Reporting automation for retail and e-commerce
Store, e-commerce and marketplace sales are pulled from separate dashboards and merged in Excel. The weekly report eats half of someone's Monday.
▶ The solution
I automate the reports that are built by hand today, bring scattered data into one source of truth, and build the dashboards management will actually read.
▶ Use case
All sales channels are combined into one source, and channel, store and category reports update automatically every morning.
▶ Data you need
Point-of-sale data, e-commerce and marketplace exports, and product master data.
The industry's data landscape
In retail and e-commerce, data is spread across point-of-sale systems, the e-commerce platform, loyalty programs and marketplace dashboards. Transaction volumes are high and product ranges wide, so even small improvements in rates add up to a visible difference.
Reporting automation means the numbers someone collects, merges and presents by hand every week or month update themselves. Underneath are three jobs: getting the data into one place, calculating each metric with one definition, and showing the result on a dashboard the decision maker can read.
The math behind it
Annual hours = Σ (hours per report × people × repeats per year)
- Hours per report: time to prepare it once
- People: how many contribute
- Repeats per year: 52 for weekly, 12 for monthly
How I work
- Week 1
Report inventory.
Which report is for whom, built from which source, in how much time, and which one is actually used in a decision. At the end it is clear what gets automated and what gets dropped.
- Weeks 2–3
One source of truth.
The core metric definitions are written down and agreed with the teams involved. Sources are brought together and pipelines that refresh the data on a schedule are set up.
- Weeks 4–5
Readable dashboards.
A small number of dashboards for management and teams, written in code to fit the need, with no BI licence attached. Each has an owner and a purpose, and replaces a report that was built by hand.
- Final week
Handover.
A metric glossary, documentation of the data pipelines and a short training for your team. The system has to run without me; that is the deliverable.
▶ Questions and answers
Reporting automation for retail and e-commerce — what data do you need?
Point-of-sale data, e-commerce and marketplace exports, and product master data.
When is this the wrong choice?
You have one source and a few reports. A well-built spreadsheet or your software's own reports may be enough. Building infrastructure would be an unnecessary cost. The problem is the decision process, not the data. If the numbers are right but nobody acts on them, that is a management issue. A better dashboard won't fix it.
How does this work start?
With a short intro call. I listen to what you need and tell you plainly whether your data is enough for the job and what the first step should be. I reply to every message within 24 hours.
▶ Concepts
Linked to Wikipedia and Wikidata.
▶ Sources
- [1]Wikipedia, Single source of truth, 2026-10. en.wikipedia.org/wiki/Single_source_of_truth
- [2]Wikipedia, Extract, transform, load, 2026-10. en.wikipedia.org/wiki/Extract,_transform,_load
▶ Intro call
Let's talk about your situation.
In a 30-minute call I listen to what you need and tell you plainly how I can help.
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