Virtual Try-On app Development Like Doppl

The shift towards virtual shopping experiences is gaining momentum, and one of the most exciting advancements is virtual try-on technology. Apps like Doppl offer users the ability to try on clothes digitally, providing a more interactive and personalized shopping journey. By using AI, these platforms create realistic visualizations of how clothing will look on an individual, allowing users to make more informed decisions before making a purchase.

This technology not only enhances the shopping experience but also helps reduce product returns, a common challenge in online retail. Users can see exactly how items will fit and appear, eliminating much of the uncertainty associated with online shopping.

In this blog, we will talk about how apps like Doppl are transforming the e-commerce landscape and the core technologies behind this app. We will also discuss key features you should consider, the development steps and guide you with the estimated cost to launch this platform properly, as we have developed and delivered multiple AI products for many companies. IdeaUsher has the expertise to launch your virtual try-on app like Dopple that not only solves the customers’ and users’ needs but can also compete with other apps in the market.

Why You Should Invest In An AI Virtual Try-On App?

The Virtual Try-On technology market is estimated to be valued at USD 1.2 billion in 2024 and is projected to reach USD 4.5 billion by 2033, growing at a CAGR of 16.5% from 2026 to 2033. This growth is driven by increasing consumer demand for immersive, personalized shopping experiences and advancements in AI and AR technologies.

GlamAI, a San Francisco-based AI startup, has made impressive strides since launching in June 2024. With over 1.3 million monthly active users and an annual recurring revenue (ARR) of $5 million, the app’s success can be attributed to its engaging AI-generated filters and virtual try-on features, which resonate with both users and brands.

Perfect Corp., a leader in AI and AR solutions for beauty and fashion, saw a 12.5% year-over-year revenue increase in 2024, reaching $60.2 million. This growth was driven by the popularity of its YouCam mobile apps and virtual product try-on services, which allow users to virtually try on makeup, skincare, and fashion items.

Zeekit, acquired by Walmart in 2021, raised $16 million in funding and achieved an estimated annual revenue of $11.6 million. The company’s AI-driven virtual try-on technology was integrated into Walmart’s e-commerce strategy, highlighting the importance of such solutions in enhancing the online shopping experience.

Investing in AI virtual try-on apps offers a strong opportunity to tap into the rising demand for immersive, personalized online shopping. Success stories like GlamAI, Perfect Corp., and Zeekit show their potential for high returns. As the market grows, early investment could bring substantial benefits.

What Is Virtual Try-On App: Doppl?

Doppl is an AI-powered virtual try-on app that uses artificial intelligence to allow users to visualize how different outfits might look on a digital version of themselves. By uploading a full-body photo, users can try on clothes from photos or screenshots of outfits they encounter online, such as on social media or in stores. The app uses AI to generate realistic images and even short videos of users wearing the selected outfits, providing a dynamic preview of how the clothes fit and move.

How Doppl Works?

Doppl is an AI-powered virtual try-on app developed by Google Labs, designed to enhance online shopping by allowing users to try on clothes virtually. The app uses cutting-edge augmented reality and generative AI technology to simulate how various outfits will look on the user’s body in real-time. Here’s how Doppl works and the technology behind it:

1. User Input – Uploading a Full-Body Photo

Doppl uses computer vision and machine learning to analyze users’ full-body photos for the virtual try-on experience. Users upload their image in a natural pose, avoiding obstructions like hats or loose clothing, to ensure accurate pose detection and body mapping for realistic results.

2. Outfit Selection – Using Images or Screenshots

Doppl allows users to select outfits from its catalog or upload photos/screenshots of clothing they want to try. The app’s AI algorithms detect and extract relevant details like color, texture, and fabric from these images, enabling users to try on items from various sources.

3. Virtual Try-On – Mapping the Outfit

Using AI-based image processing and deep learning, Doppl maps the selected outfit onto the user’s photo. The app takes into account body measurements, fabric drape, and natural body movements to create a realistic fit, adjusting for various poses and ensuring a natural appearance.

