How Office Depot managed to transform product data from Icecat with Gepard Syndicator

Office Depot, a global provider of products, solutions and services for workplaces and offices, with its annual revenue of $11 billion uses Gepard Syndicator to automatically transform product information from Icecat into its internal data model.

Early 2015, the management of Office Depot realized that product information on its websites and apps was getting outdated and that manual updates of product data would be inefficient for its business. That is why Office Depot teamed up with Icecat to import standardized product data.

However, after an initial test, it was clear that the taxonomies of Office Depot and Icecat did not fully coincide and needs pre-processing to transform it into the taxonomy of Office Depot. The Icecat taxonomy contains, for example, a range of camera categories named ‘compact cameras’, ‘advanced digital cameras’, ‘DSLR cameras’, and ‘security cameras’ (which are installed on walls). However, Office Depot has only one category, called “cameras”. And the product page of each camera contained an additional field, called “type” to distinguish sub-categories of cameras. In order to import  these data correctly, Gepard Syndicator is used as a transformation or mapping tool, to transform these categories into camera types.

Altogether, it took 320 man hours to map the taxonomy of Icecat to the taxonomy of Office Depot and to settle all the transformation rules resolving cases like the one in the cameras example. Currently, the automated solution imports and updates approximately 600 products per day.

Helen Iskos, Application Support, MDM Governance & Data Quality Manager at Office Depot confirms that synchronized services of Icecat and Gepard Syndicator helped Office Depot to:

• automatically enrich about 60% of the assortment with required product information;
• reduce a product’s time-to-market;
• minimize manual product enrichment;
• improve product data quality.

Icecat and Bintime, the developer of Gepard, see a big need for the smart mapping tool in the market, especially for larger retailers with a historical and therefore frozen taxonomy.