Augmented reality e-commerce: Types of try-ons for online-shops

In the digital retail landscape, the forefront of revolutionizing the online shopping experience lies with AR-based virtual try-on (VTO). As brands actively seek innovative solutions to mitigate high return rates and elevate customer satisfaction, virtual try-on emerges as a promising avenue.

In this exploration, we will delve into the diverse technological manifestations of VTO presently available, emphasizing the advantages and drawbacks of each to aid in evaluating what may be most suitable for your business. These approaches encompass real-time 3D virtual try-on, generative image try-on, Avatar try-on, and AI survey-based try-on. We will analyze the practical application, specific technical prerequisites, benefits, constraints, and the potential for an integrated future solution for each.

1. Real-Time 3D Virtual Try-On

Technical Prerequisites

This method necessitates high-fidelity 3D product models, AR body-tracking software, a camera-equipped smartphone or computer, and internet connectivity.

Advantages

• Provides an immersive and interactive experience, enabling customers to visualize garments and accessories from varied angles and in motion, closely simulating the in-store experience.

• Easily embeddable into any e-commerce web page or platform.

• Facilitates users in capturing realistic images and videos of themselves wearing the garment, which can be shared with friends for feedback.

• When coupled with AI technology, it can analyze a user’s facial or body shape to recommend well-fitting products. For makeup, it can assess skin tone and texture to suggest relevant products.

• On-device computation ensures that no personal data is transmitted to the server, addressing privacy concerns.

• The 3D try-on technology not only realistically displays clothing but also creates an immersive user experience. The 3D engine can generate real-time effects, enhancing the try-on process and leaving a lasting impression. This can generate heightened interest and traffic to the product’s e-commerce page. Additionally, if the same experience is utilized on the product page with effects disabled, it can lead to substantial cost savings of 70-90% in development.

• Achieving a lifelike appearance: Leveraging the capabilities of the 3D rendering pipeline allows for nearly identical 3D quality to the actual product, enhancing the immersive nature of the try-on process.

• Mix and match outfits seamlessly: Users have the freedom to experiment with various combinations of tops, bottoms, and accessories, enabling them to visualize different ensemble possibilities and understand how different elements complement each other. This flexibility extends to assessing the compatibility of specific clothing items.

• Stand out with cutting-edge technology: Embrace a distinctive technological approach that embodies the future of retail, setting your brand apart from competitors.

Cons:

• Expense of developing 3D models: Creating detailed 3D models, particularly for items like sunglasses and watches, can be costly. However, there are AI solutions available that can automate the process by generating 3D models from 2D images.

• Requirement for high-processing devices: The necessity for devices with robust processing capabilities may pose a barrier to widespread adoption.

2. Generative Image Try-On:

Before and after images showcasing garment superimposition.

Technical Requirements:

This method utilizes AI algorithms to overlay clothing items onto user-uploaded photos, relying on machine learning models and image processing technology.

Pros:

• Personalized try-on experience: Offers users a customized preview by incorporating clothing items into their own photos swiftly.

• Low-touch solution: Eliminates the need for special preparation of clothing assets.

• Cost-effective option: Particularly beneficial for small to medium-sized businesses as it reduces reliance on physical photo shoots, models, and associated logistics.

• Cloud-based computation: No specific device requirements as all processing occurs in the cloud.

Cons:

• Limited interactivity and realism: The static nature of image-based try-on may not accurately convey fit and drape, lacking the dynamic engagement of real-life or AR try-ons.

• Server-side photo processing: User data storage and analysis in the cloud raise privacy concerns.

• Lack of multi-angle examination: Users cannot assess garment appearance or fit from different perspectives.

• Risk of unrealistic expectations: Idealized renderings may create false impressions.

• Susceptibility to technical glitches: Potential disruptions to user experience due to technical issues.

• Challenges with 3D mirror experiences: User engagement may suffer if photo uploads and result waits hinder an interactive and enjoyable try-on experience. Engaging and memorable interactions may be challenging without interactivity.

3. Avatar Try-On

Technical Requirements

This approach involves generating a digital representation of the user, utilizing their measurements and employing avatar modeling technology.

Pros

• Offers a personalized try-on experience without the necessity for real-time video or high-quality photos, ensuring privacy and convenience for users.

• Gathers precise body measurements, yielding valuable data for tailored marketing strategies and product recommendations.

• In the future, this could serve as an interoperable asset, functioning across various fashion retail platforms to assist shoppers in understanding accurate size fittings.

Cons

• The general nature of avatars may not faithfully depict individual body shapes, potentially impacting the perceived fit of clothing items.

• Lacks the authentic feel of in-person shopping, as users encounter a representation of themselves rather than their actual appearance.

• Requires users to input personal measurements, potentially raising concerns about privacy or reluctance to share sensitive data.

4. Size Recommendation Try — on Based on Surveys

Technical Requirements

Relies on algorithms that suggest sizes based on user-provided measurements and preferences, necessitating a comprehensive database and user interface.

Pros

• Straightforward and accessible, demanding minimal technical infrastructure and providing immediate size suggestions compared to more advanced solutions such as 3D avatars.

• Respects privacy, as it does not require access to the camera.

• Available to a broad spectrum of users, requiring no special hardware or software beyond a basic web interface.

Cons

• Lacks the visual engagement found in other methods.

• The process of completing the survey may be tedious for some users, potentially leading to reduced utilization of the feature.

• Might not accommodate nuances in suitability and color preferences beyond basic fit measurements.

• The accuracy of recommendations heavily relies on the quality and honesty of the user-provided information.

• May offer more generic results compared to highly personalized systems, resulting in a less customized experience.

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