4. Dynamic Visualization – AI-Generated Animation

Doppl generates AI-based animations to show users how clothing moves and fits in real life. Using motion tracking and generative AI, the app simulates how garments flow, stretch, and shift with the user’s movements, offering a dynamic, lifelike representation of the outfit.

5. Interactive Features – Save and Share

Once users visualize their outfit, Doppl allows them to save and share their virtual try-ons via cloud storage. This feature ensures that users can securely store images and videos, making it easy to revisit or share their looks with friends and on social media.

6. User Privacy and Feedback

Doppl ensures user privacy with end-to-end encryption and allows users to share feedback for improving AI accuracy. Additionally, it collects data on user interactions to further personalize the experience and continuously enhance the app’s performance, ensuring a secure and tailored service.

Core Technologies Behind Virtual Try-On App

The success of a virtual try-on app relies on the integration of several advanced technologies that work together to provide a seamless, realistic, and personalized experience. These core technologies enable the app to map clothing accurately to the user’s body, creating a highly interactive shopping experience.

1. Augmented Reality

AR overlays digital content (like clothing) onto a real-world image, enabling users to see how items would look in their actual environment. Doppl uses AR to map outfits onto the user’s body, ensuring that the clothing fits in a natural, realistic way.

How It Works:

• Doppl’s AR technology uses the user’s full-body photo and projects the selected clothing onto the photo in real-time.
• The system uses depth-sensing technology to adjust the clothing as the user’s body moves.
• The clothing shifts and adapts to the body’s movements, creating a lifelike virtual try-on experience.

2. Artificial Intelligence and Machine Learning

AI and machine learning help Doppl understand body shape, size, and movement. Over time, the app learns to make better predictions about what will fit and look best on the user.

How It Works:

• Doppl’s AI algorithms process the user’s input (such as body type and image) to generate a realistic virtual try-on.
• The system continually learns from user feedback, refining its ability to make better predictions about fitting outfits.
• AI-based recommendations help personalize the shopping experience by suggesting similar outfits that align with the user’s preferences.

3. Computer Vision

Computer vision enables Doppl to analyze and interpret visual data, such as the user’s body shape and the design of the clothing being tried on.

How It Works:

• Doppl uses pose detection algorithms to track the user’s body position and structure.
• This allows the app to accurately map the clothing items onto the user’s image, considering body shape, size, and specific measurements (like waist and chest circumference).
• It employs 3D modeling to ensure the clothes fit realistically, adjusting to the body’s movements and ensuring the clothes drape and behave correctly.

Why Virtual Try-Ons Like Doppl Are Game-Changing for Fashion Retail?

Virtual try-ons like Doppl are transforming fashion retail by using AI, AR, and 3D simulation to enhance online shopping with greater convenience, personalization, and efficiency. Here’s why they’re game-changing.

1. Solving the “Fit” Problem in Online Shopping

One of the biggest challenges in online shopping is the inability to try on clothing before purchasing. Doppl’s virtual try-on technology solves this by allowing users to upload a photo or video of themselves, creating a 3D avatar. The app’s AI algorithms simulate realistic garment fitting and fabric movement, eliminating the uncertainty of sizing and fit, reducing returns and increasing customer satisfaction.

2. Reducing Returns and Improving Sustainability

High return rates, often due to poor fit or unmet expectations, are a major issue in online fashion retail. Doppl’s virtual try-on technology allows customers to accurately see how clothes will fit before purchasing, reducing returns. This not only saves retailers on logistics and supply chain costs, but also helps sustainability goals by cutting down on shipping waste and carbon emissions.

3. Personalized Shopping Experience

Doppl creates a highly personalized shopping experience by using AI to analyze the customer’s body shape, size, and preferences. Over time, the app learns from interactions, providing better product recommendations tailored to the user’s style, body type, and purchase history. This level of personalization leads to stronger customer engagement, loyalty, and a more efficient shopping process.

4. Enhancing Customer Confidence in Purchases

The uncertainty of buying clothes without trying them on is a significant barrier to online shopping. Doppl enhances customer confidence by providing hyper-realistic virtual try-ons that show how clothing fits and moves on their body. This results in fewer abandoned shopping carts, higher purchase likelihood, and increased social commerce as customers share their virtual outfits on social media.

