Online Retailer Case Study

The ability to respond to local competition has enabled the retailer to expedite its plans for expansion to additional countries. In addition, the retailer expects to increase the variety of its private brand.

The Client

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.

The Main Challenges

Before Quicklizard

When the collaboration with Quicklizard began, the retailer was using a single channel – its local ecommerce website – 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.

The goal

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.

The QL Solution

  1. AI-based profit optimization

    Working side-by-side with the retailer, Quicklizard established an AI-based solution for profit optimization. The solution encompassed 80% of the retailer’s products.

  2. Inventory optimization added

    After QL’s AI-based dynamic pricing platform began delivering results, the retailer and Quicklizard decided to add an important feature that addressed inventory optimization.

  3. Pricing tied to inventory status

    This feature allows the retailer to optimize pricing in accordance with existing inventory status – 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.

  4. Competition modeling on own brands

    In addition, sophisticated competition modeling (for the retailer’s 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

The Result

  • 34%

    Increase in revenue

  • $130M

    Total sales after six months

  • 11%

    Increase in profit

QL’s dynamic platforms leverage AI-based pricing to fundamentally transform the retailer’s approach to pricing. The new pricing strategies drove significant success, enabling the retailer to expand into two additional sales channels across two new European countries.

Pricing was optimized individually for each sales channel, using distinct parameters tailored to local market dynamics. As a result, the retailer successfully operated across three countries.

Six months after implementing the Quicklizard platform, the company recorded a 34% increase in revenue, growing total sales to $130M. During the same period, profit increased by 11% compared to the pre-implementation phase.

The Future

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