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The customer panel started to work on the product data indexing quality.
Introduction
The current way of indexing the products has its limitations., sometimes wrong products are linked to a Product Data Index product, resulting in an inability to find the right products.
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Another idea is to use the database with 2.5 MIO products with the manual knowledge of classification inside, to extract that knowledge with machine learning so not the user has to decide on a classification mapping, but the machine does.
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The idea
The customer panel started to work on the product data indexing quality. The idea, in general, is to identify suspects by comparing GTIN's, brands and manufacturer part numbers from the linked supplier items with each other.
The suspects will be displayed in the portal to the suppliers for their own products, the portal will also show the products that failed processing and not available in the Product Data Store. They can either correct their internal product data, so with the next processing, it will be correct, or mark the product to be correct. In that case, another supplier has probably to correct the product data.
Also, for the buyers, a portal will be available to display the suspects. And on top of that, the suspect flag will be available in the product data output and in the real-time Product Now.
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