5. Improving Inventory Management for Retailers

Doppl’s technology offers valuable insights for retailers by collecting data on customer preferences, popular items, and sizing trends. Retailers can use this data to optimize inventory management, forecast demand, and identify fit issues or size preferences that impact purchasing decisions. This data-driven approach helps retailers stock items more efficiently, ultimately improving conversion rates and reducing unsold stock.

6. Facilitating Virtual Fashion Shows and Lookbooks

Doppl’s virtual try-on technology also facilitates digital fashion experiences, such as virtual fashion shows and lookbooks. Customers can interact with the latest collections in real-time, either via the app or live streams. This immersive experience encourages engagement, helping customers visualize how clothing fits and how they can style individual pieces, driving informed purchasing decisions.

7. Expanding Accessibility and Inclusivity

Virtual try-ons offer significant advantages in breaking down barriers to shopping. Doppl makes fashion more accessible to diverse body types and demographics, allowing users to try on clothes tailored to their unique bodies. The app also promotes inclusivity by offering virtual try-ons that represent a broad range of ethnicities, skin tones, and body types, supporting the growing demand for diversity and body positivity in fashion.

8. Future-Proofing the Fashion Retail Industry

With the rise of digital shopping and the growing demand for immersive experiences, Doppl’s virtual try-on technology helps future-proof the fashion industry. As virtual reality (VR) and metaverse fashion gain traction, integrating these technologies now allows retailers to stay competitive in a rapidly evolving market, positioning their businesses to meet consumer expectations for technology-driven shopping experiences.

Key Features to Include in a Doppl-Like Virtual Try-On App

Creating a Doppl-like virtual try-on involves integrating AI, AR, 3D modeling, and machine learning for an immersive shopping experience. Developers must ensure the platform is intuitive, seamless, and personalized to engage users and enhance shopping. The key features listed are essential for building such an experience.

1. Realistic 3D Avatar Creation and Body Mapping

The foundation of an AI-powered Virtual Try-On App like Doppl lies in creating a personalized 3D avatar that mirrors the user’s true body dimensions and posture. Body detection algorithms analyze photos or videos to extract measurements, while custom body mapping allows for precise adjustments. This ensures a highly accurate garment fit, refining the experience based on preferences and previous try-ons.

2. Advanced Fabric and Cloth Simulation

For a lifelike virtual try-on, the AI-powered Virtual Try-On App like Doppl accurately simulates how fabrics behave on the body. Cloth physics modeling, using techniques like finite element analysis (FEA), mimics how different materials stretch, fold, or drape based on body movements. The app ensures garments follow natural body contours and react dynamically to various poses for a more realistic try-on experience.

3. Real-Time Virtual Try-On

Augmented Reality (AR) brings the virtual try-on experience to life in an AI-powered Virtual Try-On App like Doppl. By using ARKit (iOS) and ARCore (Android), users can see 3D garments overlaid onto their bodies in real-time. This technology allows clothing to adjust to the user’s movements, providing accurate fitting and scaling as they interact with their avatar, offering a more dynamic shopping experience.

4. Personalized Fit Recommendations Powered by AI

The AI-powered Virtual Try-On App like Doppl, personalizes the shopping experience by providing AI-powered fit predictions based on the user’s body shape, measurements, and style preferences. The app learns from past interactions and feedback, refining its recommendations over time. This enables it to suggest better-fitting garments, improving the overall shopping experience and boosting customer satisfaction by offering tailored suggestions.

5. 360-Degree Clothing View and Zoom-In Functionality

To give users a comprehensive view of the garments, an AI-powered Virtual Try-On App like Doppl offers a 360-degree clothing view and zoom-in functionality. Users can rotate their avatar to view the garment from every angle, and zoom in on specific details like fabric texture and stitching. This ensures that customers can thoroughly examine garments, helping them make more informed purchasing decisions.

