Dashboards for retail and e-commerce
Sales, stock and campaign data sit in separate dashboards, and managers have to combine them in their heads.
▶ The solution
I build management dashboards from scratch with my own code instead of off-the-shelf BI tools. No limits on design, interaction, data sources or calculations; the dashboard is shaped exactly around what your business needs.
▶ Use case
One dashboard shows sales, days of stock and campaign impact by store, channel and category, with rates calculated correctly.
▶ Data you need
Sales, stock and campaign data plus store 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.
A custom management dashboard is a web application written from scratch around your data and your decisions. Charts, drill-downs, filters, custom calculations, role-based access, mobile views and embedding into your internal portal are designed to fit the need.
The math behind it
Correct rate = Σ numerator / Σ denominator ≠ average(numerator / denominator)
- Example: store A makes 10 sales from 100 visitors, store B 45 from 900.
- The average of the rates is 7.5%; the real conversion is 55 / 1,000 = 5.5%.
How I work
- Week 1
Decisions and users.
Who is the dashboard for, and for which decisions? Which metrics, at what level of detail, on which device? The screens are clear on paper before any building starts.
- Weeks 2–3
Data connections and calculations.
Sources are connected, metrics are calculated with one definition, and the refresh schedule is set up. This is where the numbers under the dashboard are made right.
- Weeks 3–5
Design and build.
The dashboard is built with real users in short cycles. Every cycle ends with a working version that is shaped by feedback.
- Final week
Launch and handover.
The dashboard goes live in the agreed environment and access is set up. How it works and how to update it is documented and handed to your team.
▶ Questions and answers
Dashboards for retail and e-commerce — what data do you need?
Sales, stock and campaign data plus store and product master data.
When is this the wrong choice?
Your current BI tool already meets your needs. There is no point replacing a setup that works. If the tool isn't the problem, a new dashboard won't fix it. Your team wants to keep changing the dashboard itself. If a team that doesn't code wants to add new charts every week, a BI tool's self-service features may fit better.
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, Simpson's paradox, 2026-10. en.wikipedia.org/wiki/Simpson%27s_paradox
- [2]Wikipedia, Performance indicator, 2026-10. en.wikipedia.org/wiki/Performance_indicator
▶ 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.
Book an intro call▶ In other industries