Our client is a high-end menswear brand known for its exquisite craftsmanship and luxurious fabrics. While their products are renowned globally, the brand wanted to enhance the customer journey experience, especially in-store - their primary sales channel - where their customer assistants play a pivotal role.
The Challenge
The client identified an opportunity to boost sales by encouraging customers to purchase entire outfit combinations rather than single items, and wanted to upgrade their “clienteling app” - the digital platform used by store assistants - to include a personalized “outfit configurator”. The challenge of applying a data-driven approach to the “outfit configurator” was the lack on one hand of a proper style-based customer profile and product tagging. The goal was to develop a system that could suggest the best combinations of shirts, trousers, jackets, and accessories from their collection, thus enhancing the customer's shopping experience and increasing the average transaction value.
Innoleaps’ Solution
Our team was first tasked with creating a data-driven algorithm to combine different items into consistent outfits, and then match them with specific customer profiles with a preferred outfit and to a technology-driven solution to address this challenge. With that, we designed an outfit recommendation module that was rapidly tested and iterated upon with a panel of Customer Assistants in Asia, America and Europe.
Startup Collaboration and AI Technology Integration
To bring this concept to life, we scouted for innovative startups that could offer advanced visualization technologies to create new outfits from the clients' core component items. One of the engaged partners has been Bigthinx, a startup accelerated by our sister company Startupbootcamp, specializing in transforming flat 2D images into 3D models and dressing virtual avatars.
Implementation
The prototype we built was integrated into the clienteling app used by customer assistants in-store. Powered by AI-generated images, this app guided the sales process by displaying recommended outfit combinations. Customer assistants could easily show customers various looks and make real-time adjustments based on preferences and available stock.
Results
The introduction of the AI-driven outfit configurator transformed the customer shopping experience. It empowered customer assistants with a powerful tool to enhance their service, resulting in:
- Increased average transaction value due to the sale of complete outfits.
- Improved customer satisfaction as they could visualize how different pieces worked together.
- Enhanced efficiency in the sales process, making it easier for assistants to provide personalized recommendations.
Conclusion
By leveraging cutting-edge AI technology and partnering with industry-leading startups, we helped our client innovate their customer journey. The successful implementation of the outfit configurator app not only boosted sales but also set a new standard for customer service in the luxury menswear industry. This project exemplifies how technology can be harnessed to drive customer journey innovation and create a more engaging and personalized shopping experience.