6. Virtual Wardrobe and Outfit Planning

A virtual wardrobe in the AI-powered Virtual Try-On App like Doppl allows users to save their favorite outfits, mix and match garments, and plan their purchases. This feature enhances personalization by enabling users to create digital closets, organize items, and receive outfit suggestions based on preferences, trends, and seasonal collections. It makes the shopping experience more organized and efficient for users.

7. Social Sharing and Collaborative Shopping

The AI-powered Virtual Try-On App like Doppl fosters an interactive and community-driven shopping experience by allowing users to share virtual try-ons on social media platforms. This social sharing feature encourages engagement and boosts brand visibility. Additionally, collaborative shopping allows friends and family to join the session, providing feedback, suggesting items, or voting on outfits, enriching the overall shopping experience.

8. Seamless E-Commerce Integration

An essential feature of the AI-powered Virtual Try-On App like Doppl is its seamless integration with e-commerce platforms. After trying on clothes virtually, users can easily click through to product pages for quick purchases. The app ensures that the try-on experience is consistent across different platforms, whether on desktop, mobile, or website, allowing users to transition smoothly from virtual fitting to actual buying.

9. Size and Fit Adjustment Tools

The AI-powered Virtual Try-On App like Doppl includes size and fit adjustment tools, allowing users to digitally modify the fit of clothing on their avatar. Users can adjust areas like sleeve lengths or waist sizes to better visualize how garments will look on their bodies. The app also suggests optimal sizes based on previous try-ons, ensuring a more accurate and satisfying virtual fitting experience.

10. Analytics and Retailer Insights

By integrating analytics tools into the AI-powered Virtual Try-On App like Doppl, retailers gain valuable insights into customer behavior. The app tracks popular items, body types, and sizing preferences, enabling brands to optimize their inventory and marketing strategies. Product popularity data and fit issues also help predict trends, giving retailers an edge in the competitive fashion market while improving customer satisfaction.

Step-by-Step Guide to Developing a Doppl-Like AI Virtual Try-On App

Creating a Doppl-like virtual try-on app involves integrating AI, 3D modeling, computer vision, machine learning, and AR for a seamless, immersive shopping experience. Here’s a step-by-step guide to develop such an app, focusing on user satisfaction, customization, and scalability.

Step 1: Define the Project Scope and Objectives

At IdeaUsher, we start by working closely with you to define the project scope and set clear objectives for the virtual try-on app. We’ll collaborate to identify whether the app will serve consumers directly, fashion retailers, or both. We’ll help you determine product categories, such as clothing, eyewear, or accessories, and outline essential features like 3D avatar creation, fabric simulation, AR functionality, and personalized fit recommendations. Based on this, we’ll assist you in deciding the monetization strategy, whether the app will be B2B, consumer-facing, or a mix of both.

Step 2: Data Collection and Preparation

Our AI developers will help you collect the necessary data for building a robust AI-driven virtual try-on app. We’ll work with you to gather user data, such as diverse images and videos with different body types and lighting conditions, and ensure that it’s properly anonymized for security. We will source garment data including 3D models and high-quality images with accurate fabric details. Throughout the process, we’ll ensure that data privacy and security are top priorities, and that users give consent through privacy policies and consent forms.

Step 3: Develop 3D Avatar Creation and Body Mapping

Our team will use advanced computer vision and pose estimation algorithms (e.g., OpenPose) to develop highly accurate 3D avatars for users. By analyzing their uploaded images or videos, we’ll map the user’s body shape, height, and size. We’ll also build in the ability for users to input personal measurements to refine their avatar’s accuracy. Our AI experts will incorporate depth perception technology to ensure avatars maintain correct proportions when viewed from various angles and dynamically adjust to user movements for a realistic fitting experience.

Step 4: Implement Cloth Simulation for Realistic Fit

To provide a realistic virtual try-on experience, our developers will integrate cloth physics modeling using techniques like finite element analysis (FEA) and smoothed-particle hydrodynamics (SPH). We’ll simulate how different fabrics (e.g., cotton, silk, denim) behave based on body movements. Users will have the ability to adjust garment fits in real-time, such as lengthening sleeves or tightening waistbands, to better visualize how the garment will look on their body. This level of dynamic interaction will make the virtual experience feel lifelike.

