Clean data is the key to retail success: how AI makes the difference
03/10/2025
Omnichannel is no longer a choice, but an essential condition for any retail strategy.
Customers move seamlessly between physical and digital, switching from an app to a store, from an online review to a real shelf, expecting a consistent, smooth, personalised experience.
In this context, data – and especially product master data – becomes the crucial touchpoint, the silent yet essential backbone that allows services to truly meet expectations.
In recent months, as the spread of AI accelerates the development of more and more sectors, we’ve noticed a profound shift in how retail and grocery companies view data.
If in the past product master data management was seen almost as an accessory function, confined to technical or IT departments, today it has become a strategic hub that embraces sales, logistics, marketing, and customer experience.
In an omnichannel model, no innovation – whether dynamic promotions, personalised pricing, predictive analytics, or automated replenishment – can work without a clean, integrated, consistent data foundation.
Every day, companies face new challenges: shrinking margins, rising operating costs, and ever-higher consumer expectations. In this scenario, the quality and centralisation of master data become key to reducing inefficiencies, simplifying processes, and cutting errors and waste.
Unfortunately, many retailers are still a long way from achieving this ideal. It’s not unusual, for instance, for the same product to be recorded with different codes by two affiliated stores – Milan uses one code, Florence another. The result is duplication, reporting errors, supply chain misalignments, and even e-commerce disruptions. The hidden costs of poor data management are enormous, yet still widely underestimated.
Head offices are now progressively centralising the management of product codes, promotions, and pricing, particularly for affiliated stores. This is no longer about exercising control, but about making growth and innovation orderly and sustainable, ensuring consistency and quality of information across all channels.
In this context, Artificial Intelligence is emerging as a decisive resource. It’s not just about predictive algorithms or chatbots, but about a genuine shift in the way data is managed and harnessed. Today, AI can automatically analyse master data, spot inconsistencies, recommend merging duplicate codes, highlight pricing anomalies, suggest intelligent product clusters, and even generate compelling text descriptions for e-commerce and apps.
The impact is twofold: it not only enhances data quality and consistency, but also cuts down the time spent on manual, repetitive tasks, freeing up resources for more strategic activities. In this sense, AI is far more than a tool – it is a catalyst for a new way of doing retail: more agile, more intelligent, and more closely aligned with the real needs of the end customer.
But there’s another point worth highlighting: the retail world has always been fragmented, with each chain, store and department often relying on different software and suppliers.
This adds increasing complexity around compatibility, updates, security, and maintenance. Managing servers and applications in a fragmented way drives up costs, slows down response times, and leaves companies exposed to systemic risks that are difficult to control.
It’s no coincidence that many companies are cutting back on technology partners and turning instead to integrated, reliable solutions that support every stage of the operational cycle – from initial product coding to promotion management, from automated replenishment through to sales data analysis.
This isn’t just about technology – it’s about shaping a new data culture. An approach that places information quality at the heart, using it as the lever to create better experiences, streamline the supply chain, and support smarter decision-making.
I strongly believe this is the true transformation AI is bringing to retail: not automation for its own sake, but the creation of a smarter ecosystem where every decision – from coding a new product to reviewing the results of a promotional campaign – is backed by reliable, timely, and well-structured data.
The retail of the future will be ever more omnichannel, personalised and data-driven. And it’s being built today, starting with a task that may appear simple but is, in fact, critical: managing product master data. This is where much of the challenge lies – and where artificial intelligence can truly make the difference.
