Virtual Try-On Makeup App Development

Project background

Gone are the days when cosmetic purchases relied solely on physical store experiences. Today, retailers face the challenge of meeting customers’ heightened expectations for engaging in-store and online experiences. This transformation is fueled by technology, with mobile advancements such as chatbots and virtual makeover app development revolutionizing the beauty retail landscape.

As a leading player in the beauty and cosmetics retail sector, our client serves a diverse global customer base, with a significant presence in the United States. Recognizing the need to meet the evolving demands of their audience, the company prioritized the training of a substantial team of consultants. In a bid to optimize operations and reduce reliance on manual labor, the concept of custom solution for virtual makeup try-on was conceived.

We started with initial marketplace improvements and redesign. After that, we suggested an AI system capable of analyzing customers’ facial features and skin types to recommend the most suitable products, thereby elevating the overall shopping experience. Moreover, we empowered the solution with a chatbot and AR fitting room. 

This integration of AR/AI technology promises to reshape the beauty retail industry, offering personalized solutions and enhanced customer satisfaction in AI for beauty and cosmetics retail.

Business needs

Technical Assessment and Integration:

– Review the initial client’s solution to identify all technical limitations and explore potential integrations.

– Ensure seamless integration of augmented team members to enhance the existing marketplace, advancing AI in beauty industry.

Customer Service Enhancement:

– Minimize human effort while guaranteeing exceptional customer service.

– Develop strategies to balance quality with efficiency in customer service operations, optimizing AI for beauty and cosmetics retail.

Facial Analysis Application Development:

– Face recognition software development with facial analysis functionality to provide information about the user’s skin condition based on a photo.

– Prioritize reliability, accuracy, and user-friendliness in the application’s design to attract AI in beauty industry enthusiasts.

Personalized Recommendations:

– Implement algorithms to provide users with personalized recommendations for skincare products and cosmetics, tailored for AI for beauty and cosmetics retail.

– Ensure recommendations are based on the results of facial analysis and aligned with user preferences.

Virtual Try-On Experience:

– Create a virtual try-on feature for recommended products to facilitate user experience.

– Ensure seamless integration with the recommendation system to streamline the try-on process, enhancing user experience.

AI Cosmetic Consultant Chatbot:

– Develop a personalized AI chatbot to serve as a cosmetic consultant and respond to FAQs, optimizing for AI for beauty and cosmetics retail engagement.

– Ensure compliance with regulations and refrain from providing medical diagnoses, adhering to AI in beauty industry standards.

Product features

Solution

We began our partnership with this client by enhancing their web platform, adding features and refining the initial solution. As our collaboration progressed, the client presented us with new and challenging objectives: exploring market opportunities and integrating advanced AR and AI-powered features, like augmented reality makeup, smart chatbot and recommendation system, into their solution. As a result, we provided the following solutions for AI in beauty industry:

1. Refined Cloud Marketplace

2. AI Discovery 

3. Facial Skin Analysis 

4. Personalized Cosmetic Recommendations

5. GPT- Enhanced Customer Chatbot 

6. Virtual makeup Try-on Experience 

Phase #1: Marketplace improvement 

We assessed the client’s solution, identified technical limitations, and explored integrations. Our experts joined as augmented team members to enhance the marketplace. Suggestions included:

– A new design and optimal platform improvements for scalability, 

– Inventory management, secure payments, and improved product listings. 

– Utilizing AWS for scalable infrastructure and implementing auto-scaling ensured efficient handling of varying workloads. 

– Cloud-based inventory management reduced out-of-stock instances, while secure payment enhancements improved order processing speed and security. 

– Detailed product listings aided informed decision-making for customers.

Phase #2: AI Discovery  

Client’s challenge: 

Challenges arose in building a large, highly trained consultant team to maintain exceptional customer service, necessitating a balance between quality and efficiency. The client aimed to minimize training costs and human effort while ensuring top-tier service.

Solution:

To address these challenges, we proposed to create a makeup simulator app tailored for AI in the beauty industry. This solution aimed to streamline processes, diminish manual labor, and consequently reduce training costs and workload. We initiated a comprehensive discovery phase tailored to meet the specific business needs of our clients.

Discovery Phase Results:

We suggested proceeding iteratively, gradually adding new functionality, analyzing every step’s results.  

