--- title: "Digital Shelf Analytics: From the digital shelf to Agentic PIM" description: Digital Shelf Analytics provides transparency regarding product data across digital sales channels. Find out how this forms the basis for Agentic PIM. url: https://www.novomind.com/en/blog/digital-shelf-analytics/ markdown_url: https://www.novomind.com/en/blog/digital-shelf-analytics.md type: post slug: digital-shelf-analytics-from-the-digital-shelf-to-agentic-pim author: marketing published: 2026-07-23T02:53:49Z modified: 2026-09-02T13:08:37Z language: en-US taxonomies: category: - AI - Blog - Digital Commerce word_count: 1206 tokens: 2268 --- # Digital Shelf Analytics: From the digital shelf to Agentic PIM Overview Anyone responsible for maintaining product data expects it to appear on marketplaces, retailer websites and other sales channels exactly as intended. In practice, however, this is often not the case. Is all the information complete? Are the correct images being displayed? How visible is the product compared with competing products? Without transparency into how products are actually presented, these questions often remain unanswered. This is precisely where Digital Shelf Analytics comes in. A view of the digital shelf Companies selling products online no longer present them solely in their own online shops. Marketplaces such as Amazon, retailer websites, price comparison portals and social commerce platforms are now important sales channels. Each of these digital shop windows forms part of what is known as the digital shelf. Unlike in physical retail, however, manufacturers often have only limited control over how their products are actually presented in these channels. This is where Digital Shelf Analytics (DSA) comes into play. The technology continuously analyses how products are presented across digital sales channels and provides reliable insights into their visibility and the quality of their presentation. The information assessed includes: The completeness and quality of product information Images and videos Prices and price trends Product availability Ratings and reviews Positions in search results Competing products and how they are presented Digital Shelf Analytics creates transparency and reveals opportunities for optimisation. Digital Shelf Analytics and PIM: Stronger Together A Product Information Management (PIM) system acts as the central source for product information. Descriptions, technical specifications, images and marketing copy are maintained within the system and distributed to online shops, marketplaces and retail partners. Once the data has been distributed, however, the PIM no longer has visibility into what happens next. It does not know how products are actually presented across individual sales channels or how they perform compared with competing products. Digital Shelf Analytics complements the PIM by analysing how products are presented on marketplaces and retailer websites. It provides the transparency required to understand their actual presentation across sales channels. Together, the two technologies create a continuous information cycle: The PIM creates and distributes product information. Digital Shelf Analytics checks its presentation and performance. The insights gained are fed back into the process and support the continuous optimisation of product data. This enables companies to identify incomplete product information, declining visibility and opportunities for optimisation across individual sales channels. From monitoring to continuous optimisation Analysis alone does not improve product data. In many companies, issues are first evaluated, then passed on to the relevant teams before corrective action is taken. Several days or even weeks can pass between identifying an issue and implementing an improvement. This is where the learning-loop approach comes in. Insights from Digital Shelf Analytics flow directly back into the optimisation process, helping companies continuously develop their product information. The result is an ongoing cycle of analysis, optimisation and review. Product data is no longer maintained solely at fixed intervals. Instead, it is continuously improved using real market insights. This lays the foundation for a significantly more agile product data strategy. The next step: Agentic PIM What happens when this optimisation cycle is no longer driven mainly by people, but AI agents take on much of the analysis and implementation? This marks the beginning of the next stage in the evolution of Product Information Management: Agentic PIM. AI agents analyse insights from Digital Shelf Analytics, identify opportunities for optimisation, add missing information and help publish changes once they have been approved. A linear process becomes an intelligent optimisation cycle – the learning loop. Digital Shelf Analytics provides the necessary market information, while AI agents help turn these insights into concrete actions. The PIM evolves from a system for managing product data into an intelligent platform that continuously improves product information. This is where the potential of Agentic PIM lies. The key benefits for manufacturers The combination of PIM, Digital Shelf Analytics and AI-supported processes helps companies optimise product data more efficiently. It delivers benefits on several levels. Higher data quality and greater visibility Continuously comparing product data with how products are actually presented on marketplaces and retailer websites makes it possible to identify incomplete or incorrect information at an early stage and improve it in a targeted way. At the same time, complete and up-to-date product data provides the foundation for greater visibility in search results and across digital sales channels. Faster optimisation with less effort Instead of manually identifying issues and passing them on to different teams, optimisation processes can be supported in a targeted way or partially automated. This shortens response times, reduces manual effort and enables product information to be adapted more quickly to changing market conditions. Better cooperation When product management, marketing and sales teams have access to the same insights from Digital Shelf Analytics, they share a common basis for decision-making. Improvements can be coordinated more efficiently, responsibilities can be assigned more clearly and product information can be developed consistently across channels. Conclusion: The digital shelf becomes a sensor for intelligent product data Digital Shelf Analytics turns the digital shelf into a valuable source of information for the continuous optimisation of product data. Combined with a PIM system and AI agents, it creates an intelligent optimisation cycle that helps companies continuously adapt their product information to market requirements. In this way, the traditional PIM gradually evolves into Agentic PIM. novomind is following this development closely and continuing to advance novomind iPIM with a clear focus on intelligent, AI-supported optimisation processes. Recommended reading For a deeper look at Digital Shelf Analytics, Gartner’s current Market Guide for Digital Shelf Analytics provides an informative overview of the market, common use cases and recent developments. Market Guide for Digital Shelf Analytics Back to overview Frequently Asked Questions about Digital Shelf Analytics What is Digital Shelf Analytics? Digital Shelf Analytics examines how products are actually presented on marketplaces, retailer websites and other digital sales channels. It gives companies insights into product information, visibility, prices, availability and competitive positioning, enabling them to optimise their product data in a targeted way. Why is digital shelf analytics important for manufacturers? Once manufacturers have distributed their product data, they often lose direct control over how it is presented. Digital Shelf Analytics provides transparency into how products actually appear and helps companies identify discrepancies and opportunities for optimisation at an early stage. What role does a PIM play in conjunction with digital shelf analytics? A Product Information Management (PIM) system provides a central source of product information and distributes it to different sales channels. Digital Shelf Analytics complements this function by checking how the information is actually presented in those channels and identifying possible improvements. What distinguishes Digital Shelf Analytics from a PIM? A PIM manages and distributes product information. Digital Shelf Analytics, on the other hand, analyses how products are actually displayed and how they perform across digital sales channels. It is only through the interaction of both systems that continuous optimisation of product data is possible. What role does Agentic PIM play? Agentic PIM enhances traditional PIM systems with AI agents. These agents can use findings from Digital Shelf Analytics to prepare optimisation suggestions, initiate changes and review their effectiveness. As a result, optimisation processes can become increasingly automated.