Blog
May 23, 2024
The biggest challenge for many automotive companies is the enormous amount of product data. This challenge quickly becomes more complex when it comes to ensuring the compatibility of automotive products, such as spare parts and accessories, for different vehicles. Traditional manual data entry and processing methods are time-consuming and error-prone, resulting in inconsistent product lists, prices, and specifications. Many companies are therefore looking for new, more robust, and powerful solutions for product data management.
Therefore, implementing an efficient, scalable, and traceable process for digital product data management is essential for innovative automotive companies. However, implementing such a data strategy involves a great deal of effort for many companies, as product data is not usually available for online publication and the procurement of product data is time-consuming and fragmented. In addition, suppliers and manufacturers are often unable to provide product data in electronic formats.
All of this contradicts the business goals that companies in the automotive spare parts market want to achieve in order to remain competitive. On the one hand, the product range available online must be continuously expanded in order to increase sales. On the other hand, it is important to accelerate the market launch of new product segments and to continuously and reliably keep existing products up to date. Another lever for increasing sales is to raise the conversion rate based on improved product data quality. It is data quality that ensures the comparability of highly technical products across different suppliers and spare parts manufacturers. So how can a comprehensive digital strategy for the automotive aftermarket achieve these goals?
The challenge of product data preparation for the automotive market
Since it is challenging to prepare different data types from different sources and enrich missing product data, the AI-powered product data platform can be used to convert product data from various fragmented sources into an import file. This import file can then be read into any desired ERP, PIM, or MAM system. This transformation of product data is so successful because Onedot AI has been trained with over 750 million SKUs and more than 1,000 suppliers, making it one of the most innovative and powerful platforms for product data transformation. The platform enables the rapid market launch of complex, extensive, and technical products, systems, and machines while maintaining high product data standards. It is the most sustainable approach to offering a well-curated product range online while reducing time-consuming and error-prone manual product data maintenance. In addition, the premium supplier portal gives manufacturers and suppliers easy access to the platform and enables catalog uploads with a single click. This simplifies data acquisition and makes it easier to organize and keep track of various data sources, including the catalog’s version history.
By using the Onedot product data platform, companies in the automotive industry can dramatically improve their product data processes. Onedot’s product data platform allows users to upload product catalogs and initiate data onboarding processes with just a few clicks.
- Reduction of onboarding time from months to hours.
- Accelerates the enrichment process and time-to-market for product data by a factor of five.
- Increases data completeness to 80-90%.
- Enables easy compliance with industry classification standards.
- Reduces the cost of manual product data processing by 85% through automation.
- Providing an intuitive user interface designed for everyone involved in product data management.
By implementing a rigorous, structured, and automated onboarding process for product data, automotive companies can ensure that their large volume of product data is always accurate, up-to-date, and of the quality required for business success. Onedot’s structured and proven onboarding process uses machine learning, NLP, and LLM algorithms to transform unstructured and confusing product data into saleable data. But what does this process look like, and how can companies in the automotive industry make the most of it?
Successful product data management through AI
After uploading the supplier catalogs to the platform and cleaning them up for onboarding using product matching, the clearly structured product data onboarding process begins. This ensures that only the desired products in the right quality find their way into the desired product database. Once it has been ensured that the catalog is ready for onboarding, the process can be started with a single click. The first step is to assign the supplier categories to the target categories. Onedot AI does this automatically and ensures that the categories are assigned correctly. If a category cannot be assigned, the software suggests options that the data team can review. After mapping the categories, Onedot AI assigns the suppliers to the target attributes. In the subsequent normalization step, units are standardized and value lists are filled. Finally, product variants are created based on the variant-forming attributes before an import file for the product database is created. This automated onboarding process transforms extensive product data into ERP, PIM, or MAM-compatible import files.
The versatility of the Onedot product data platform benefits all companies that are confronted with complex product data situations on a daily basis. The Onedot product data platform can quickly prepare catalogs in accordance with current standards, enabling AI-supported catalogs to be prepared for syndication without manual effort. Companies in the automotive industry can get started quickly and easily with Onedot’s AI-supported product data platform and transform their product data management today.