Step 5: Integrate Augmented Reality for Real-Time Visualization

Our AR developers will integrate ARKit (for iOS) and ARCore (for Android) to offer a seamless real-time virtual try-on experience. With AR, users will be able to overlay clothing onto their bodies via their phone or tablet’s camera. As users move, the virtual garment will adjust in real-time, ensuring it fits naturally. Our team will ensure that the motion tracking is precise, providing a smooth interaction where the virtual clothing adapts to the user’s body position and movement, making the experience as lifelike as possible.

Step 6: Personalization with AI and Machine Learning

Our AI experts will leverage machine learning to make the app more personalized and efficient. By processing user data, the system will predict the best-fitting size and garment style based on each user’s body type, preferences, and past interactions. Over time, the AI will learn from user feedback and improve its suggestions, offering personalized styling recommendations. We will also use AI-based fit prediction to suggest clothes that best match users’ unique styles, ensuring they receive a tailored and personalized shopping experience.

Step 7: Develop a Seamless E-Commerce Integration

At IdeaUsher, we ensure that your virtual try-on app integrates flawlessly with e-commerce platforms. Our developers will connect the app with backend systems via API integrations, allowing real-time syncing of inventory, product catalogs, and user accounts. After users virtually try on clothing, they’ll be able to add items directly to their shopping cart, with updated prices and availability. We’ll focus on making the purchase process as smooth as possible, so users can buy directly from the app with minimal friction, regardless of the device they’re using.

Step 8: Design UI/UX Infrastructure

Our UI/UX design team will create an intuitive, user-friendly interface that makes navigating the app effortless. We will design the app with simple navigation so that users can easily upload photos, try on clothes, and adjust their avatars. Clear instructions and helpful tutorials will guide users through the process, making it easy to understand how to use the virtual try-on feature. We’ll ensure that the app has a responsive design, providing a consistent experience whether users are on desktop, mobile, or tablet.

Step 9: Testing and Iteration

Once the app is ready, we’ll initiate extensive user testing to identify any issues in body mapping, garment fitting, or AR rendering. Our developers will focus on performance testing, ensuring the app works efficiently, even under high load. We’ll use feedback loops to collect data from real users, allowing us to refine the AI’s fit predictions and improve garment simulations. Regular iterations after launch will ensure that the app continues to improve and evolve, offering users a seamless and accurate virtual try-on experience.

Step 10: Launch and Scale

When the app is fully developed and tested, we’ll assist you with a targeted marketing campaign and collaborations with fashion brands to drive adoption. Our team will start with a select group of retailers to ensure everything functions correctly before scaling. We will focus on scalability, ensuring the backend infrastructure can handle increasing numbers of users, products, and virtual try-on simulations. With cloud services like AWS or Google Cloud, we will ensure your app can scale seamlessly to accommodate growing demand and provide a smooth user experience.

Cost To Develop A Virtual Try-On App Like Doppl

Developing a high-quality virtual try-on app requires careful consideration of various technical and design factors. From advanced AI and AR integration to seamless e-commerce syncing, understanding the cost breakdown for each phase is essential to building a successful and scalable solution.

