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Product pricing control

Which products need a price update, and who owns them? Price changes, markups and sales impact in one report.

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A real project. This public demo has been recreated with fictional data.

Product pricing report

Anonymous trading company · September 2026 / September 2025

Demo · all data is fictional
Preparing demonstration data…100,000 demonstration products
More filters

Full demonstration catalogue

Matching products100,000of 100,000 in the catalogue
Matching prices46,888Matching share: 46.9%
Different prices46,330Prices to update
Non-comparable prices6,782Change unavailable

Every summary, chart and CSV uses the same selection. Pagination only limits the visible table rows.

How should I read these metrics?

“Updated” in this demo means that two positive comparison prices match to the cent. It is not a last-update date. Price change = new / previous − 1. Missing or zero bases are non-comparable. Matching share uses all selected products, including non-comparable ones. Markup = selling price / cost − 1; actual unit selling price = turnover / quantity sold. Margin = gross profit / turnover.

Price matching by product manager

Lowest matching share first. Select a manager to filter their products.

Price matching by product manager
Product managerMatching productsMatching pricesDifferent pricesNon-comparable pricesMatching share
16,5022,79012,5921,12016.9%
16,5024,89110,4911,12029.6%
16,5016,8518,5281,12241.5%
9904534716645.8%
16,5028,3787,0051,11950.8%
16,50210,8964,4891,11766%
16,50112,6292,7541,11876.5%

How far and in which direction prices moved

Chart data table
Change intervalProduct countShare
Down ≥5%5,7925.8%
Down 2–<5%5,7395.7%
Down 1–<2%5,7135.7%
Down <1%5,8445.8%
Matching price46,88846.9%
Up <1%5,8585.9%
Up 1–<2%5,8545.9%
Up 2–<5%5,8185.8%
Up ≥5%5,7125.7%
Change unavailable6,7826.8%

Configured pricing and actual sales

Configured prices: products with a valid cost. Actual markup: sold products with a positive cost only. Unit selling price is calculated from turnover and quantity.

Minimum-price markup

Retail-price markup

Chart data table
Markup intervalMinimum priceRetail priceActual sales markup
<0%001,955
0–<10%000
10–<20%24,41409,145
20–<30%48,823011,410
30–<50%24,4134,40423,138
50–<75%054,25929,069
75–<100%038,98717,189
≥100%000

Where attention is needed

Select a name in the table to apply that filter.

ProductMatching productsMatching pricesDifferent pricesNon-comparable pricesMatching share
10,0044,6764,67765146.7%
9,9874,6854,64365946.9%
9,8144,6474,49467347.4%
10,0284,6534,68768846.4%
9,8824,6104,59068246.7%
9,9454,6914,53571947.2%
9,9784,6744,63866646.8%
10,1214,7984,63169247.4%
9,9064,6494,60964846.9%
9,8954,6094,61067646.6%
4401962162844.5%
Demo · all data is fictional · September 2026 / September 2025

The task

A CSV with approximately 7 million rows needed to be broken down by product manager, highlighting price differences and pricing by manufacturer and product group.

The solution

An HTML report brought together product manager summaries, price comparisons, markup analysis and sales impact. Filtered product lists helped prepare price update work.

This public example

This recreated report contains 100,000 fictional products. The original project size provides context; this demo is not a 7-million-row performance benchmark.

Download this HTML

One file with a 100,000-product generator, charts and controls. Works without an internet connection.

Download this HTML

A real project. This public demo has been recreated with fictional data.

I want a similar report