Boosting Product Recommendations: Simplifying the Process for Wellness Experts at Wrkout
As the lead UX/UI designer at Wrkout, a startup aimed at improving health outcomes for wellness professionals and their clients, my mission was to enhance the Wrkout Store app. Our app facilitates wellness professionals in recommending health and fitness products to their clients, with professionals receiving cash rewards for client purchases. Over the course of a 3-week project, I was tasked with improving the number of recommendations shared through app.
UX/UI Designer
Product Manager, FE Dev
iOS / Android App
Figma
3 weeks
Role
Team
Platform
Tools
Duration
The Goal
Our goal was to boost the number of product recommendations sent through the platform. With Wrkout's revenue dependent on users purchasing recommended products, increasing these recommendations was crucial. We aimed for changes that were low effort to develop, allowing us to quickly gauge the success of the update.
Research & Analysis
To begin, we conducted user research to understand the current pain points and motivations of wellness professionals using the app. This involved:
User Interviews: Conducting interviews with a sample of wellness professionals to gather qualitative data on their experiences.
Surveys: Distributing surveys to a larger user base to quantify common issues and preferences.
User Personas and User Goals: Creating detailed user personas and defining user goals to better understand the needs and behaviors of our users when recommending products to clients.
From our research, we identified several key issues and insights:
Complex Navigation: Users found the current navigation structure cumbersome, making it difficult to quickly find and recommend products.
Overly Complex Recommendation Flow: The MVP version of the recommendation flow was too complex.
Users were not engaging with features within the recommendation flow.
Users were not sharing recommendations via emails, which required the user to create and manage client profiles.
Some users found the recommendation message to be redundant for use cases when they were sending a recommendation to a client in the moment.
User Personas & Goals
Creating user personas and defining user goals helped us to understand the diverse needs of our users. This process included:
Persona Development: Based on our interviews and survey data, we developed personas representing different types of wellness professionals using the app. Each persona included information on their background, motivations, pain points, and typical behaviors.
User Goals: Along with personas, we outlined specific goals related to recommending products that we could refer back to during the design phase.
As a user, I want to quickly gather products to recommend to my clients
As a user, I want to provide value to my clients by providing meaningful and valuable product recommendations.
Design Solutions
Drawing from insights garnered during the research phase, we seamlessly integrated mapping user journeys and wireframing into our design process. By aligning the user journey mapping with wireframing sessions, we ensured that the identified pain points and user needs directly informed our design concepts. This approach allowed us to swiftly iterate on various design solutions, focusing on addressing user challenges and enhancing the overall user experience.
Based on finding from the wire framing process, the following design solutions were proposed to address user needs:
Streamlined Navigation: Simplified the app's navigation by introducing a more intuitive layout with clear categories and a prominent 'Recommend' button on the main screen.
Simplified Recommendation Flow: Redesigned the recommendation process to be more straightforward and user-friendly.
Enabled quick recommendations without the need to create detailed client profiles.
Simplified the messaging system to allow instant recommendations without redundant steps.
This holistic approach to design ensured that our solutions were rooted in user insights and tailored to meet the needs of our target audience, ultimately leading to a more seamless and engaging user experience.
Results & Reflections
The final updates to the Home Screen and recommendation flow received approval from the product team and key stakeholders. I collaborated closely with the development team to create developer-ready versions of the mocks, ensuring seamless implementation of design decisions. Following a successful launch, the update was rolled out to all users. The success of this initiative was measured by tracking the number of recommendations shared over a period, which showed a small increase.
Reflecting on this update, there are a few limitations I would approach differently in the future. At the time, due to resource constraints as a startup, we unfortunately lacked the finer analytics to track click-through rates on the home page and recommendation flows. Our plan was to collect more data in these areas to further fine-tune our improvements. While I relied largely on qualitative user feedback to inform my design decisions, time constraints prevented thorough user testing before development. Given more time, I would have tested the home page for ‘first click’ tendencies to gauge new users' interest in discovering new brands. Additionally, I would have tested the proposed recommendation flow for ‘task success rate’, ‘user error rate’, and ‘time on task’ to gain insight into any unforeseen shortcomings with the flow.
Check out the figma file
Have a look at the final mock ups for this project in Figma.
