22 Jan Trends and Developments in Product Data Management 2025

What are the trends and developments in product data management 2025?

Or in other words: What do the Digital Product Passport (DPP), Data Democratization, and Composable Commerce have in common? Exactly! They all relate to how we handle product data — and all these topics will play an even more significant role in 2025.

Get first-hand insights and assessments of current developments from three nexoma experts: our CEO Guido Sauerland, along with Business Developers Fabian Fischer and Kevin Mattig. Enjoy reading!

What role do digital tools play in modern product data management this year?

Guido: As in many other areas, specialized software solutions have become practically irreplaceable for modern product data management. On the one hand, this is due to the wide range of possibilities offered by such digital tools—think “data transformation,” such as the generation and adaptation of various data standards like BMEcat or xChange, as well as compliance with classifications like ETIM or ECLASS. On the other hand, there are also practical reasons: particularly with large volumes of product data, Excel tables and spreadsheets quickly reach their limits, because they become unmanageable and highly labor-intensive. PIM and MDM systems are definitely the better choice here.

PIM systems, for example, provide a centralized way to create and maintain product data. They are often referred to as the ‘Single Point of Truth,’ serving as a single, always up-to-date source for data. This not only ensures consistent data but also prevents data silos, meaning separate data sets scattered in various folders etc. Moreover, all departments—eCommerce, sales, marketing—work from the same data foundation. This transparency and uniformity ultimately lead to higher productivity and increase employee satisfaction.

In today’s modern economy, where flexibility and speed are critical success factors, such tools enable a much faster provision and optimization of data. This brings several interlinked benefits: optimized data increases visibility facilitates better listings, which in turn reduce returns due to misinformation.

How will product data quality and employee training impact businesses in 2025?

Fabian: These days, no retailer can succeed with incomplete or outdated product data. While the term “data quality” may sound dry, it’s a very central issue in the digital economy, which basically “separates the wheat from the chaff”. High-quality product data can even serve as a strong lever for increasing revenue, since customers are more likely to trust comprehensive, informative product descriptions over minimal, vague ones.

This is why we strongly recommend targeted training to raise employee awareness of the crucial role product data plays in success. They’ll learn how to efficiently collect, organize, and analyze data to spot inaccuracies or improvement opportunities. This helps them understand how to enhance the overall data quality and respond more quickly to market changes, such as sudden adjustments to product data standards or new legal requirements. All of this ensures consistent, high-quality data that is invaluable for making informed business decisions.

Here, the general rule applies: the higher the data quality, the better and more satisfactory the decision-making—internally (e.g., when sourcing the best suppliers) and externally with partners and customers. For example, if a manufacturer integrates well-structured product data into a PIM system, already starting during the early stages of product development, it becomes much easier for buyers to make purchasing decisions lateron.

Training can also foster innovation by enabling employees to identify potential weaknesses in workflows and refine those processes. This not only boosts employee empowerment but also helps secure competitive advantages through high-quality data and optimized processes.

A solid understanding of data management also simplifies generating standards like BMEcat and xChange or classifications like ETIM and ECLASS.

What role will automation play in data processes?

Kevin: This is an essential topic. In today’s fast-paced economy, the old saying “time is money” is more relevant than ever. Process automation in product data management helps manufacturers optimize their data quickly and easily to meet the specific formatting requirements of industry platforms like Mercateo Unite or simple system, providing precise and timely data. These platforms usually require product data in specific standards; for example, Mercateo Unite currently demands data in BMEcat 1.2 format and classified according to ECLASS 5.1.4. Manually implementing such detailed adjustments would be extremely time- and resource-intensive.

Specialized tools automate these processes, converting product data into the required format and delivering it—on schedule—via SFTP or email. Also, to ensure optimal data refinement, direct access to relevant data sources like PIM or ERP systems is crucial. SaaS solutions like CatalogExpress already include standard interfaces to renowned PIM providers such as Akeneo, ATAMYA (eggheads), Contentserv, Crossbase, OMN by Apollon, Pimcore, or Viamedici EPIM, as well as shop systems like Shopware and Oxid, or databases like MongoDB. This significantly reduces the need for manual data exchange and also minimizes associated errors.

What role will Data Democratization and Data Governance play this year?

Guido: Data Democratization and Data Governance will be critical in 2025 for making product data management more efficient. Data Democratization ensures that relevant data is prepared and made accessible so employees can easily access and use it—without depending on IT teams. This is particularly important for data-intensive processes like Data Onboarding and also Data Syndication, as consistent and readily available data facilitates collaboration and also decision-making.

