Large-Scale Product Data Onboarding: How It Works

Large-Scale Product Data Onboarding

The eCommerce market is expanding, with a value of $5.5 trillion in 2022. Unsurprisingly, there are between 12 and 24 million e-commerce sites worldwide. With customers favouring marketplace, long tail and omnichannel models, eCommerce players need to invest more in data management processes than ever before. Here is why implementing modern product data management processes has become indispensable and why large-scale product data onboarding is integral to product data management success.

According to a new study, 94% of customers believe correct product information is important when shopping online. In addition, in case of missing or bad information, 53% of customers shop elsewhere. These numbers show that product data quality and availability impact sales and, therefore, the conversion rate. Therefore, companies need to quickly offer a broad, personalised and deep product range with products of the best possible e-commerce quality.

Elements of an effective product data onboarding strategy 

As experts in the sourcing, preparation, and syndication of product data for commerce and industry, we at Onedot understand retailers' product data challenges. It can be overwhelming to prepare many different data types from various sources and enrich missing product data. Thanks to the Onedot product data platform, retailers can seamlessly connect all suppliers with their ERP, PIM, and MAM systems, process thousands and millions of SKUs automatically and have the product data always needed available, up-to-date, and ready for syndication into various online shops. Here is how the automated large-scale product data onboarding process works and why it's the most effective onboarding strategy:

  • Gathering all available product data – Before starting the onboarding process, it is important to collect all available product data catalogues from vendors efficiently. Exchanging emails is not considered best practice.
  • Organising product data according to the product data model – Retailers need to invest in finding the best possible product data model for their business success. This data model specifies which attributes, categories and values all products must have so that they can be later found in the online shop.
  • Importing product data to appropriate systems – Before the product data can be imported into the correct product data systems, normally ERP or PIM, supplier catalogues need to be aligned to the merchant’s taxonomy.
  • Syndication of product data to online shops, marketplaces, and other channels – Successful product data onboarding processes end with the product data being played out to the various channels retailers want to operate. 

By implementing a large-scale automated product data onboarding process, retailers can ensure that the data displayed on various channels is accurate, up-to-date, and of the quality needed for eCommerce success. Let's take a detailed look at the AI-supported product data platform, which turns unstructured data into consumable data.

Automated product data onboarding

Manual data preparation processes, time-consuming editing of rigid templates and nerve-racking collection of additional product information should have been a thing of the past. With a structured data preparation process, old, time-consuming and rigid processes can be replaced and fit for the future. The product data platform is designed so that every supplier or manufacturer catalogue in the most diverse data formats is brought directly into an importable ERP/PIM format. How can this be ensured quickly, efficiently and automatically?

This automated onboarding can only be achieved through advanced machine learning, which transforms the supplier catalogue directly in a structure that the ERP or PIM can consume. If the quality of the transformed supplier catalogue is not good enough, intermediate steps can be checked and, if necessary, improved by the user before importing it into the ERP or PIM system. In this way, data teams bring their expertise specifically to bear in reviewing proposals instead of blocking their time with repetitive manual preparation steps.

Onedot's product data platform goes beyond traditional onboarding. It allows retailers and suppliers to exchange information directly via a supplier portal. Central to this is the sourcing of data with specific data requests, which can be sent from the retailer to the supplier via the platform. However, it is also possible for suppliers and manufacturers to upload their catalogues themselves, which further reduces the effort for the retailer. Depending on whether it is a new manufacturer or supplier, the entire new catalogue or only parts of the catalogue are updated and prepared for onboarding after appropriate product data matching.

Investing in modern data management for eCommerce success

There are many reasons why product data onboarding is the foundation of any modern data management. But mainly, companies can ensure that they have implemented a consistent, standardised and automated data sourcing and data preparation process that adds real value. Manual data maintenance processes can be reduced, and products can be brought online five times faster and in much better quality on a wide range of channels. This positively affects the conversion rate, which can be increased by up to ten per cent and thus boost sales.

It is modern data management that is dedicated to the product experience. Because only those who can provide products with the right product information at the right time to the desired target group in the most personalised way possible will win in the highly competitive e-commerce market, thanks to the unique Onedot AI, companies can invest in their product data quality in a targeted, sustainable and long-term manner and thus achieve more sales.

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