BSTN, with different objectives for different product lines, achieves stellar performance with Differs:

Munich-based BSTN is a leading premium sportswear and streetwear retailer, known for offering limited-edition sneakers and apparel from top brands like Nike, Jordan, and Adidas. Founded in 2008, BSTN evolved from a grassroots brand to an internationally recognized retailer.

The Pain 💥: Optimizing pricing strategies across diverse product lines is a time-consuming process. Especially when there are different objectives, namely, maximizing margin and stock clearance.

As BSTN has a wide range of products, it still uses the manual pricing method. It was time-consuming and overwhelming to adjust prices dynamically for seasonality or product-specific factors. To make the matter worse, customer price sensitivities vary across the extensive range of products.

With Seasonal products and Never Out of Stock (NOS) products, each product required different strategies. BSTN aims to reduce excess inventory for outdated seasonal products without sacrificing significant profit. On the other hand, BSTN would rather maximize profit margins for its core product.

To remain competitive, BSTN need to figure out which products are sensitive to low competitor prices? and by how much? BSTN required a new way of working. The one that is more efficient, faster, and flexible.

The Cure 🧪: Tailoring the sale prices to match purchasing behavior in various scenarios of product lines and objectives.

Differs provides a platform that automates pricing decisions across diverse product lines. Differs' AI is tailored to objectives, price elasticity, and brand-specific insight which allows users to customize to

• Balance the profit margin and sales volume for NOS collection

• Adjust pricing and sell-through to avoid excess inventory for the current season items

• Reduce excess inventory while boosting revenue from old-season product lines

Not only for decision-making, the platform also provides a discount elasticity curve, helping BSTN understand customers' willingness to pay better and enabling the brand to adjust prices dynamically and strategically in the long run.

The Results ✨: +126% Quantity uplift, +20% revenue uplift for old collections, and +25% gross profit for NOS Collections.

During live A/B testing, as a comparison between the previous pricing strategy and Differs' price recommendation, BSTN managed to increase sales quantity for end-of-season and old stocks by +126%, resulting in a +20% revenue increase. For the Never Out of Stock (NOS) Collection, BSTN achieves a +25% gross profit over the year.

Differs' AI helps BSTN uncover customers' willingness to pay, allowing the store to tailor prices and plan scenarios for each strategy and product line. With Differs, BSTN realizes the full potential of each strategy for both Markdown optimization for old stocks and Price optimization for NOS.

Instead of blindly chasing competitor pricing, BSTN now has a rigid pricing model that helps them set the price that matches customer willingness to pay.

Final thought: Customer willingness to pay is the key

What allows BSTN to pursue different strategies for different product lines is the customer's willingness to pay. It helps brands unlock the new power not to only adjust short-term markdown strategy but also long-term pricing strategy.

Differs in three words? Efficient. Intelligent. Responsive.