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How to build an automated KPI reporting dashboard

Someone on your team spends a few hours every week copying numbers between tools so that everyone else can look at them for ten minutes. The numbers are already in the tools; the work is entirely in the moving. That is a reporting problem rather than an analytics problem, and it is the easier of the two to solve.

Start building free~10 min to first version

What you’re building

An automated KPI dashboard pulls metrics from the tools that hold them, computes the comparisons that matter — week over week, against target, by segment — and publishes the result on a schedule, either as a live dashboard, a Slack post, or both.

Who this is a good fit for

  • Founders rebuilding the same board update every month
  • Teams whose metrics live in four tools and one much-loved spreadsheet
  • Anyone who wants to be told when a number moves, rather than checking

How to build it

  1. Step 1

    Name the metrics and the comparison

    A number without a comparison is not a metric, it is trivia. Say what you want measured and what you want it measured against — last week, target, same week last year. Also say what should wake someone up, because an alert threshold is the difference between a dashboard people check and one they ignore.

  2. Step 2

    Connect the tools that hold the numbers

    Read-only is enough for every source here, and worth preferring — a reporting agent has no reason to be able to write to Stripe. Each connection is scoped when you grant it.

  3. Step 3

    It builds the pulls, the maths and the schedule

    It wires each source, computes the deltas, assembles the dashboard, and sets the schedule and the alert thresholds. The definitions are written down as part of the build — which quietly solves the other reporting problem, where two people compute churn differently and neither knows.

  4. Step 4

    Check the first run against your old numbers

    Run it once and reconcile it with however you were calculating before. Discrepancies here are almost always a definition mismatch rather than a bug — whether churn counts downgrades, whether MRR is net of refunds — and that is a conversation worth having once, in writing, rather than every quarter.

What it does once it’s running

  • Metrics pulled from billing, product analytics and spreadsheets into one view
  • Week-over-week, against-target and segment comparisons computed for you
  • A scheduled post to Slack or email, so the report arrives rather than being fetched
  • Threshold alerts that fire immediately rather than waiting for the weekly run
  • Metric definitions written down once, so everyone is computing the same thing

Tools it connects to

StripePostHogGoogle AnalyticsGoogle SheetsSlackRazorpayHubSpot

What it won’t do

  • It reports; it does not explain. A metric moving is surfaced, the reason is still yours to find
  • Sources with slow or delayed APIs will bound how fresh the numbers can be
  • Deep ad-hoc analysis over large datasets still wants a proper BI tool behind it

Start from a template instead

Each of these opens with the prompt already written. Edit it before you build.

Slack Digest

Daily Stripe, PLG funnel, and product metrics pushed to Slack.

Market & Competitive Intel

Monitor pricing, changelogs, reviews, and competitor signals.

Common questions

Which tools can it pull metrics from?
Stripe and Razorpay for revenue, PostHog and Google Analytics for product, Google Sheets and Airtable for anything you maintain by hand, and HubSpot for pipeline. Most dashboards end up combining two or three.
Can it alert me instead of me checking?
That is usually the more valuable half. You set thresholds in plain language — churn above four per cent, signups down twenty per cent week over week — and those fire immediately rather than waiting for the scheduled report.
Why do its numbers differ from what I calculated?
Almost always a definition mismatch rather than an error — whether churn includes downgrades, whether MRR is net of refunds. Reconciling the first run against your existing numbers is worth doing, and the definitions are then written down so it stays settled.
Does the dashboard update live?
It refreshes on the schedule you set, and alerts fire between runs. For most teams a daily or weekly rhythm is right; a live-updating dashboard sounds better than it is in practice.

Related use case

AI agent for analytics & reporting

Build an agent that pulls metrics from your tools, computes deltas, and reports them automatically.

Build it in the next ten minutes

Start with a sentence. Leave with a working app on its own URL.

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