Rewards UX discovery Plan
Discovery goals
This exercise to understand how users currently experience the Rewards feature in the Moniepoint personal app. We're looking to identify any pain points or areas for improvement in how users engage with Rewards.
Review of current data
We are already tracking key account data on Rewards performance. You can access the live dashboard here, where we monitor general activity and trends :.https://hera.teamapt.com/dashboard/rewards-hm-?p_Account Opened Period=["Post-Rewards Accounts"]
Customer space breakdown & selection criteria
We divided personal banking users into three groups based on how they interacted with the Rewards. The survey was sent to all customers in each of the following segments:
Segment A: Users who have activated Rewards, completed transactions, and successfully cashed out.
Segment B: Users who have activated Rewards, completed transactions, but haven’t cashed out.
Segment C: Users who opened accounts before September, have Rewards activated but haven’t done any transactions.
This segmentation allows us to collect insights from users at different stages of their Rewards journey.
Segment | Population | Segment Description | Rewards activated (can see rewards section in their app) | Done a transaction? | Cashed out the rewards? |
---|---|---|---|---|---|
Segment A | 276,225 | These users have cashed out rewards | Yes | Yes | Yes |
Segment B | 357,593 | These users have not cashed out rewards | Yes | Yes | No |
Segment C | 699,149 | These users have rewards activated but haven’t done a transaction. | Yes | No | No |
Methodology
To clearly understand how users feel about the Moniepoint Rewards program, we ran a structured survey targeting three groups of users (Segment A, B, and C).
Each group represents different levels of engagement with the Rewards feature, helping us cover the full range of user experiences.
Survey Design
We created the survey using Typeform, focusing on key areas like how easy it is to find the Rewards, how to use them, how fast users get their cashback, and their overall experience. The survey included both Yes/No and multiple-choice questions to measure user satisfaction, behavior, and the challenges they face.Survey Distribution
Using Customer[dot]io, we sent the survey to each group via email. The emails were tailored for each group to make sure they received questions specific to their experience. We also included clear calls-to-action (CTAs) to boost response rates.Data Collection
The survey was live from 13th to 16th September 2024. Our goal was to get at least 400 responses per segment for a solid analysis.Sample Size
Target sample size: 400 responses per segment.
Total personal banking users: 1,332,967.
Responses received:
Segment A: 725 respondents
Segment B: 630 respondents
Segment C: 1106 respondents
Data Analysis
After data collection, we started analyzing the responses. We are looking for patterns and key findings in areas like:Discoverability: Do users know about the Rewards, and how did they find out?
Ease of Use: Do users understand how to use Rewards and cash out?
Speed: Are users happy with how quickly they receive cashback?
Overall Experience: What do users like about the program, and what can we improve?
Survey Guide
Timeline and resources
Resources required:
Resource | Usage |
---|---|
Typeform | For creating and managing the survey |
Customer[dot]io | For sending out the survey via email |
Team members involved
Iwalola Sobowale
Lase Tawak
Ahmed Umar
Sequence of execution
Task | Timeline | Status |
---|---|---|
Data gathering | 13-16 September 2024 | Done |
Creation of artefacts | 17 September 2024 | Done |
Data analysis | 16-18 September 2024 | Done |
Review call and handoff | TBD | In Progress |
Expected outputs
Output | Status | Details |
---|---|---|
OST | We created an Opportunity Solutions Tree (OST), to map out the challenges users face with the Rewards program and potential solutions. | https://www.figma.com/board/HJTgi6xPqxpdA4ed5Ym0AW/Rewards-OST?node-id=0-1&t=vxHR6nPpzLst1VLJ-1 |
Survey analysis | We are currently analyzing the survey responses. |