Lola Ogundipe UX Portfolio

WORK

RESUME

PROJECT RELATE ONBOARDING

Improving usability to make a confusing beta

app intuitive and accessible.

Challenge

User abandonment and a lack of understanding of the app's product value were barriers of user engagement

Impact

Highlighted in the Accessibility portion of Google I/O, May ‘24

Solution

An onboarding sequence was implemented to lower churn and enhance user growth.

UX Methodologies

User Research

User Journey

Heuristic Evaluation

Wireframing

Mockups

Prototyping

Tools

Figma

Timeline

Oct 2023 to Aug 2023

View summary

About the app: Why do people use Project Relate?

People with atypical speech face many challenges:

Difficulty communicating with people and voice recognition devices

Having trouble being understood by others

Being dependent on caregivers to relay their messages

What is Project Relate?

Project Relate is an app backed by machine learning that allows users to communicate easily and independently with others while having access to Google Assistant.

Challenge

How might Project Relate improve usability and provide product value for their user?

Project Relate was an Engineer driven app that lacked UX insight and analysis.

Imagine having to record 500 voice samples but not understanding the benefit

User goals

See the app’s benefit

See the feature differentiation

Business goals

Grow user base

Retain existing user

Gaining clear understanding of speech workstream

Missing UX support led to limited user understanding. We realized users with really strong speech difficulties often have other challenges too.

Brainstorming user journeys for alignment

I led a brainstorming user journey workshop to unlock user needs among the impairment specific group. Outcomes aligned the team and direction.

Discover

Addressing usability needs and proposing design solutions

I completed a product audit, identified key improvement areas and proposed design solutions.

Research review

A thorough review of the SLP research revealed user feedback highlighting further issues. To gain a deeper understanding of these concerns, I collaborated closely with SLPs / UXRs.

Users were confused...

...and we were losing them.

100%

79%

20%

17%

Completed interest form

Invited to app

Started app

Recorded something

Recorded enough for

personalized model

Used their model

30-day active users

The chart provided is a helpful visual representation of the user drop-off data. It shows that the largest drop-off occurred between the "Started the app" and "Recorded something" stages, with a 27% decrease in users. This suggests that users were having difficulty either finding or using the recording feature. The next biggest drop-off occurred between the "Recorded something" and "Recorded enough to get a personalized ASR model" stages, with a 16% decrease in users. This suggests that users may have been having difficulty meeting the requirements for a personalized ASR model, or that they were not aware of the benefits of having one.

Let's take a look at the potential reasons for dropoff...

How might we address user pain points?

Explain product value from beginning

State feature benefits and differences

Provide onboarding for recording phrases

Re-educate on return of app

Solution

Enhance initial onboarding with feature education, highlighting benefits and differentiation. New tooltips and refresher upon receiving a personalized speech model will further solidify user understanding.

Feature Education

Onboarding

Re-teach

Feature education

App skips explanation and delivers confusion

Confusing auto-enrollment left users in the dark about valuable features and the personalization process. By clearly explaining features and personalization upfront, we can empower users and boost their understanding and engagement.

Previous Screens

Design iteration proposal

Feature education

Final delivery

Ditching auto-enroll confusion, we empower users with clear steps and engaging visuals, igniting excitement for their personalized speech journey. Simple process, showcased value - users confidently navigate the app, unlocking its full potential.

Feature Education

Onboarding

Re-teach

Onboarding

Shaping the onboarding experience

Unpacking user pain points during onboarding, I crafted a core product MVP with a step-by-step flow aligned to their mental model. Recognizing the need for user empowerment, I incorporated clear instructions and audio review, tailoring for cognitive users.

Onboarding

Enhancing usability and streamlining flow

Low-fi wireframes led to team discussion and refinement. Collaborating with a UX expert, I integrated research-based patterns and addressed user edge cases, streamlining the flow

for intuitive experience. Tooltip guidance and pagination simplified the sequence, reducing steps and enhancing clarity for diverse users.

Low-fi wireframes led to team discussion and refinement. Collaborating with a UX expert, I integrated research-based patterns and addressed user edge cases, streamlining the flow for intuitive experience. Tooltip guidance and pagination simplified the sequence, reducing steps and enhancing clarity for diverse users.

Onboarding

Final delivery

Embracing user choice, I retained the edge case for flexible onboarding. Prioritizing readability, I removed the logo and placed a clear audio review point, further iterating on the audio buttons for easier user distinction. Collaboration with a UX writer ensured concise instructions, empowering users with a seamless and intuitive audio review experience.

Feature Education

Onboarding

Re-teach

Worth the wait: Bridging the feature gap and re-engaging users

Clear "why" and anticipated features based on training data bridged the model arrival gap. Engaging feature page unveiled new functionalities, while bite-sized explanations catered to cognitive users, maximizing value discovery.

Design iteration proposal

Re-teach

Final delivery

Seamless re-education bridges the training-to-model gap, empowering users to understand and utilize their personalized speech experience with confidence.