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Conversation Design & Mobile UI for Female Wellbeing App Chatbot

Our customer - one of the world’s leading providers of women’s health apps - addressed R-Style Lab with a non-trivial request: contribute with our UI and mobile skills to the development of its Python-based platform providing end users with personalized menstrual cycle patterns and health insights. R-Style Lab team worked on the chatbot for iOS and Android that would rely on the client’s custom written neural network to communicate with users, collect necessary analytics and provide them with personal health recommendations.

Our customer - one of the world’s leading providers of women’s health apps - addressed R-Style Lab with a non-trivial request: contribute with our UI and mobile skills to the development of its Python-based platform providing end users with personalized menstrual cycle patterns and health insights. R-Style Lab team worked on the chatbot for iOS and Android that would rely on the client’s custom written neural network to communicate with users, collect necessary analytics and provide them with personal health recommendations.
Technologies & tools
UIKit, CoreAnimation (iOS); SupportFragmentManager, ObjectAnimator (Android)
Project team
2 iOS developers, 1 Android developer, 1 UI designer

Solution

The data-driven application uses a custom Python-based neural network which permits to analyze massive inputs of data, collected by the implemented chatbot, and make scientifically accurate predictions.

Collecting the necessary data was a challenging task, and the customer wanted R-Style Lab to develop sleek, top-notch UI design for a smooth user-chatbot dialog flow. For this we developed conversational interfaces so that a user would describe her state, indicate symptoms and health problems at each stage:

  • Once registered, a user logs her current mood, physical activity, and symptoms like acne, cramping or fatigue with the provided icons.
  • The app processes the supplied data using its machine learning algorithms and comes up with an individual menstrual cycle pattern as well as a personalized flow of tips and health insights.
  • If the user doesn’t feel well – for example, she’s indicating abdominal pain – the smart assistant asks her questions and provides different tools to identify its cause: close-ended and multiple choice questions, questions based on identifying a hurting area on the clickable picture, etc.
  • With the received data, the bot analyzes all the data collected after the user’s registration, suggests the diagnosis ("It looks like indigestion") and comes up with health advice ("Take activated charcoal").

To make the data collection process more engaging and simple for the user, the chat is provided with animations and eye-pleasing pictures and icons. For completing the task, R-Style Lab development team used native frameworks for each platform:

  • For iOS: UIKit for implementing layout elements like buttons, tables, and tests, and CoreAnimation for providing the app with drawings and animations;
  • For Android: SupportFragmentManager for developing intuitive navigation in the app, and ObjectAnimator for executing animations.

The clear-cut and user-friendly UI part of the app has contributed to its success. The app has been successfully launched and featured by App Store among other health-related solutions, topping the category on the US and European markets.

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