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Fashionette Achieves +10% Profit Growth with Predictive Pricing

Learn how Fashionette used AI optimized pricing to hit its business targets and automate pricing processes.
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Company Overview

Fashionette is a leading online retailer in the luxury fashion segment, catering to style-conscious consumers across more than 20 countries. Founded in 2008 and headquartered in Düsseldorf, the company employs around 250 people and specializes in premium accessories, shoes, and apparel. Its customer base is primarily in the DACH region (Germany, Austria, and Switzerland). 

To manage its large and diverse assortment, Fashionette sought a smarter, more efficient way to handle pricing. Their existing rule-based approach and manual processes were too slow and rigid to react effectively to a fast-changing market. By partnering with 7Learnings, Fashionette automated its pricing strategy, leading to substantial profit improvements.

Fashionette logo

Fashionette increases profitability while reducing complexity

Challenges

  1. Fashionette’s pricing decisions were primarily handled manually via CSV uploads. This process was inefficient and resource-intensive, making it challenging to adapt prices dynamically.
  2. Despite having a wealth of customer and product data, Fashionette could not fully leverage it in pricing decisions. This led to missed opportunities to optimize profit and revenue across categories.
  3. Prior to working with 7Learnings, pricing decisions heavily relied on a few individual decision makers. This created a bottleneck and increased the risk of inconsistency and human error.
  4. The limitations of rule-based pricing made it difficult to factor in real-time market trends, customer behavior, or seasonal changes. It also hampered the ability to forecast the outcomes of pricing strategies.

Solution

  • Fashionette adopted 7Learnings’ AI-powered pricing platform to replace manual processes with predictive automation. This enabled the team to make faster, data-informed pricing decisions while significantly reducing operational effort.
  • The 7Learnings platform allowed Fashionette to simulate the impact of price changes before implementing them. This forecasting capability meant pricing strategies could directly align with business goals such as profit, revenue, or sales volume.
  • With the ability to set individual pricing goals for different product segments, Fashionette achieved granular control over its pricing strategy. AI-driven optimization delivered better results than blanket rules ever could.
  • The intuitive 7Learnings interface allowed for easy price review, scenario analysis, and implementation, even for stakeholders without deep technical knowledge. This democratized access to pricing insights and improved cross-functional collaboration.

7Learnings helped achieve:

+10%

profit increase

Automated

pricing processes

Conclusion

Fashionette transformed its pricing from a manual, rule-based process to a dynamic, AI-driven system using 7Learnings. By automating price setting and leveraging predictive analytics, the company scaled pricing efficiency across its extensive catalog and achieved a remarkable +10% increase in profit. With stronger forecasting, greater agility, and reduced manual effort, Fashionette is now well-positioned to grow its leadership in luxury fashion retail.

Fashionette logo
“Working with 7Learnings allowed us to automate our pricing decisions, align them with our strategic goals, and unlock substantial margin growth in a short amount of time.”
Leonie Schumacher
Head of Commercial Controlling, Fashionette

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