Sales KPI dashboard Revenue, AOV, concentration, trends
Build a KPI dashboard from an Excel/CSV: revenue, unique customers, top contributors, Top 1/3/10 concentration and monthly trends (MoM).
What you measure
Concrete examples by activity type.
Steering KPIs
Revenue, unique customers, average basket, AOV (if order ID), frequency, top customers/products, margin (if available).
Risk KPIs
Top 1/3/10 concentration, 80/20 Pareto, client dependency, stockouts, promos that kill margin.
A reliable method (no spreadsheets)
RGAnalyzer standardizes dates/amounts, traces exclusions, and computes consistent KPIs on the same clean base.
KPI pipeline
- Import CSV/Excel
- Detect + remap
- Clean + data-quality audit
- KPIs + charts + export
Why it works
Because a KPI is wrong if date/amount parsing is broken. Here: normalization + transparency.
Example use cases
Concrete dashboard examples depending on your activity.
E-commerce / DTC
Track revenue, AOV, returns, top SKUs and export quality to quickly spot margin and conversion levers.
Independent / Services
Track client concentration, month-over-month revenue changes and dependency on a few accounts to prioritize commercial actions.
Retail / Multi-store
Compare periods, stores, areas or teams to spot performance gaps, seasonality and data quality issues.
FAQ
Quick answers about sales KPIs and building a reliable dashboard.
Which KPIs should a sales dashboard include?
Start with revenue, unique customers, basket/AOV, top contributors and concentration. Add margin/profit if present.
Average basket vs AOV: what’s the difference?
Average basket can be computed per line. AOV is per order and requires a reliable order ID.
How do you avoid wrong KPIs?
Normalize dates/amounts, trace exclusions, and always compute on the same cleaned dataset.
When should concentration worry you?
If Top 1 or Top 3 contributes a large share of revenue, dependency risk rises (validate with Pareto).