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Case Study

Markdown Optimization for a Shoe Retailer

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About Reno

Reno is a shoe retailer that operates around 400 stores in 6 countries. For over 30 years Reno has been known for the top brands that it carries as well as its broad range of shoes for the whole family. In addition to its core product range, the retailer also sells matching accessories such as handbags and jewelry. Through its network of stores, its online shop and the Reno app, the omni-channel retailer makes around €500 million in annual revenue.

The Challenge

The market that Reno operates in has changed dramatically over recent years and become increasingly dynamic. Like many other retailers, Reno lacked the necessary tools to manage its complex operative processes, as it still relied on outdated systems and processes. As a result, Reno’s achieved sales ratio and turnover were below expectations. At the end of each season, Reno was left with a high level of unsold inventory, which meant that a large quantity of old merchandise was being transferred into the next season. Reno was in need of a solution that would make its processes more efficient and improve financial performance.

Reno & aifora

In order to prove the usability and applicability of the aifora pricing tool, a proof of concept was conducted for a selection of product groups. First, aifora performed a retrospective analysis of Reno’s data, created the mathematical models and integrated Reno’s SAP system with the aifora platform to ensure a continuous exchange of data. Next, the aifora solution was configured according to Reno’s markdown strategies, business rules and workflows. Finally, the users were trained and onboarded so that they were able to apply the new tool efficiently and effectively.

"Markdown optimization was implemented in just 4 weeks, including integration to our SAP systems."
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Following the successful proof of concept, aifora’s Markdown Optimization tool was rolled-out for all product groups, stores and countries. A Customer Success Manager supported the change management process and continues to support the users. Reno continues to increase the level of automation, as necessary.

The Solution

  • Consumer demand is forecast per style, based on current and historical transaction and inventory data
  • Using demand forecasts and price elasticities, Reno is now able to set the right markdown amount at the right time for each product in each sales channel
  • Reno’s specific business rules, budget targets and planned activities are taken into account in the price calculations


By implementing aifora’s markdown optimization solution, Reno has been able to achieve its desired objectives: increased sales and revenues. Furthermore, Reno now has the ability to quickly react to changing market conditions thanks to real-time demand forecasts. Reno is particularly happy with the level of flexibility and transparency provided by aifora’s solution.

Increased turnover

Reduced inventory

Increased agility

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