{"id":20725,"date":"2022-03-18T09:43:47","date_gmt":"2022-03-18T06:43:47","guid":{"rendered":"https:\/\/quicklizard.wpenginepowered.com\/blog\/online-retailer-case-study\/"},"modified":"2026-09-23T07:54:27","modified_gmt":"2026-09-23T04:54:27","slug":"fallstudie-eines-online-handlers","status":"publish","type":"post","link":"https:\/\/quicklizard.com\/de\/blog\/online-retailer-case-study\/","title":{"rendered":"Fallstudie eines Online-H\u00e4ndlers"},"content":{"rendered":"

The Client<\/h2>\n<\/div>\n\n\n

A leading European online retailer with $97M in annual revenues and 8% profit margin that sells a wide variety of branded and private label home products. The retailer is a pure online player with no brick & mortar presence. Inventory is a central business component, and cross border shipping is utilized by the retailer to cover additional countries within the EU.<\/p>\n\n\n

The Main Challenges<\/h2>\n<\/div>\n\n
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Before Quicklizard<\/p>

When the collaboration with Quicklizard began, the retailer was using a single channel \u2013 its local ecommerce website \u2013 to sell products in its home country. When it came to pricing, the retailer used a sophisticated excel spreadsheet, which allowed for gradual price increases or reductions, mostly based on inventory and seasonality.<\/p>\n<\/div> <\/article>\n

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The goal<\/p>

The retailer approached Quicklizard because it had decided to pursue a more advanced, AI approach to pricing. The retailer wanted to fully automate pricing decisions, while taking into consideration variables such as real-time user behavior, inventory data, pricing history, competitive data and cost constraints.<\/p>\n<\/div> <\/article>\n <\/div>\n<\/div>\n\n

The QL Solution<\/h2>\n<\/div>\n\n
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  1. \n

    AI-based profit optimization<\/p>

    Working side-by-side with the retailer, Quicklizard established an AI-based solution for profit optimization. The solution encompassed 80% of the retailer\u2019s products.<\/p>\n<\/div> <\/li>\n

  2. \n

    Inventory optimization added<\/p>

    After QL\u2019s AI-based dynamic pricing platform began delivering results, the retailer and Quicklizard decided to add an important feature that addressed inventory optimization.<\/p>\n<\/div> <\/li>\n

  3. \n

    Pricing tied to inventory status<\/p>

    This feature allows the retailer to optimize pricing in accordance with existing inventory status \u2013 especially for limited-time clearance sales. Inventory renewal costs (which may be higher or lower than existing inventory costs), and inventory renewal times have also been taken into consideration.<\/p>\n<\/div> <\/li>\n

  4. \n

    Competition modeling on own brands<\/p>

    In addition, sophisticated competition modeling (for the retailer\u2019s own branded products) was also applied. This enables the retailer to use market data on its own brand as well, thus reducing competitive response times and preventing revenue<\/p>\n<\/div> <\/li>\n <\/ol>\n<\/div>\n\n

    Das Ergebnis<\/h2>\n<\/div>\n\n