SKU-level basket data from 650,000 consenting shoppers' e-receipts in the UK and US, aggregated weekly to retailer, brand and product with prices, units and buyer penetration.
Data product · Listing updated 11 Nov 2026
United Kingdom
United States
Weekly files every Tuesday for the prior week
About 650,000 panelists, 410 retailers and 2.3 million products
Mid-market, Enterprises
E-receipts shared with permission by members of a shopping-rewards app panel
Receipt parsing and product matching; weekly aggregation with a 30-buyer minimum per cell
Product-level purchase data that shows what shoppers actually bought, and at what price.
Weekly aggregates by retailer and product: units, spend, average selling price, number of buyers, basket penetration and repeat-purchase rate, with each product matched to a brand and a category tree. Retailer-level views show share of wallet and cross-shopping between retailers. Promotions and price changes can be read from week-to-week price movements per retailer.
Receipts come from members of a shopping-rewards app who connect their email or upload receipts and agree to their data being used in aggregated research. Personal details are stripped at ingestion and members can withdraw at any time. Receipt lines are parsed and matched to a product catalogue of about 2.3 million items, with roughly 89% of spend matched to a product. Only aggregates are delivered, and any cell with fewer than 30 distinct buyers is suppressed. The panel over-represents online and younger shoppers, so weights by age, region and household size are applied. Weekly files are published every Tuesday for the prior week.
13 fields as documented by Tillroll Spend Insights.
| Field | Type | Description | Example |
|---|---|---|---|
| week_start | date | Monday of the reporting week | — |
| retailer | string | Retailer name | — |
| product_id | string | Tillroll product ID | — |
| product_description | string | Normalized product description | — |
| brand | string | Product brand | — |
| category_path | string | Category tree path | — |
| units | integer | Units purchased, weighted | — |
| spend | number | Spend in local currency, weighted | — |
| avg_unit_price | number | Average price paid per unit | — |
| currency | string | GBP or USD | — |
| buyer_count | integer | Distinct panel buyers | — |
| basket_penetration_pct | number | Share of retailer baskets containing the product | — |
| repeat_rate_pct | number | Share of buyers purchasing again within 12 weeks | — |
Free sample available on request
The provider sends a sample file so you can test fit and quality before you buy.
Prices in USD, as published by Tillroll Spend Insights
one category, both countries
all categories with SKU-level aggregates
Converted amounts use DataStoa display rates and are approximate. Tillroll Spend Insights quotes the final price, taxes and terms.
Request detailed pricing2 countries across 2 regions.
Time coverage: 2019 to present.
Provider-reported
Latency: Weekly files every Tuesday for the prior week
DataStoa has not audited these figures. Ask the provider how they are measured, or test them on a sample.
The licence is agreed directly between you and Tillroll Spend Insights. This summary is provider-reported; the linked terms prevail.
Not listed: use in commercial products, AI / ML model training, AI retrieval and grounding, redistribution allowed, marketing and outreach. Ask Tillroll Spend Insights if you need any of these.
Aggregated card, receipt and open-banking spend panels for investors
Tillroll builds de-identified consumer spending panels from consented card, e-receipt and open-banking data in the UK and US. Investors and consumer brands use its aggregated, ticker-mapped outputs to track sales trends before companies report.
Also available on: Snowflake Marketplace, AWS Data Exchange
What buyers say about Tillroll Spend Insights. Reviews cover the provider, not only this listing.
from 2 reviews
Our compliance team got complete answers to the due-diligence questionnaire, including consent and de-identification, within a week. The panel churn adjustments are explained in detail. It is not cheap, and the full universe tier is a stretch for us.
Priya S., Head of data strategy, Multi-strategy asset manager
For the large retailers we cover, the panel's quarterly growth lined up with reported like-for-like sales closely enough to be useful ahead of trading updates. Ticker mapping handles brand portfolios properly. Smaller names are noisier, as the coverage notes say.
James C., Equity analyst, Long/short hedge fund