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Sales

Where are my customers, by area?

The shop’s customers counted per city and drawn where the cities are, then counted into the regions of France, each coloured by its revenue per customer. Needs the geo module. On the synthetic shop (180 customers in twelve cities) and the product’s map of the French regions.

Who pays late, and how late?

The days from each order to its payment, an unpaid one counted up to the last known date; a level by rules, from paid on time to final notice; and the orders to chase. On a synthetic sales dataset: one invented shop, 2024-2025.

Who are my best customers?

How recently, how often and how much each customer buys, cut into thirds; a segment by rules, from champions to lost; what each segment weighs in customers and in revenue; and the champions by name. On a synthetic sales dataset: one invented shop, 2024-2025.

Which orders break my own rules?

Two house rules checked on every order, a zone each: no store or phone order on a weekend, when the counter is closed; and no two orders of one customer on the same day. On a synthetic sales dataset: one invented shop, 2024-2025.

Which days do we sell the most?

Every day’s revenue on a calendar, then the mean revenue of each day of the week. A workshop on dates: a day without an order is a day at zero, not a missing day. On a synthetic sales dataset: one invented shop, 2024-2025.

Where does my revenue come from?

The net revenue of 2025 by category and product: a treemap shows each one’s weight and share at a glance, and the ten products that weigh the most are listed. On a synthetic sales dataset: one invented shop, 2024-2025.

What sells together?

The baskets turned into one column per product: the combinations of the most bought products, and the strongest rules « who takes A also takes B ». Needs the statistics module. On a synthetic sales dataset: one invented shop, 2024-2025.

What is wrong in my transactions?

Three leads side by side: the lines entered twice, the quantities absurd for their product, and the customers whose amounts swing far more than the others’. Each ends on the list of what to look at. On a synthetic sales dataset: one invented shop, 2024-2025.

What do my customers look like?

From order lines to one row per customer: orders, revenue, average basket. Then the segments compared, in a Table 1 and one dot per customer. On a synthetic sales dataset: one invented shop, 2024-2025.