Assortment

Create customer-led assortment recommendations that reflect real customer behaviour

The opportunity

Assortment decisions may look data-driven on the surface, but too often they’re still built on averages and assumptions rather than real customer behaviour. Without science-led decision-making, retailers struggle to create a truly compelling customer offer - making it harder to stay competitive and deliver the right range, in the right place, at the right time.

Decisions rely on broad averages, not granular customer behaviour
Customer offers lack relevance, limiting differentiation and competitiveness
Ranges are shaped by constraints and inputs, not optimised outcomes
Opportunities to improve performance are missed through lack of optimisation

How we help

dunnhumby helps retailers create more compelling, competitive customer offers by replacing assumption-led decisions with science-driven, customer-centric decision-making. Using advanced, retailer-built data science and AI, we optimise every assortment decision - connecting customer insight, commercial priorities, and real-world constraints.

Combine loyalty and EPOS data to understand customer behaviour at store level
Use impact science to quantify the commercial impact of every decision, balancing risk, opportunity, and performance
Generate AI-powered, space-aware recommendations optimised for customer and business outcomes
Align teams and suppliers around a single, actionable view of category performance

Get ranging decisions right first time

Make changes to your assortment with a clear view of how customers will respond, reducing the risk to sales and loyalty.

Reduce the need for manual input

Automate analysis, recommendations, and workflows, cutting manual effort and freeing teams for higher-value work.

Make decisions with confidence

Understand which products drive decisions in each store, ensuring that delists and additions are based on real evidence.

Create ranges that work

Generate planograms that work as well in-store as they do in principle, reflecting actual space, fixtures, and behaviours.

Case Study

Simplyfying choice without sacrificing sales

At one Latin American wholesaler, discussions about range reduction had become subjective and difficult. dunnhumby used behavioural data to identify need states, reduce duplication, and uncover significant private label opportunities.

44% SKU reduction
99% sales retained
100% customer needs maintained
$3.6M private label opportunity

Read the case study

Our impact

2-5%

like-for-like sales uplift from coverage optimisation

10x

average return on investment

50%

efficiency savings through automation

reduction in planogram build time

Analyst recognition

A Sample Vendor in the 2026 Gartner® Hype Cycle™: For Retail Assortment Management Applications in Hype Cycle™ for Retail Technologies

Thought leadership

14 July ‘26

EMEA Consumer Trends Tracker

Explore the EMEA Consumer Trends Tracker for Summer 2026 from dunnhumby. Discover the latest consumer shopping behaviours, retail trends, and market insights across Europe, the Middle East, and Africa.

18 February ‘26

The future is brewing: Coffee trends redefining 2026

Explore 2026 coffee trends with insights from 50 million global shoppers. Discover sales shifts and growth opportunities for retailers & CPGs.

20 November ‘25

Differentiation, loyalty, and growth: winning with private brands

At this year’s Global Partner Summit, we explored how private brands are evolving and helping retailers strengthen loyalty and boost growth.