5 reasons why many e-commerce problems arise in product data rather than in the shop
Product data as the starting point for many challenges
Many typical challenges in e-commerce do not originate in the shop itself. They are the result of how product data is structured, maintained, and made available across systems. This article shows why the shop often only reveals symptoms and where companies should take concrete action to improve scaling, quality, and time-to-market in the long term.
1: The shop reveals problems, but is not their cause
Missing variants, contradictory product information, manual corrections before campaign launches, or different data statuses on marketplaces become particularly apparent in the shop. However, the shop is rarely the source of these problems. It merely displays what is delivered from upstream systems – including all inconsistencies and gaps.
2: Product data has grown historically and is not structured consistently
In many companies, product data is created over many years. Attributes are interpreted differently, variant logic is incompletely modeled, and translations are not consistently linked. These grown structures mean that product information cannot be reliably used across channels.
3: There is no clear ownership of product data between departments
Product management, marketing, and IT work with the same product data, but according to different rules and objectives. It is often not clearly defined who is responsible for maintenance, approval, and further development. Without clear responsibilities, inconsistencies, coordination loops, and manual workarounds arise, which have a direct impact on e-commerce.
4: Shop optimization cannot compensate for poor product data
Modern shops can do a lot, but they cannot fix poor data. New features, better performance, or optimized UX improve the presentation, but not the quality of the underlying product information. With increasing channel diversity, internationalization, and personalization, these limitations are becoming increasingly apparent.
5: Product data is the real lever for scaling in e-commerce
Cleanly structured, consistent product data is a prerequisite for scaling. A powerful PIM such as NovaDB Headless-PIM makes it possible to model products correctly once and then flexibly deploy them across different channels. Time-to-market, data quality, and the degree of automation therefore depend less on the shop itself than on the quality of the product database.
Recommended action: Where companies should start
If you want to solve e-commerce problems in the long term, you should consciously shift your focus from the shop to the product data. Four steps have proven effective in practice:
• Strategically anchor product data
Product data influences conversion, scaling, and time-to-market and must be prioritized accordingly at the management level.
• Clarify the data model before discussing the system
Before tools are evaluated or replaced, it should be clearly defined how products are to be structured, varied, and used across channels. A clean data model reduces complexity in the long term.
• Define ownership and governance
Clear responsibilities for the maintenance, approval, and further development of product data are crucial to avoid inconsistencies and media breaks.
• Think holistically about architecture
A PIM system only unfolds its benefits in conjunction with CMS, DAM, commerce, and other systems. API-first and composable approaches create the necessary flexibility for future requirements.
Conclusion
Many e-commerce problems cannot be solved in the shop. The decisive lever lies in the product data. If it is thought out strategically, shops, marketplaces, and other channels can unfold their full potential.
If you have any questions about the strategic classification of PIM and product data, we are available to advise you.
We will explore the topics covered in this article in more depth with the NovaDB PIM system in the OMR Tool Talk on March 18 at 9:30 a.m. together with Akeneo, novomind, and Temel Kahyaoglu – with a focus on classification, architecture, and practice.
Tobias Denninger
After completing his Bachelor of Science in Online Marketing at the University of Applied Sciences Würzburg-Schweinfurt (THWS) in 2021, he began his career in sales at Noxum. There, he gained solid experience in business development and continuously expanded his expertise.
In 2022, he took on the role of Account Manager with a focus on NovaDB. In this position, he is responsible for developing customer relationships and delivering tailored solutions based on NovaDB technology, with the aim of building long-term partnerships and creating measurable value for clients.