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What is WANNA?

WANNA's innovative Virtual Try-On technology transforms the online shopping landscape by enabling customers to utilize augmented reality to try on products virtually, closely mimicking the experience of shopping in a physical store. This captivating feature allows users to creatively combine various items with different outfits, boosting their satisfaction and confidence when making purchasing decisions. The platform supports a diverse array of product categories, including shoes, bags, watches, jewelry, apparel, scarves, home decor, premium beverages, and fragrances. With a user-friendly web integration that can be executed in just a single day, consumers can access this feature without the need for additional applications. Brands are able to leverage the 3D assets created for these products, optimizing their usage across multiple channels to enhance their return on investment. WANNA's solutions are built upon comprehensive research into user experiences and insights gathered from luxury consumers, forming a complete ecosystem that closely emulates the in-store shopping experience. Additionally, this technology provides brands with an opportunity to reconnect with shoppers who may have browsed their physical locations but were reluctant to complete their purchases, effectively reigniting their interest and nudging them toward a final decision. Ultimately, WANNA's approach not only enhances customer engagement but also drives sales by bridging the gap between online and offline shopping experiences.

What is WAIR?

WAIR revolutionizes the shopping experience by helping customers find products that fit them perfectly. Brands choose WAIR not just for its size and fit suggestions, but also for the extensive benefits it offers. By leveraging the world's largest database of 3D body scans, WAIR allows businesses to tailor their products to match the physical characteristics of their customers, thus streamlining their operations. The WAIR Fit Advisor seamlessly integrates into your online retail platform, assisting shoppers in choosing the correct sizes while also gathering critical data for operational teams. This information is instrumental in enhancing design, inventory management, and marketing strategies that address the diverse body shapes of the clientele. Furthermore, WAIR aids customers in establishing benchmarks, refining their grading systems, and managing regional inventory effectively, while also facilitating the use of realistic 3D avatars in their digital environments. With over 2,000,000 3D body scans amassed over four years, WAIR’s solutions are robust and data-driven. Retailers adopting WAIR's Fit Advisor often witness an impressive 28% increase in conversion rates and a 21% reduction in size-related returns, which results in improved customer satisfaction and operational effectiveness. By focusing on fit and personalization, WAIR ultimately enhances the entire shopping journey for brands and consumers alike, making it more efficient and enjoyable. As a result, both businesses and shoppers benefit from a more tailored approach to online retail.

Media

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

API Availability

Pricing Information

Free
Free Version

Pricing Information

Pricing not provided

Supported Platforms

SaaS
iPhone

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Online Training

Training Options

Documentation Hub
Online Training

Company Facts

Organization Name

WANNA

Company Location

United States

Company Website

wanna.fashion/virtual-try-on

Company Facts

Organization Name

WAIR

Date Founded

2020

Company Website

getwair.com

Categories and Features

Size Recommendation

Not specified

Virtual Fitting

Not specified

Virtual Try-On

Not specified

Categories and Features

Size Chart

Not specified

Size Recommendation

Not specified

Virtual Fitting

Not specified

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