Solutions / Reporting digest

Automated reporting digest

A short written digest of what changed in your numbers, why it changed and what needs a decision — delivered every Monday instead of a dashboard nobody opens.

Analytics Internal LLM
A digest, not a dashboard
read in two minutes
Anomalies explained
with the likely driver named
Same time every week
in Slack or email
Who it is for

Teams with dashboards that nobody opens and a weekly report that one analyst assembles by hand.

Short answer

The system pulls your metrics on a schedule, finds what moved beyond normal variation, attributes the movement to the segment or channel driving it where the data allows, and writes it up in plain language with the chart attached. Numbers that merely wobbled are left out, because a digest that reports everything is a dashboard with extra steps.

The problem

The dashboards exist, nobody opens them, and the weekly report still eats an analyst’s Monday.

01

Dashboards need someone to go looking

A dashboard answers a question you already thought to ask. Nothing arrives to tell you that something moved, so problems are found late or by accident.

02

Assembling the weekly report is skilled work wasted

Pulling numbers, pasting charts and writing commentary takes an analyst most of a day, and it is the least valuable thing they do all week.

03

A number without a cause is not actionable

Knowing revenue fell nine percent starts the work rather than finishing it. The useful part is which segment, which channel, and whether it is normal for this week of the year.

How it works

From trigger to result, step by step.

01

Agree the metrics that deserve attention

A short list per audience with owners and definitions. A digest of forty metrics gets skimmed and then ignored, which is exactly the failure mode we are replacing.

02

Learn what normal variation looks like

Seasonality, weekday patterns and each metric’s usual noise band from your own history, so a seven percent Tuesday dip is not reported as an incident.

03

Explain movements, not just detect them

When something moves beyond its band, the system breaks it down by segment, channel and product to name the likely driver — and says when the data does not support a single explanation.

04

Write it for the audience receiving it

The operations digest and the executive digest come from the same data and read nothing alike: different metrics, different depth, different length. One digest for everyone is read by no one.

05

Deliver on a schedule and prune by feedback

Slack or email at a fixed time, with charts attached and a link to the detail. Items marked unhelpful are dropped, so the digest gets shorter and more relevant instead of accumulating.

Before / after

What changes on the ground.

Today, by hand
×Dashboards that nobody opens
×An analyst’s Monday spent assembling a report
×Normal weekly noise reported as a problem
×Movements found without their cause
With the automation running
›A written digest arriving on schedule
›Only genuine deviations reported
›Movements broken down to the driving segment
›Different digests for operations and leadership
What you get

Delivered, not demoed.

›An agreed metric set per audience with owners and definitions
›Baselines that account for seasonality and weekday patterns
›Anomaly detection with segment-level breakdown of each movement
›Written digests in Slack or email with charts and links to detail
›A feedback loop that prunes items nobody finds useful
Built with

We build in your stack rather than moving you onto ours. The list below is what this solution most often connects to — other systems are a scoping question, not a blocker.

Claude Python PostgreSQL BigQuery Metabase Slack n8n GA4
Time to production4–6 weeks
Build priceFixed price
First stepFree mini-audit
Honest limits

When this is not the right solution.

·If your underlying data is unreliable, an automated digest broadcasts that unreliability weekly to everyone. Fix the pipeline first.
·With one product and one channel, a two-line message and a chart do the job, and a system is overkill.
·If nobody acts on the current weekly report, automating it will not change that. The problem is ownership, not production time.

Questions we get about this one

It breaks movements down by segment, channel and product to name the most likely driver from the data. Where the data cannot support one explanation it says so, which is more useful than a confident guess.

Bring us the process that hurts.

The mini-audit is free: we take your version of this process apart and tell you plainly whether automating it pays. If it does, you get a scope and a fixed price.