Hundreds of thousands of girls are looking for a suitable hair coloring recipe every day. You saw the desired shade in a photo, but how to repeat it in real life?

What problem does the app solve? Creates a unique and individual recipe from hair dyes of different brands. The app will take into account the original hair color and type, length, coloring history to select a strategy and a cocktail of dyes that will help achieve the color as in the uploaded image.

How does it work? The user uploads an image with the desired hair shade, and also takes detailed photos of their hair under different lighting. The user also takes a survey in the form of a test about whether they have had coloring done before and how long ago, what other salon procedures have been done on their hair, how often the user washes their hair, what type of hair they have, etc.

After that, the application analyzes the photos and answers and selects a mixture of dyes to obtain the desired shade. It is useful to create a filter in which the user could initially choose which brands of dyes to make a cocktail from. It is enough to simply write down the algorithm and compare the answers.

A mobile application for creating personalized hair coloring recipes based on the desired result, the current hair condition and the user's individual characteristics. It does not just select a color, but does it with an expert approach and deep personalization.

Main functional modules

Image Analysis Module

Hair color recognition in a photo. Base color determination. Tone and depth analysis. Compensation for different lighting. Color calibration for accurate determination.

User profiling system

Color history. Hair type. Length and thickness. Current color. Scalp sensitivity. Frequency of hair washing. Use of thermal tools. Previous chemical treatments.

Algorithm for selecting dyes

Database of dyes of different brands. Dye compatibility matrix. Mixing proportions calculator. Accounting for the original color. Calculation of the holding time. Prediction of the result.

User interface

Onboarding of new users. Profile with coloring history. Uploading and processing photos. Visualization of the result. Step-by-step instructions. Coloring timer. Notification system.

Additional functions

Chat with colorists. Video consultations. Knowledge base on coloring. FAQ on common problems. Educational materials.

Social functions

Reviews and ratings of recipes. Before/after photos. Exchange of experience. User forum. Success stories.

Commercial functions

Integration with online stores. Promo code system. Loyalty program. Referral program. Premium subscription.

Monetization model

Basic functionality (free). Profile creation. Basic photo analysis. 3 free recipes. Access to the knowledge base. View reviews.

Premium subscription

Unlimited recipes. Priority support. AI recommendations. AR color try-on. Salon integration. International localization. API for partners. Exclusive educational materials. Advanced analytics. No ads.

Additional sources of income.

Commission on sales of dyes. Brand advertising. Commission on consultations. Affiliate programs. Sale of training courses.

A few additions and implementation ideas that could make the application even more attractive.

The selection algorithm can take into account nuances such as cool and warm tones, taking into account the user's skin color and preferences. Add the ability to take into account eye color and possibly clothing style if the user is looking for a harmonious combination.

Using AI for analysis.

Apply AI to analyze uploaded images. This can help highlight shades in popular images and suggest realistic recipes. Use AI to analyze hair condition: density, texture and even damage.

Virtual mirror.

Add a feature where the user can "try on" a color in virtual reality. This will not only help users see the result in advance, but also make sure that the shade suits them.

Product selection. The app can provide recommendations for after-colour care for each hair type. Build in filters where users can select brands and formulations they prefer (e.g. ammonia-free, organic ingredients).

Mechanics of monetization

Free access to basic functions and a limited number of recipes. A paid subscription may include additional features such as more advanced analysis, saving coloring history, and a virtual mirror. The "Pro" subscription option, in which the user will have access to personalized advice from professional colorists.

Brand Partnerships: Include partnerships with color brands and hair care products, featuring them as featured products. Promote salons and colorist services if users choose to have their hair colored professionally.

One-time purchases. A one-time payment option for access to premium recipes for popular shades that are currently trending (for example, "Scandinavian blonde" or "blue ombre").

Advertising. Embed advertising for hair care products, shampoos, masks, and other products. Tech stack and technical details

Shade selection algorithm. Use computer vision to analyze the uploaded photo, highlight shades and coloring recommendations. Libraries such as OpenCV and neural network-based algorithms can be used for this. Apply Machine Learning to create recipes based on photos and surveys so that the result is as accurate as possible.

