Binance NFT / Fan Token User Research
I successfully increased the user page duration by 23%
My Role
Lead UX Researcher
Full-time Employee
My Skills & Tool
Data Analysis, Survey, User Interview, User Flow, Persona, Figma, SQL
Meet My Team
Lida Lee, Product Manager
Sinem Suslu, Europe Marketing Specialist
Lorenzo Capone, Operation Specialist
Rex Tseng, UX Designer
Siu Seth, UI Designer
Duration
04/2022
(8 weeks)
Project Overview
Data & Qual Insights
Combined quantitative and qualitative research to uncover user motivations, behaviors, and pain points for actionable recommendations.
Unlocked 3 Fan Token User Segments
Led research identifying distinct user groups and their unique needs, driving tailored UX improvements.
Boosted User Engagement
Developed data-backed strategies to optimize the Fan Token experience, leading to increased active users and satisfaction.
Constraints
The study aimed to cover active users; due to the principles of humanity, 7 countries affected by the war were excluded.
1. User Coverage
Users from 7 countries were excluded from this survey because of Ukrainian-Russian War.
2. Dedicated Active Users who only used relevant utilities
Definition of the active user: user engaged in any of the 13 relevant utilities.
My Impact
I successfully increased the user page duration by 23%
I made one set of Fan Token user segmentations
This was the first user segmentation report that clearly classified the active users on user research in the Fan Token team
With the research outcome, our team could realize the composition of our active users and attract more users
Process
I led a 2-month study from research conception to strategy aiming to define user segmentation and increase the user page duration of a new product.
Background Insights
X % of users were newly registered users, and Y % were existing users with the DataWind analysis of the user’s behavior.
Survey Insights from the Pilot Survey
The study focused on two distinct groups: traders and sports fans. The survey analysis revealed two unique characteristics for each group
💡 The Fan Token team shifted their focus to developing strategies that targeted users with relevant features from my study outcome.
Define features
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Features of trader and fan
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Generate multiple questions for the following study
At first, our team's main objective was to turn a large portion of the traffic from the main platform into our own users. However, following a pilot survey, they came to the realization that their assumption was incorrect. As a result, the team shifted their focus to developing strategies that targeted users with relevant features from my study outcome.
Survey Insights from the First Survey
💡 I Increased survey response rate for "Pure Fans" by 37%: Persuaded F1 and European soccer teams to send the survey via their fans weekly email.
To increase the survey response rate for the “pure fans” using Fan Token, I persuaded the F1 and European soccer teams to send the survey via their ”fans weekly email” for me.
Key timings to inspect the replies are the first three hours, the first day, and the third day.
Outcome
💡 I successfully increased the user page duration by 23%
Interestingly, I found that creating campaigns focusing on user segmentation N1 and N2 could attract more potential users to stay on the Fan Token platform.
I made one set of Fan Token user segmentations, including [trader/fan], [not trader/fan], and [trader/not fan].
This was the first user segmentation report that clearly classified the active users on user research in the Fan Token team.
With the research outcome, our team could realize the composition of our active users and attract more users.
Takeaways
Natural users from the main platform can be large, but the user conversion rate to the sub-platform might not be as high as expected because the selling points were not the same for users even if some of them had a trader feature.