You want this week’s numbers on Monday morning, not a spreadsheet on Wednesday afternoon.
Most of your month goes to collecting and checking data before any analysis starts.
Ad, analytics and CRM numbers for the board or for clients, rebuilt by hand every month.
Sales, stock and service figures live in five systems and one tired analyst.
Numbers from the FP&A Trends Survey, Treasure Data, Gartner and Parseur. The problem with manual reports is not the chart — it is the week spent exporting, cleaning and reconciling before the chart.
of FP&A time goes to collecting and validating data and only 35% to analysis and insight — a split that has not moved in four years.
FP&A Trends Survey, 2024 ↗per week marketing teams spend collecting and managing customer data; 18% spend more than 20 hours.
Treasure Data, cited by Coupler.io ↗per year is what poor data quality costs an average organisation.
Gartner ↗of professionals admit manual data entry has caused costly errors, delays or missed opportunities.
Parseur manual data entry report, 2025 ↗of organisations still use spreadsheets as their main planning application.
FP&A Trends Survey, 2024 ↗Put your monthly volume into the calculator and see hours and dollars.
Automated reporting replaces the weekly ritual of exporting CSVs from every system, pasting them into a spreadsheet, fixing the dates and currencies, reconciling why the CRM and the ledger disagree, rebuilding the charts and writing a paragraph of commentary — with a workflow that does the same thing every night, the same way, and publishes the result before anyone is at their desk. The analysis does not change; the week spent getting ready for it disappears.
We build automation reporting around the systems you already have rather than a new BI platform. A scheduled workflow pulls yesterday’s data from HubSpot, Google Ads, GA4, Shopify, QuickBooks or whatever you run, normalises it into one store in Google Sheets, BigQuery or PostgreSQL, deduplicates it and reconciles totals across systems. Your metric definitions are written once, in code, and calculated identically every run. A dashboard in Looker Studio, Power BI or Metabase reads from the store, a language model drafts the “what changed and why” summary, and for board or client reports a named person approves it before it goes out.
Monday starts with the numbers already there, a mismatch between systems is caught before it reaches a slide, and alerts arrive the hour a metric crosses a line rather than at the end of the month. Automated reports give finance and marketing their analysis time back; what the figures mean, and what to do about them, stays with people.
The run path of a typical reporting workflow. It runs every night and every Monday; a person only sees it when numbers disagree or a summary needs sign-off.
Starts every night at 02:00 and again on Monday at 06:00 for the weekly report; any source can also trigger a refresh on demand.
Fetches yesterday’s data from HubSpot or Salesforce, Google Ads, Meta Ads, GA4, QuickBooks or Xero and Shopify through their APIs.
One schema for everything: currencies converted, dates aligned to your fiscal calendar, campaign and product names mapped.
Writes the clean rows to Google Sheets, BigQuery or PostgreSQL — the single place every report reads from.
Removes duplicates and compares totals across systems: ad spend against the ledger, orders against payouts.
A mismatch above your tolerance holds the report and sends the data owner a Slack message with both figures.
Revenue, margin, CAC, pipeline and whatever else you define — calculated in code from your definitions, identically every run.
A sales drop, a CAC spike or an overdue balance beyond the limit sends an alert to the owner the same hour.
Looker Studio, Power BI or Metabase reads the updated store; the dashboard is current by the time anyone is at a desk.
A language model reads the metrics and their changes and drafts “what changed and why” in plain language, flagged as a draft.
For board and client reports the summary waits for a named reviewer in Slack, with reminders; internal reports go out directly.
Google Slides or Docs template filled with the numbers and charts and exported to PDF for clients.
A question in Slack — “revenue by region last month?” — becomes a checked query against the store, answered with the query shown.
Typical minutes per weekly or monthly report for a small team. Your own numbers go into the calculator below.
Based on 2 h by hand and 10 min with the flow per item, from the table above.
The flow collects, checks, calculates and publishes. People decide what the numbers mean and what to do.
What counts as revenue, a lead or a churned customer is decided by you and written down once.
The flow shows the variance; a person decides what it means and what to change.
Summaries for the board or a client are approved by a named reviewer.
A difference the rules cannot resolve goes to the data owner, not into the report.
Access to dashboards and raw data is set by you per person and per client.
When a system or an API changes, a person confirms the new mapping.
Flip a switch to hand a step to the flow or take it back.
Benchmarks from the FP&A Trends Survey 2024 and Treasure Data’s marketing survey: the hours finance and marketing teams spend collecting and checking data are the hours automated reporting gives back to analysis.
We map the process as it runs today, count the minutes and agree what the flow must never do on its own.
A working flow on your real data, in a sandbox. You see every run and every exception.
Edge cases, approvals and alerts, then the switch-over — with the old way kept as a fallback.
Monitoring, fixes when a vendor changes a format, and a monthly report of hours saved.
Yes. The data is collected and cleaned by the flow and written into your Sheets or Excel file, so the formulas and layout your team knows keep working — they just stop being fed by hand. A dashboard on top is optional.
Anything with an API or a scheduled export: HubSpot, Salesforce, Pipedrive, Google Ads, Meta Ads, GA4, Shopify, WooCommerce, QuickBooks, Xero, Stripe and most helpdesks. For a system without an API we work from its export files.
Nightly by default, hourly where the source allows it and you need it, and on demand from Slack. The last refresh time is shown on the dashboard so nobody reads stale numbers without knowing.
The run fails loudly: a person gets an alert with the error, the report is held rather than published with a gap, and the last good data stays visible. Keeping connectors current is part of support.
It writes the first draft from the computed numbers only — it cannot invent a figure that is not in the store. For internal reports many teams send the draft as is; for the board or a client a named reviewer approves it first.
A weekly report from two or three sources typically runs in a few weeks: a week to agree metric definitions and connect the systems, then parallel runs against your manual report until the numbers match.
That is why reconciliation runs before publishing: totals are compared across systems and a mismatch holds the report. During launch the automated report runs alongside your manual one until both agree.
Describe it in two sentences — we reply within a day with a workflow sketch.
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