KPMG at EuroShop 2026: AI & Data Driving Smart Decisions

Our solutions combine data-based location analyses, market potential assessments and psychographic segmentation to provide companies with targeted support for sales optimisation and expansion. White spot analyses reveal untapped market opportunities and new target groups, while market sizing and network optimisation provide a reliable basis for decisions on investments and location closures. 
 

The integration of Sinus-Milieus enables a targeted approach and differentiated campaign planning. Interactive dashboards ensure transparency and efficient resource allocation – both in the B2C and B2B(2C) sector. This creates measurable added value through better market knowledge, greater relevance and sustainable growth.
 

We will be giving a presentation on this topic on the Blue Stage on 24 February 2026 at 2.40 p.m.

Artificial intelligence is changing the way retailers manage their master data. AI-based agents handle recurring tasks such as the automatic detection and correction of incorrect data, the enrichment of missing information and the harmonisation of data from different sources. 
 

Through continuous learning, these agents improve master data quality in the long term and reduce manual intervention. They recognise patterns, suggest optimisations and help to make processes more efficient. The result: fewer errors, greater reliability and a solid database for all business processes.

An AI-supported digital twin shop presents new possibilities for the targeted optimisation of branch layouts and planograms. Virtual simulations allow placements, assortment variants or alternative store layouts to be tested realistically without disrupting ongoing store operations. AI-based shopper personas and simulated shopping routes reveal how customers react to changes and what impact these have on orientation, dwell time and purchasing decisions.

The combination of simulation, scoring logic and clear KPIs allows the effect on sales, out-of-stock risks and operational efficiency to be identified at an early stage. Decisions are prepared based on facts, with processes being improved in a targeted manner and investments in space and product range being secured. New concepts can be tested risk-free in the digital space – with measurable effects on planning reliability, profitability and shopper experience.

Our data cleansing and enrichment solution creates a reliable, streamlined and future-proof database by consistently cleaning up outdated, duplicate and inconsistent master data and enriching it in a targeted manner. Companies reduce their active data records by up to 80 percent while achieving data coverage of up to 95 percent – the basis for sound, faster and economically sound decisions.

The result is noticeably lower operating and maintenance costs, less manual maintenance and stable systems with reduced error and compliance risks – for measurable savings with greater efficiency and transparency.

Trade Data Check creates transparency and security in import and export data. Through standardised analyses of global-good flows, companies identify potential savings and refunds, data inconsistencies as well as tax and regulatory risks – especially in a volatile trading environment with rising tariffs and trade barriers.

Companies reduce customs costs through the targeted use of trade preferences, strengthen export compliance and gain a clear overview of global supply chains. This creates a reliable basis for decision-making for a strategically optimised and future-proof tax strategy.

Cost to Serve is a data-driven ABC analysis. Using dynamic distribution keys created from the company's operating data, the data model breaks down financial transactions along the value chain and by individual products or services. This approach creates cost transparency within the company, provides a detailed understanding of cost drivers and enables measures to be taken in relation to pricing, production, logistics, and product mix. The Cost to Serve model is implemented on the company's own data platform, thereby avoiding additional licence fees. It requires only a few manual entries and can be scaled according to the size and changes in the organisation.