that moved more than 20 % week on week, with the rows behind it

AI checks, human decides

  • Commentary under each chartthe AI drafts it, you edit before it goes out
  • A metric definition changesthe AI rewrites the query, a person checks the history
  • Board or investor numbersprepared automatically, signed off by a person

Leave it manual

  • Deciding which metrics mattera conversation, not a workflow
  • One-off analysis for a decisiona person, with the AI as a fast assistant
  • Reports for the tax advisortheir format wins, by hand if that is what it takes

#systems

Example system

product api · excel · claudeBulk data loader25 hours of manual entry per client dataset, now minutes

Diagram of the Bulk data loader system: 5 steps

Steps

  1. Client export: The client sends a spreadsheet export in whatever shape it comes.
  2. Maps the columns: The columns are matched to the fields the product expects.
  3. Rows that fail validation: Rows with missing or odd values are set aside for a look.
  4. Product API: Clean rows are written into the product in batches.
  5. Imported, with a report: The client gets a report of what went in and what did not.
CRM and RevOps

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