By Team 36: Annie Yang; Pinar Tetiker; Jad Abderrahmani-Ghorfi; Jelle Sanders
The fashion industry has been challenged by the shift to online shopping and the changing needs of customers in recent years. We saw a need in retailers to provide a more personalized shopping experience, and how Generative AI could be the solution. This is where DressSense steps in, A Virtual Stylist powered by GenAI that unserstands natural language and customer preference, right inside the their website or app.
The central idea of our business model is built around a continuous feedback loop that connects retailers, consumers, and our Generative AI system. After the retailers embed our AI stylist into their online stores as an API plug in, the consumers (end users) interacts with it directly. Every interaction generates valuable data, which is then fed back unto the system for model improvement. GenAI allows the system to learn from these insights and become more accurate and personalized over time. This continuous loop is how DressSense operates, and how we help retailers achieve business impact such as higher conversion rates, lower return rates, and better customer relationships. We chose to position DressSense as a B2B platform to avoid the high acquisition costs and competition of customer-facing apps. DressSense focuses on enhancing the e-commerce experience that retailers already provide, with the goal to build long-term partnerships.
Unlike platformss that use AI only for internal optimization, DressSense enhances the consumer experience directly. As 81% of consumers now prefer personalized shopping, retailers that fail to deliver risk lose market share to those that do. GenAI’s ability to interpret language and context means personalization is no longer limited to rigid algorithms. We also leverage the data collection and the higher layer of our business is to generate from data-as-a-service.
With the help of DressSense we expect retailers to raise click-through rates from the industry average of 3% to around 10%. Average order values can see a growth from roughly €150 to €250 per purchase. Moreover, for startups adopting DressSense, the cost is around €60,000 compared to the €600,000 often spent building AI systems from scratch. On the business side, DressSense targets a three times ROI within the first growth phase. But the long-term impact goes beyond revenue, the potential for a more data-driven process and sustainable business growth may not be quantifiable in the short term but crucial for the future business development.
Although DressSense could be the pioneer of next generation e-commerce experienc, we must mention the potential risk and challenges as well. The challenge for data quality and consistency is important since incomplete data could cause inaccurate AI recommendation. Another concern is data privacy. Because the platform uses customer behavior to improve personalization, full GDPR compliance can not be neglected. Finally, we want to avoid the perception of promoting overconsumption. DressSense aims to balance personalization with responsible shopping. We help people buy better, not just more.
