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PIM or MDM? We show you the differences between both systems, when one is enough, and when you need both.

Digital shelf analytics creates transparency into how products are presented and perform across retailers, marketplaces and other digital channels. But collecting insights is only the first step. Learn how DSA helps improve availability, product content, share of search and retail media performance – and why connecting these insights with PIM and PXM is key to creating a continuous optimisation loop.

How LLMs are revolutionizing product communication processes

This is how AI makes your product search in an enterprise environment intuitive, highly accurate and noticeably effective at driving conversions.

How AI translates your product texts highly efficiently, consistently, and measurably into over ten languages.

AutoMapper is already in productive use, showing how AI concretely supports product data onboarding in the enterprise environment.

Agentic AI is changing the business world – but its potential can only be realized with reliable data, clear processes, and suitable integration. ADXO demonstrates how successful implementation can be achieved.

Many companies are testing AI. However, the true value only emerges when AI agents are integrated into real processes, data, and systems.

Master data chaos? An MDM strategy lays the foundation for all subsequent digital projects.

Today, data is considered one of the most important resources for businesses. It is meant to enable better decisions, automate processes, accelerate innovation, and drive new business models.

Product data scattered everywhere? Here's how to successfully implement a PIM system – from data strategy to operations.

Stefan Gander, Head of PIM & MDM: While recent years have been marked by economic uncertainties, sharp cost increases, restrained innovation, and the first cautious steps with AI tools, the question now is how companies can align their PXM landscapes in a way that measurably increases product innovation.

Sustainability is one of the most important current topics and companies in every sector will have to deal with the consequences for their business sooner or later. Various commissioned studies show that both consumers and companies are prepared to invest in sustainability, whether through higher costs for a sustainably produced end product or through improvement measures and restructuring within the company.

Many companies are aware of the value of their data. The greater challenge is actually making that value usable. Today, business data is distributed across ERP, CRM, PIM, MDM and other operational systems, data warehouses and data lakes, as well as cloud platforms and external data sources. To use this data collectively for analytics, operational processes or AI applications, companies need consistent and straightforward access.

In the midst of global, highly competitive and extremely dynamic markets, more and more companies recognize the value and critical role of data for business success. However, a look at practice shows that many leave the potential in their database unused.

Data-driven working is not a new concept. Companies have always used information about customers, products, suppliers, markets or business processes to make decisions. What has changed, however, is the volume and variety of available data as well as the opportunities to use it in business processes with the help of modern data platforms, analytics and artificial intelligence.

A comprehensive selection and implementation of tools and solutions is crucial for a successful e-commerce operation, with e-commerce platforms and PIM systems in particular playing a key role.

Today, data is one of a company’s most important resources. Yet even a modern data platform, high data quality and comprehensive analytics or AI capabilities do not create business impact on their own. Only when employees understand the available data, trust it and actually use it in their daily decisions and processes can real value be created for the business.

There is a lot of discussion today about the benefits of AI and new uses in product content management.

Data analysis and interpretation have taken center stage with the advent of the digital age... and the sheer volume of data can be terrifying. According to a study by Digital Universe, the total data volume in 2012 amounted to 2.8 trillion gigabytes! Based on this amount of data alone, it is clear that the ability to analyze complex data, gain actionable insights, and adapt to new market requirements will be the calling card of every successful company in today's global world – and all in the quick of thought.

For a successful e-commerce operation, the use of a variety of tools and solutions is crucial to selling effectively and optimising the customer experience; this article deals with the various aspects of selection and implementation.

Syndication is one of the buzzwords that have been circulating in the software market for quite some time. This is due to the fact that the importance of digital product distribution continues to grow and that omnipresence in retail is now more important than ever. Each channel, be it your own communication and sales channels or those of retail partners, is important and increases the potential for sales increases.

Content marketing is a strategic marketing direction that involves creating and delivering valuable, relevant, and consistent content. All of this is aimed at attracting a clearly defined target group, retaining this group and ultimately capturing beneficial customer actions.

Artificial intelligence (AI) is described by marketing experts as “the technology of the future” because it has the greatest potential to increase ROI (return on investment). Many believe that AI will have a bigger impact on marketing in the long term than the invention of social media.

Marketing automation uses software to automate monotonous marketing work. Marketing departments can automate repetitive tasks such as email marketing, social media posts, and even advertising campaigns – not just for efficiency, but also to give their customers a more personalized experience.

The idea of Master Data Management (MDM) as a cross-system instance that ensures that a company's relevant data is obtained from the respective data sources, consolidated and further processed in a regulated manner, cannot be applied to just one type of data. Multi-domain MDM thus refers to the extension to include all data domains relevant to a company, such as product data, customer data, supplier data or location data.

Data plays a key role in the success of marketing and sales processes as well as in supplier and customer loyalty. Companies need to think about which combinations of data they can derive the greatest possible value from. Networked information about products, customers, locations, suppliers and other business partners can provide exciting insights and provide information on how processes can be optimized and profitable communication measures can be strengthened.

Everyone is talking about data transparency and is communicated as a unique selling point (USP) by many software manufacturers. In a world full of over and false information, there seems to be a global need to bring clarity to communication and to offer people the opportunity to inform themselves unequivocally and completely about certain things.

As much as business goals may differ, one thing always remains the same: Data is the basis for companies to achieve them. If the goal is to increase sales, a closer look at the data helps to understand which products represent the most lucrative business in which context.

Master Data Management (MDM) provides companies with a lot of added value. Consolidating data across all relevant areas creates the necessary big picture to meet today's consumer requirements.

Innovation always occurs when existing offerings are further developed and rethought. On the one hand, this can affect the product itself, but also the way it is presented or made available. Since these developments always aim to make the offer more attractive to the target group, customer needs are always the starting point for every innovation.

Reliable data forms the basis for successful and sustainable business – and Master Data Management (MDM) is the technology that generates this data and makes it centrally accessible. With the help of MDM, companies can use MDM to realize a whole range of advantages that make it easier to argue with decision makers in the company.

The importance of data in companies continues to grow. Each expansion of the digital offering results in even larger amounts of data – but only a few companies are able to effectively use these volumes of data for themselves today. This is due to the fact that the data is not available in a structured manner, there is no central access to it and therefore the business relevance cannot be identified. In addition, poor quality of the data prevents real added value from it.