Data Governance complements this by setting clear guidelines: it ensures that data is consistent, accurate, and also securely managed. This is achieved through clearly defined responsibilities and processes that maintain high data quality and transparency for all employees. Together, these concepts form the foundation of an efficient data strategy. The better this strategy is established, the faster employees can make informed decisions—whether working with suppliers or also communicating with customers.

In short: a clear data strategy that incorporates both data democratization and data governance reduces chaos, increases efficiency, and also leads to noticeable cost savings for businesses.

What impact does artificial intelligence have on data processing and the workplace?

Kevin: Today, being able to offer “AI-supported” services is already a clear competitive advantage for businesses. Why? Because AI-driven automation processes — like managing product data or generating required data formats — run significantly faster and also more efficiently while reducing human errors.

Data standards like BMEcat provide clear structures for data sets, enabling uniform, comparable, and transparent data exchanges. This standardization allows AI to identify patterns effectively and map source data to target formats. This saves time and enables businesses to adapt their data to new market demands more quickly and effectively.

However, it’s also important to address the challenges that come with AI. The job market is constantly evolving, and employees must adapt to new conditions. This makes ongoing training more critical than ever. It’s not enough to just implement AI systems—employees must also learn to evaluate and also use their outputs constructively. After all, not every AI result is inherently accurate. While AI can modernize and accelerate existing processes, the results of AI-driven workflows must always be critically assessed.

What’s clear is that creativity, empathy, and personalized interactions with customers or suppliers simply remain irreplaceable. Therefore, companies should never blindly rely on AI but instead carefully evaluate where it adds value and where human expertise remains irreplaceable.

What significance will Composable Commerce have in 2025, and what are the customer needs?

Fabian: The global economy is constantly changing. Data requirements are evolving, and customers are also demanding more detailed product information than ever. In eCommerce, factors like process scalability and the flexibility of software solutions — be they PIM, ERP, CMS, or CRM systems — are becoming increasingly important. This is where the concept of “Composable Commerce” comes in. It’s a modular approach that allows companies to combine different software modules to create tailored and scalable solutions for their specific individual needs. In product data management, for instance, this could mean extending an existing ERP system with a modern PIM module to centralize product data management and also quickly adapt it to various marketplaces or customer requirements.

In 2025 and beyond, these concepts will play an even more central role because hybrid architectural environments enable maximum flexibility and scalability. Systems interconnected through interfaces can provide real-time data on sales figures or inventory levels, also allowing immediate responses to market changes or adjustments to supply chains. Being able to offer products promptly gives companies a competitive edge.

It’s definitely worth taking a closer look at this topic.

What relevance will the Digital Product Passport (DPP) have in the future?

Fabian: The shortest answer to this is that, as of 2030, products without a digital product passport may no longer be sold within the EU—according to the current plan. While some details about the DPP are still being defined, businesses should definitely start preparing now. A digital product passport relies on well-maintained, complete, and also up-to-date product data. Without this foundation, meeting future requirements will be an unnecessarily big challenge.

The DPP, part of the EU Ecodesign Regulation finalized in July 2024, mandates that every product sold in the EU must have its own digital passport. This is basically a comprehensive dataset detailing a product’s entire lifecycle, including standard attributes like dimensions, weight, and materials, as well as information about origin, supply chains, chemical contents, repairability, and also recyclability. The goal of the DPP is to make these details available 24/7 in a standardized, transparent format for manufacturers, retailers, customers, and regulators alike.

For businesses, the DPP represents an opportunity to optimize products for sustainability while empowering customers to make more informed choices. Early adopters who meet these requirements build trust in their products and also gain a competitive edge.

The DPP will become more defined starting in 2025, and by 2027, it will likely be already mandatory for some product categories, such as batteries. Businesses should therefore proactively address these requirements, including how to generate and also deliver such datasets. Tools like CatalogExpress can help businesses prepare. Those who act early will lay the foundation for sustainable success in a data-driven economy. The future of data management remains exciting!

Tackle product data management trends and challenges—with nexoma’s expertise!

Would you like to learn how to address these and other developments, trends, and challenges in product data management for 2025? Or are you interested in our specialized software tools like “CatalogExpress” or the “Supplier-Portal” for supplier management? Schedule a no-obligation consultation with us today. We’re happy to help!