Blog
May 23, 2022
Anyone who wants to be successful in e-commerce in the long term must invest in their own data quality. But how can online retailers improve the quality of their data? According to Otto Friedrich University in Bamberg, around 315 million parcels were returned. For many retailers, the negative economic and environmental consequences of returns are something that needs to be addressed. The most important lever here is data quality. A recent global study by PIM provider and Onedot partner Akeneo found that 64% of customers are willing to buy a different product if information that is crucial to their purchase decision is missing. Furthermore, according to the same study, poor product information is reason enough for another 66% not to buy a product. In short, optimally prepared product data is a key success factor in digital 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?
New business models in retail
Customer expectations are clear: the product range must be deep but also broad. Today, online retailers are best advised to offer everything. This development is prompting a shift 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 a wide variety of sources at their disposal, ensure not only quality but also consistency?
This challenge must be viewed from two different perspectives: On the one hand, suppliers and manufacturers are under increasing pressure to provide retailers with product information in certain formats. However, it is difficult for them to achieve the required e-commerce quality, as this requirement is not part of their core business. Retailers, on the other hand, receive this data and have to consider how they can transfer the data they receive quickly and sustainably into their individually developed product data model , despite ERP or PIM systems. This is because the introduction of a PIM or shop system does not necessarily solve the actual data problem. Only those who make supplier data efficiently usable can exploit the full potential of the PIM system.
Making supplier data usable means that data preparation is structured according to a clearly defined process and, where possible, automated.
High data quality through automation
Automated product data onboarding follows clearly defined steps that run automatically. The market leader is Onedot’s first intelligent platform for sourcing, preparing, and distributing product data, which acts as a link between raw product data and the goal of a positive and smooth shopping experience. The automated and clearly structured onboarding process provides various onboarding modules that use AI to extract product attributes, map supplier attributes, classify different products, and convert attribute values and attribute units to the retailer-specific target format. This process thus turns unstructured product data into consumable data. In other words, product data that is always up-to-date, accurate, and complete.
Everything you always wanted to know
Every two weeks on Friday at 2 p.m., we show how such a process can be tailored specifically to your own setup in the Onedot Open Sessions. In addition to a demo of the Onedot product data platform, we address questions relating to the 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 a calendar entry for the session and dial in free of charge and without prior registration. We look forward to seeing you there!