Questionnaire and analysis systems. Implement an interactive test to collect information about the user, which will include not only basic questions, but also the ability to take into account individual preferences, types of care and frequency of coloring.

Cross-platform: Create an app based on React Native or Flutter so that it is available on both Android and iOS.

Smart database. Store data on popular recipes, user preferences and accumulate statistics for further analysis.

Strengths.

Solves a real problem for a large audience. Multiple potential revenue streams. Scalability (add new brands, features, languages). Practical benefit for users. Potential for community building.

Possible difficulties:

Accuracy of color determination from a photo (lighting can greatly distort). Responsibility for the coloring result. The need to constantly update the dye base. Competition with beauty salons. Complexity of the selection algorithm taking into account all factors.

To minimize risks:

Add clear disclaimers of liability. Provide a function of preliminary consultation with a colorist. Implement a recipe rating system. Create detailed instructions on coloring techniques.

This idea can be in demand for many users, because it solves a pressing problem - it helps to achieve the desired color without errors. There are several virtual hair coloring applications on the market, but they mainly focus on showing how the color will look on the user, without creating a custom recipe.

The uniqueness and difference of this idea from existing solutions.

Custom recipes based on hair condition analysis. Unlike existing apps, the proposed idea involves creating a recipe taking into account the initial condition of the hair, its history and the individual needs of the user. Most apps are limited to visualizing the result, without giving real recommendations on the composition of the paint. Hue Maven is positioned as a “digital coloring expert” offering an accurate, scientific approach to selecting hair shades. The app is aimed at those who are looking for professional recommendations and want to receive a custom recipe that best suits their personal characteristics and preferences.

Universal selection of dyes from different brands. The application selects a mixture of dyes available on the market, giving recommendations on proportions and application technique to achieve the desired shade. The user can customize which brands he prefers, as well as specify parameters such as the absence of ammonia, natural components, etc. The application can offer recipes from different dyes, which allows the user to choose between brands and even combine them. Most existing applications, if they offer dyeing recommendations, are limited to products of one brand.

Hair condition and type test for more accurate selection. Hue Maven uses artificial intelligence to analyze the user's uploaded photos and their test answers. For example, the app can automatically detect the thickness and texture of the hair, the coloring condition and suggest suitable shades. It is also possible to analyze photos under different lighting for a more accurate selection of a recipe. The proposed app can take into account the structure, thickness, type and current color of the hair, which helps to create a more accurate recipe for achieving the desired shade. Apps on the market rarely go so deep in analysis.

Professional Colorist Consultations: Introducing paid consultations with professionals directly through the app adds additional value that most competitors lack. Built-in paid consultations with professional colorists give the user confidence that the recipe will work for them. Hue Maven can offer specialized consultations for those with complex coloring histories (such as bleached or severely damaged hair).

Hair care recommendations. In addition to the recipe, the app will recommend suitable aftercare products based on the user's hair type and selected shade. You can add a separate section with useful tips from colorists on hair care, color maintenance, and restoration.

Personalization and intelligent technologies. Using AI not only to select shades, but also to analyze the current condition of the hair in detail based on uploaded photos, allows for more individual recipes to be recommended, making the approach more scientific and precise. The idea can be enhanced by using algorithms that learn with each new user, offering more accurate recommendations over time.

Aesthetics and design. Hue Maven should look and feel like a premium product. The interface can be minimalist, with pastel colors reminiscent of a paint palette. Complex recipes and tips can be presented visually, making them easy to understand.

Expert Image and Trust. Maven's name suggests expertise, which helps build trust with users. The app positions itself not just as a visualization tool, but as a "hue expert" that people can turn to for advice. Hue Maven could include advice from renowned colorists or reference industry professionals to bolster its reputation.

Hue Maven is aimed at a wide audience. Women and men of all ages who want to change their hair color and maintain it in good condition. Colorists and stylists - the app can become a tool for them to select shades. Bloggers and influencers who often experiment with their appearance and can advertise the app to their audience.

Overall, the key difference and uniqueness of the idea is in deep personalization, support for different brands, hair analysis and the presence of a training and recommendation component, which puts it an order of magnitude higher than existing applications.

Author: Arina Yakuba ID #570DP27/10/2024

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