# Decide assortment and price on real demand.

> What people actually buy, in which combination and at what price: from orders, e-receipts and searches across retailers. You see which categories react to promotions, where demand goes unserved, and what a threshold like a free-shipping minimum does to the basket.

From what was really in the basket. Not from a remembered willingness to pay.

## How it works

### 01 Read demand in real purchases

Which items and categories actually get bought, how often, and in which combination. Across retailers, not only in your own numbers.

### 02 Find the gap between demand and range

Where people search with you and buy elsewhere: topics with high demand and thin presence on your shelf.

### 03 Measure price and threshold effects

How baskets react to promotions, multipacks, subscriptions and shipping thresholds. Before and after the change, in the same panel.

## What you get

### Basket structure

Revenue, units and category mix per order, comparable across retailers.

### Basket co-occurrence

Which categories are bought together and which stay consistently separate.

### Demand gaps

Search terms with strong demand and weak presence in your range, benchmarked against competitors.

### Price thresholds and promotions

How promotions, large sizes, subscriptions and shipping thresholds move the basket.

## Why our data wins here

- **7.4B+** Amazon events: orders, searches and carts at item level.
- **E-receipts** Receipts and order confirmations from the inbox, beyond the marketplaces too.
- **Search** Pre-purchase searches reveal demand that no sales report can show.

## A question you could ask tomorrow

Which categories react most to promotions, and which ones bring in new customers?

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Source: https://www.datapods.app/en/use-cases/assortment-pricing