Development Phase	Description	Estimated Cost
Consultation and Planning	Initial phase to define the project scope, target audience, key features, and monetization strategy. Aligning business objectives.	$5,000 – $15,000
Data Collection and Preparation	Gathering and preparing high-quality user data, garment data, and anonymized user feedback for AI training.	$15,000 – $30,000
3D Avatar Creation and Body Mapping	Developing accurate 3D avatars using computer vision, pose estimation algorithms, and custom body mapping features.	$30,000 – $60,000
Cloth Simulation for Realistic Fit	Implementing cloth physics modeling and fabric simulations to mimic real-world garment behavior with various fabric types.	$35,000 – $70,000
Augmented Reality (AR) Integration	Integrating AR technology (ARKit and ARCore) to enable real-time virtual try-ons and ensure realistic garment visualization.	$25,000 – $50,000
Personalization with AI and Machine Learning	Developing AI algorithms to predict best fit, provide personalized style recommendations, and improve accuracy over time.	$30,000 – $65,000
E-Commerce Integration	Ensuring seamless integration with e-commerce platforms, including shopping cart and inventory syncing.	$20,000 – $40,000
UI/UX Design	Designing an intuitive, user-friendly interface across desktop, mobile, and tablet platforms.	$10,000 – $30,000
Testing and Iteration	Conducting user testing, performance testing, and refining the app based on feedback for continuous improvement.	$15,000 – $40,000
Launch and Marketing	Targeted marketing campaigns, fashion brand partnerships, and app scaling to drive awareness and adoption.	$20,000 – $50,000

According to IdeaUsher, the estimated cost to develop a Dopple-like virtual try-on app ranges from $70,000 to $150,000, but the final amount depends on factors such as the app’s complexity, features, technology stack, and the level of customization needed.

Consult with IdeaUsher to discuss your project thoroughly and receive a tailored development plan aligned with your business objectives and budget. Our skilled team will support you at every stage to ensure a smooth and successful app launch.

How to Monetize Your AI Virtual Try-On App?

Monetizing an AI virtual try-on app can be profitable with increasing demand for digital shopping. To succeed, develop a strategy aligned with consumer and retailer goals. Here are some ways to turn your app into a revenue-generating platform.

1. Subscription-Based Model for Retailers

The subscription-based model offers a flexible pricing system tailored to fashion retailers. With tiered pricing plans, retailers can choose from basic to advanced packages, depending on their needs. Larger retailers can benefit from enterprise solutions, while optional add-on features provide further customization.

2. Pay-Per-Use or Transaction-Based Model

The pay-per-use or transaction-based model charges retailers based on the usage of the virtual try-on technology. This model works well for businesses with fluctuating demand, offering charges per virtual try-on or per-transaction fees, aligning costs with customer actions and sales.

3. In-app Purchases for Customization and Features

In-app purchases can drive revenue by offering avatar customization, advanced virtual fitting tools, and exclusive filters or effects. Users can pay to personalize their digital twin, access 3D try-ons, or enjoy seasonal and themed outfits, improving the overall shopping experience.

4. White-Label Solutions for Businesses

White-label solutions allow businesses to license your virtual try-on technology, rebrand it with their own logos and custom features. These companies can integrate the system into their e-commerce platforms, while you offer ongoing support and maintenance for a fee, creating a sustainable revenue model.

Conclusion

Virtual try-on apps like Doppl are reshaping the way people shop by offering an innovative and immersive experience. By combining AI and computer vision, these apps allow users to virtually try on clothes, helping them make more confident purchase decisions. The ability to visualize products before buying not only improves customer satisfaction but also reduces return rates, benefiting both customers and retailers. As the demand for personalized and interactive shopping experiences grows, virtual try-on technology will continue to play a key role in the evolution of e-commerce, enhancing the overall shopping journey for consumers.

Why Choose IdeaUsher to Develop Your Virtual Try-On App?

At IdeaUsher, we specialize in creating AI-powered Virtual Try-On Apps that deliver an immersive and realistic shopping experience. Our team focuses on developing accurate 3D avatars, realistic garment simulations, and seamless AR integrations, ensuring your app stands out in the fashion tech industry.

Why Partner with Us?

• AI Expertise: Our expert team uses cutting-edge AI technologies to enhance body detection, fabric simulation, and user personalization.
• End-to-End Solutions: We handle everything from avatar creation and AR integration to e-commerce platform syncing, providing a comprehensive solution.
• Scalable and Secure: We design apps that are highly scalable, secure, and able to evolve with your business needs.
• Proven Track Record: With a proven track record in AI and fashion tech, we’ve successfully delivered powerful virtual try-on solutions to industry leaders.

Explore our portfolio and see how we can help you revolutionize the fashion retail experience with a Virtual Try-On App!

Connect with us for a free consultation today!

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