1 iteration – Mobile app with face analysis

2 iteration – Recommendation system

3 iteration – AR fitting room

4 iteration – Chatbot

Phase #3: СV Module   

Aim: to develop an application with facial analysis functionality, providing information about the user’s skin condition based on a photo.

User flow:

– The user takes a selfie or uploads a photo from the gallery. The captured image is saved in a format suitable for subsequent processing.

– Image processing algorithms include facial keypoint detection and analysis of texture, colour, wrinkles, acne, pigmentation, and other characteristics.

– The user receives instant analysis results on the application interface (analysis results, including highlighted key points and skin characteristics, are displayed to the user visually – as shown in the demonstrative image).

– A machine learning model, pretrained on diverse data, is applied for deeper analysis of the obtained data.

– The app generates a conclusion based on the analysis of computer vision data and the findings of the machine learning model. This enhances AI for beauty and cosmetics retail and AI in beauty industry engagement.

In summary, we obtain:

 1.Eye color

2.Age 

3.Skin type (normal, dry, combination, etc.)

4.Skin tone (fair, olive, etc.)

5.Wrinkles

6.Face shape

7.Redness

8.Breakouts (can be grouped, but they may vary)

9.Dark circles under the eyes

Phase #4 Recommendation System Module

Aim: Users receive personalized recommendations for skincare products and cosmetics based on the results of their facial analysis.

– The previous facial analysis phase results are integrated into the recommendation system.

– The user navigates to the recommendations section of the application. They may be prompted to input additional preferences, enhancing the AI for beauty and cosmetics retail experience.

– The recommendation engine processes the data, taking into account the skin analysis findings and the user’s selected preferences (makeup style, preferences, event type, etc.).

– Recommendations are matched with the product database. The database stores product characteristics and current prices.

– The generated list of skincare and cosmetic recommendations is displayed on the application interface.

– The user can easily add desired products to their cart or wish list directly from the recommendation interface.

Phase #5: AR module: online fitting room  

Aim: Facilitate trying on recommended products after receiving personalized recommendations.

Online “fitting room” for cosmetics revolutionizes traditional shopping by allowing virtual try-on sessions. The user-friendly app interface offers exploration of various makeup categories like lipsticks, eyeshadows, foundations, etc.

How it works:

– Users open the iOS/Android app to try on makeup.

– Experiment with vibrant color combinations.

– Capture photos or record videos showcasing different looks.

– Edit and customize within the app.

– Save images/videos for future reference or social sharing.

Main features:

Virtual Makeup Try-On: Experiment with different shades and styles.

Inventory and Store Locator: Check product availability nearby and get directions to retail locations.

Phaze #6: Chatbot module

Aim: To create a personalized AI cosmetic consultant chatbot replying to FAQs. The module serves as a recommendation system and does not suggest any medical diagnoses.

Business needs:

– Improve Customer Engagement: The virtual makeover app with an AI chatbot enhances customer engagement through instant, personalized assistance and recommendations.

– Suggest 24/7 service availability: Addressing inquiries around the clock ensures we capture potential sales and support opportunities.

– Boost personalization: Tailoring product recommendations based on individual preferences and purchase history enhances customer satisfaction.

– Efficient Support: Streamlining customer support processes frees up time for our team to focus on complex issues.

– Support upselling and cross-selling: Intelligent suggestions for complementary products increase upsell and cross-sell opportunities for AI for beauty and cosmetics retail.

– Provide data insights: Gathering valuable customer behavior data helps refine marketing and inventory strategies.

– Gain a competitive edge: Offering a chatbot sets us apart in the e-commerce space, meeting growing customer expectations, and enhancing AI in beauty industry engagement.

Results:

Scalability: This chatbot module can easily scale to handle increasing customer interactions as the client’s brand grows.

Cost Savings: Automating routine tasks with chatbot reduces operational costs while maintaining quality customer service.

Our technology stack

• OpenCV
• TensorFlow
• AWS
• GPT
• ARKit

Key achievements delivered

Increased sales and revenue: By implementing personalized recommendations that drive cross-selling and upselling, our client anticipates achieving a sales growth of up to 10%, as relevant product suggestions lead to higher order values, optimizing for AI for beauty and cosmetics retail and AI in beauty industry.