Revitalizing the Referral Program
An in-depth user research project aimed at understanding the low conversion rates in a referral program and providing actionable insights for improvement.
💡 Motivation
After the launch of the Referral Program 2.0, we noticed that the overall conversion rate was only 0.3%, which was significantly lower than expected.
Research is necessary to grasp user engagement, encompassing motives for sharing, contexts in which sharing occurs, and methods of sharing. This information will be instrumental in guiding subsequent product enhancements.
✨ Research Scope
My role: UX research intern
Timeframe: 1 month (Jan-Feb 2022)
Tools: MS Excel, MS PowerPoint, Fogg Behavior Model
Methods: Log Analysis, Phone Interview, Thematic Analysis, Competitor Analysis
🌈 What I worked on
Designed Research Documents such as interview scripts.
Conducted analysis of both Qualitative and Quantitative data.
Created 9 Product Recommendations derived from the Fogg Behavior Model.
Generated Research Reports that offer support for operation-related decisions.
🧑🤝🧑 Who I worked with
Senior Researcher Rui Li, a member of our team, provided mentorship and assistance in crafting interview questions and formulating insights.
I shared and deliberated on my research findings with a team of 5 Operations specialists and the Product Manager.
📸 Impact
Enhanced the team's understanding of user engagement in the referral program, focusing on key factors such as sharing motives and user preferences.
Led to strategic changes in the design and content of the program, particularly in improving educational features to better meet user needs.
Resulted in a notable 20% increase in sharing rate, and provided strategic reports that guided operation strategies and design decisions.
Key Research Questions
How do users discover the referral program?
What is the users’ comprehension of the program?
What motivates users to participate or refrain from sharing in the program?
What are the typical sharing targets, contexts, and methods?
What are the critical operational steps in the sharing process?
What are possible recommendations for improving the program?
Research Methods
Research Groups
Elementary, junior and high school camp/experience class/regular price class users, mainly parents
Log Analysis
Overall Conversion Rate
The overall conversion rate is 0.78%, the proportion of users from exposure to sharing is too low, which leads to a low overall conversion rate.
Therefore, the subsequent improvement process can focus on the process of sharing from exposure to enhance the user sharing rate.
Conversion Rate by Division (Elementary, Middle, and High School)
Elementary school: highest exposure, highest sharing success rate, lowest invitation success rate; need to explore the motivation for sharing, analyze the reasons for the low invitation success rate
Middle School: lowest exposure, lowest sharing success rate, lowest conversion success rate; need to focus on improving exposure and sharing rate.
High school: low sharing success rate, highest invitation success rate, highest conversion success rate, highest overall conversion rate; need to focus on improving the sharing rate
Conversion Successful User Profile(Elementary, Middle, and High School)
From the perspective of the school section, the high school section has the highest percentage of successful users, reaching 89.31%.
New Users - School Division
898 old users successfully invited to 1080 new users, per capita successfully invited 1.2 new users
Among the 1080 new users, 988 new users were from the senior high school, accounting for 91.5%.
Number of new users in the senior high school: first year senior high school > third year senior high school > second year senior high school
From the results of the data analysis, improving the sharing rate is very important to improve the overall conversion rate, and the proportion of new users in high school is the largest, so we will focus on the sharing behavior of users in high school in the qualitative analysis.
User Interview
Through telephone interviews with 11 participants, I learned about the understanding of the high school users of the referral program, their motivations for participating in the program, as well as sorting out their suggestions for the program.
Interview Findings
Users generally had some impression of the "Invite for Gift" campaign.
Of the 9 users who were successfully invited, 1 had an impression after being prompted, 7 explicitly said they had an impression, and 1 explicitly said they had an impression and then took the initiative to mention the rules of the campaign to invite them to receive a discount.
Most users cannot recall the specific program rules.
Among the 9 users who were successfully invited, 1 was not clear about the rules at all, 6 remembered that there was a discount but didn't know how 1 learned from the teacher that they could get a book of math formulas for sharing 3 times, and 1 knew that they could get a cash rebate of 100RMB for enrolling in a class.
Most users learned about the program from their teachers.
Of the 9 users who were successfully invited, 7 learned about the offer from the teacher, 2 found the offer on their own, and 1 said they received both the SMS and the teacher's information.
Motivation for participation/non-participation
Motivations for participation:
the high quality of the course
significant benefits gained by the student
recognizing a need for the program in someone else's life
Reasons for non-participation:
lack of awareness about the program
unclear timing details
inappropriate timing of the program's promotion, such as right before a lesson, which users found unsuitable
The interviews revealed that users seek a clearer, more straightforward referral program with less promotional and more authentic communication. They often shared program details through personal interactions, emphasizing the need for a user-friendly approach.
This feedback suggests the importance of focusing on the program's real value and impact, rather than just rewards, to enhance user engagement and participation.
Strategic Recommendations
I read the Fogg Behavior Model and applied its concepts to analyze the referral program. I also learned from competitors' referral programs, forming some suggestions based on their designs. Drawing from these insights and the Fogg Behavior Model, I suggested several improvements, including simplifying the rewards system, increasing the program's visibility, and streamlining the sharing process, to enhance user engagement and the effectiveness of the program.
Personal Reflections
During my internship, I led this user research project, gaining hands-on experience in quantitative data analysis and qualitative interviews.
This project was my first foray into applying social science and psychology theories in UX research. The experience was invaluable, teaching me how to make informed recommendations for design and operations.
It reinforced the importance of empathetic UX research in product development, sharpening my analytical skills and deepening my grasp of user-centered design principles.