Elevating E-commerce: Virtual Try-On for Fashion Shopping

A top online fashion store had difficulty creating an exciting and interactive shopping experience for its customers. The inability to try on clothes virtually led to high return rates and dissatisfied customers.

To overcome this problem and enhance customer satisfaction, the client needed Ai consulting services that allowed users to virtually try on clothes and mix and match different styles.

Customers often found it difficult to make confident purchasing decisions online due to the absence of a virtual try-on feature. This resulted in high return rates and reduced customer satisfaction. The challenge was to provide a solution that addressed this drawback and offered a more engaging shopping experience.

To tackle the challenge, Generative AI models through an AI consultant were employed and trained on two components: GMM and TOM.

They trained these models using a Fashion dataset and human pose data. We developed advanced image processing algorithms to accurately identify body pose, backgrounds, and clothing patterns. This data was crucial in providing a realistic virtual try-on experience for users.

The implementation of this solution yielded several benefits. User engagement on the website/app significantly improved, with users spending more time exploring the virtual try-on feature.

Sales rose as users could confidently try on virtual clothes and mix and match styles. The solution enhanced the shopping experience, reduced return rates, and increased customer satisfaction.