Q.Checkout
Q.Checkout: A cloud-based analytics platform for connecting retail baskets, shopper behavior and promotions. Ranked #19 of 27 in Retail Intelligence by our editors (7.2/10); pricing: Pricing on request; best for retail teams analyzing baskets and shopper loyalty.
At a glance
- Editor score7.2 / 10
- PricingPricing on request
- Best forRetail teams analyzing baskets and shopper loyalty
- Retail data sourcesInternal
- Founded2002
- Facts checked24 Sep 2026
Where it wins
- Connects store and segment product performance with shopper profiles and loyalty.
- Analyzes switching behavior, basket composition, assortment and product ranging.
- Measures promotional incrementality and answers natural-language questions with data.
Where it doesn't
- Depends on retailers' internal transaction data.
- Pricing requires contacting Quantium's sales team.
- Its focus on commercial retail analytics may not fit broader intelligence needs.
Our verdict on Q.Checkout
Q.Checkout helps category, sales, insights and brand teams analyze first-party retail transaction data. It links category and product performance by store and shopper segment with shopper profiles, loyalty status, switching behavior and basket composition. Retailers can use those views to examine assortment and product ranging, identify shopper segments and measure promotional incrementality. The product is aimed at FMCG and CPG teams, with availability listed in Australia, New Zealand, the UK and the US.
The analytics span both product performance and shopper behavior: teams can compare category and product results across stores and segments, then examine how those results relate to loyalty, switching and what shoppers buy together. Promotional incrementality measurement gives the platform a role in evaluating promotions, while assortment analysis addresses ranging decisions. Its AI-native interface accepts natural-language questions and returns data-backed answers, offering another way to query the retailer's transaction data. That combination makes Q.Checkout suited to internal analysis where basket and loyalty questions matter together.
Q.Checkout is presented as self-serve, but prospective customers are asked to contact Quantium, and the pricing model is contact sales. The published product details frame it around retailer first-party data, so organizations seeking analysis from other data sources or a broader intelligence remit may prefer a different product. Its stated audience is mid-market and enterprise, making it a more natural fit for established retail teams with transaction data and defined category or shopper questions. Retailers that want to connect basket composition, loyalty, switching and promotional analysis in one workflow should consider it; teams without internal transaction data or those seeking public, self-service pricing should look elsewhere.
Your product? Our editors can test Q.Checkout in depth and publish a review, labelled as paid · from $149/mo →
Q.Checkout pricing
Q.Checkout fact sheet
| Free plan | Not verified |
|---|---|
| Paid from | Not verified |
| Retail data sources | Internal |
| Analytics focus | Mixed |
| Benchmarking | Not verified |
| Data refresh | Not verified |
| Listed integrations | Not verified |
| Deployment | Cloud |
| Deployment | Cloud |
| Platforms | Web |
| Built for | Mid-market, Enterprise (editorial estimate) |
| Pricing | Pricing on request |
| Website | quantium.com |
| Facts checked | 24 Sep 2026 |
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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
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