If you want to be successful in e-commerce in the long term, you have to invest in your own data quality. But how can online retailers improve the quality of their data? According to Otto Friedrich University Bamberg, around 315 million parcels were returned in 2020. The negative economic and ecological consequences of returns are something that many retailers need to combat. The most important lever here is data quality. Recently, a global study by PIM provider and Onedot partner Akeneo found that 64% of customers are willing to buy a different product if critical information is missing. Furthermore, according to the same study, for another 66%, poor product information is reason enough not to buy a product. In short: optimally prepared product data is a central success factor in the digital world Commerce. The results of the study also show that a smooth shopping experience is expected today. But how can online retailers optimally prepare their own data and thus significantly improve data quality?
Customer expectations are clear: the product range must be deep but also broad. Today, it is best for online retailers to offer everything. This development requires a rethink towards long-tail, omni-channel and marketplace business models. Several important criteria that determine the quality of product data must be taken into account in this context. In addition to the validity of the product information, it must also be correct, complete and, above all, always up-to-date. But how can online retailers, who usually have a lot of raw data from various sources at their disposal, ensure not only quality but also consistency?
This challenge has to be seen from two different angles: On the one hand, suppliers and manufacturers are under increasing pressure to provide retailers with product information in certain formats. In doing so, it is difficult for them to achieve the corresponding e-commerce quality, as this requirement is not part of their actual core business. Retailers, on the other hand, receive this data and have to think about how they can sustainably and quickly transfer the received data into their individually grown product data model , despite the ERP or PIM system. Because with the introduction of a PIM or shop system, the actual data problem is not necessarily solved. The full potential of the PIM system can only be used by those who make supplier data efficiently usable.
Making supplier data usable means that data preparation is structured along a clearly defined process and, if possible, automated.
Automated product data onboarding follows clearly defined steps that are automated. Onedot's first intelligent platform for the acquisition, preparation and distribution of product data is market-leading and acts as a link between raw product data and the goal of a positive and smooth buying experience. The automated and clearly structured onboarding process provides various onboarding modules that extract AI-supported product attributes, map supplier attributes, classify different products, as well as bring attribute values and attribute units to the retailer-specific target format. This process thus turns unstructured product data into consumable data. Product data that is always up-to-date, correct and complete.
We show how such a process can be tailored specifically to your own setup every fortnight on Fridays at 2 pm in the Onedot Open Sessions. In addition to a demo of the Onedot product data platform, we address questions around the topics of procurement, preparation and distribution of product data and explain where artificial intelligence is used in the process. You can easily download the zoom link with calendar entry to the session and dial in, free of charge and without pre-registration. We look forward to seeing you!
