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Mentor Buddies

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BACKGROUND 

Design Buddies is an inclusive Discord community of more than 50,000 designers, their mission is to support those who are new to the field of UX Design by providing virtual spaces, chats, and events to anyone who wants to join. They have discovered a growing demand from members who have specific questions for experts within their specific design field- This sparked the creation of Mentor Buddies. 

Mentor Buddies is a mobile app where members can find and match with a design expert within various fields to chat with privately, in exchange for a small donation to the charity the mentor has chosen.

PROBLEM

After a privately released beta test, hardly any users made it to sign up for their first mentorship session.

CHALLENGE

Improve Mentor Buddy's onboarding experience to increase conversion 

Learning about more Mentor Buddies through a Stakeholder Interview 

I interviewed the founder of Mentor Buddies Grace Ling to get a better understanding of what challenges the application was facing. This interview helped me learn what Mentor Buddy's Business Goals were, what was currently working in the application, and what wasn't working.

MAIN TAKEAWAYS

  • Larger distributors generally display new releases on the home page.​

  • Smaller labels and shops all display an "about us" section.

  • Larger distributors include sample audio clips.

  • Large/Impactful Imagery of the record 

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Discovering Patterns through Data Analytics

Analytics from the beta test were another tool that we had to help identify trends and patterns from users and to help us determine which specific pages within the application needed the most help.

High Drop off at "Create a Profile" page

This screen has a highest drop off rate (66%) within the app and it's very early in the onboarding process (second screen).lowest completion rate at 34%. 

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High drop off & high amount of time spent on Mentor List page

This page had the highest average amount of time spent (about 6 minutes) had a drop-off rate of 66%, and there were very few clicks on the search bar as documented with the heat map.

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Highest drop of rate at Mentor Profile

There is the highest drop-off rate out of all screens at 81%, along with a high average time on the page. the majority of clicks were centered around the mentors' name rather than the CTA button to start a mentor chat.

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Discovering specific pain points through user testing

Analytics from the Beta Test helped me Identify what some of the points of friction within the application could be- they still didn’t me the WHY of why these drop-offs were happening. Synthesizing user's feedback from usability tests helped us get a better understanding of user-specific user pain points related to the high drop-off rates

By synthesizing responses from usability testing using the affinity map method- I was able to identify four major key insights. 

1. Users want more personalization in the
search function

Users voiced not feeling confident that they would be able to find a mentor that properly met their needs by

"I wish there was more personalization so I know I'm being matched properly."

2. Users want to explore the application before having to create a profile+ verify Identity 

multiple usability test subjects mentioned wanting to be able to see the mentors before having to create a profile- this helps to explain the high drop-off rate we noticed in the analytics review. 

“I wish I could explore the app before having to create a profile."

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3. Users are overwhelmed by the mentor
list page

Users voiced confusion on this page and wanted to ability to filter through the results.

"This is starting to feel overwhelming...did all of these mentors match with me?"

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4. Users don’t feel confident selecting a mentor based on their profile

Users felt like this page lacked enough information to allow them to make sure they were making the right decision 

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Creating design solutions Informed by data, user insights and business goals

Solution : Offer multiple options for shipping, and show the calculation of extra costs as early as possible (after the shipping address is entered). 

1. How might we create more personalization within the search function of the app?  

Solution : Offer more filtering options surrounding career speciality, type of company etc. Checking out some similar sites (such as ADP list and Designers guild group on facebook) Helped give me some ideas about what categories would resonate with users here. 

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How might we let the user engage with the app before creating a profile ? 

Solution: Change the flow so that the sign-up and verification come after the user has made it to the sign-up for their first mentorship chat- this will allow them to see the value in the app, and we know that they are already invested in speaking with a mentor so they will be more likely to want to create a profile. 

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How might we provide enough information on the search page to make sure the user can pick the right mentor for them? 

Solution: Allow users to filter through the results using specific filtering criteria. The most valuable features will be shown on the page with the option to click into "more" for more specific filtering options. I checked out the UI on other mobile apps with with filtered content feeds (ClassPass,Airbnb, Yelp, Zillow) to help notice consistent design patterns and inspire my design 

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How might we provide enough information on the Mentor Detail page that the user can feel confident in their selection? 

Solution: Give social information, additional specialties, and a section that allows for users to leave feedback about mentors so that they can have more knowledge and trust in picking the right mentor for them. 

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Measuring the impact of the redesign + Next Steps

To measure the impact of the design changes based on the feedback of the beta test, Mentor Buddies will release a public beta test and measure the following: 

 

  • % Conversion rate - Users who completed a session

  • Average click-through rate of “see results” CTA, per user

  • Average click-through rate on mentor cards, per use

  • Average time on page - decrease % MoM

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