Data Led Growth | Multipl
OVERVIEW
Multipl is a fintech offering with its unique approach to integrating investments and consumer spending for the Indian market, which, despite a strong saving culture, struggles with personal finance.
Multipl operates by turning shoppers to savers and savers to investors.
What Multiple solves for
One, while the neo-banks and BNPL see aggressive adoption in India, there is discontentment in users with traditional credit solutions due to hidden free trap, debt accumulation risk in addition to the good-old much-hated high interest rates.
Two, since a significant portion of the Indian population remains underserved by traditional financial institutions, there is a pressing need for accessible financial services.
Multiple caters to the three parts of the economic equation — Consumption, Savings, and Investments while driving long-term customer behaviour of the younger generation (Millenials and Gen Z) towards saving/investing.
PROBLEM STATEMENT
Significant number of Multiple users are failing to complete their financial goals, thereby leading to a high churn rate.
For the sake of simplicity, we are isolating our solution and experimentation to focus solely on one primary cause of attrition, assuming that Multipl has a successful onboarding and first-time user experience (AHA! delivered).Therefore, we will concentrate on retaining users who have already joined the platform but are at risk of churning
Note: I'm in no way associated with Mulitipl. So, this is a hypothetical problem statement I've chosen to work on and donot have the means to it test out.
HYPOTHESIS
Users lose interest or become distracted, leading to a decline in their commitment to their financial goals. The new feature introduced on the app will improve retention among churn-prone users by increasing motivation and engagement.
Enter STREAKS - A feature that rewards users for consecutive time-periods of honouring their financial commitment towards the end-goal.
Core Functionality:
- Activity triggered rewards : Users earn points or badges for consecutive time-periods of meeting their financial goals (e.g., saving a certain amount, investing regularly). Offer rewards or incentives for achieving longer streaks, such as exclusive discounts or personalized financial advice.
- Visualization: Provide a clear and visually appealing representation of a user's streak, such as a progress bar or a streak counter and mile-stone based badges.
Social Proofing: (think fit-bit/apple watch)
- Share Streaks: Allow users to share their streaks with friends and family within the app.
- Friend Challenges: Enable users to challenge friends to streak competitions, adding an element of friendly rivalry.
- Leaderboards: Create leaderboards to showcase top performers and encourage competition amongst the user's friends and family on the app.
GOAL
Improve retention among churn-prone users. Decrease churn rate to 10% in 30 days.
SUCCESS METRICS
Improved monthly/weekly/daily active users (MAU/WAU/DAU)
Improved 7-day (because majority of the churn occurs within 9 days of app download), 14-day, 30-day, 60-day, 90-day user retention rate amongst cohorts of churn-prone users.
HEALTH METRICS
Goal Completion Rate - to track the percentage of users who successfully complete their financial goals upon treatment.
Repeat Purchase Rate - would help understand customer loyalty by tracking if customers come back to Multipl in order to set new financial goals once their initial goals are met.
Push Notification Engagement - to measure the open rate and click-through rate of push notifications related to streaks. This should help us understand the likability of the feature.
Transaction Volume - across the cohorts to understand changes in user behaviour
EXPERIMENTATION DESIGN
Purpose: Measure the impact of the streaks feature on user engagement and retention.
Null Hypothesis: the streaks feature has no effect on user engagement or retention.
Sampling:
Leverage churn prediction models to identify users with a high propensity to churn. Maybe, even combine churn prediction scores with other factors, such as engagement metrics, and demographics to filter out control group and treatment group.
Why? because targeting users who are already actively hitting their milestones would poison the experiment since such users are likely already highly engaged and motivated, making it difficult to isolate the true impact of the streaks feature. Gross misallocation of resources!
Behaviour and time-based Cohort Analysis: Group users into cohorts based on similar characteristics, type of financial goals, transaction frequency of saving/investment, magnitude of financial goal
Randomized Control Trial (RCT):
Within each cohort, randomly assign users to either the treatment group or the control group.
- Treatment group: Receives the streaks feature.
- Control group: Continues to receive the current experience.
EXPERIMENT RESULT & RELEASE DECISION
Check for
Statistical Significance
Analyze the post experiment data to determine if the treatment group has a statistically significant increase in MAU and retention rate compared to the control group.
Business Impact
Impact of the new feature on revenue and customer satisfaction to be evaluated.
LTD cumulative downloads in 4 years = 500,000
Current MAU = 100,000
Downloads per month ~400
Per Fintech Industry benchmarks of 73% of new users churn within 1 week
Churn-prone users per month = 0.73*400 ~290
Best case scenario - achieving a churn rate of 10% in 30 days
Therefore, Retained Users per month = 0.9*400 ~360
Revenue per transaction = X
Average Transaction per user = Y
Thus Potential Topline Growth opportunity per annum = 360 * X * Y * 12
If the streaks feature shows positive results, consider releasing it to a larger user base. If the results are inconclusive or negative, re-evaluate the hypothesis and experiment design.LEARNINGS
Key learnings from the experiment could be observable in the short-run such as
Uptick in goal completion due to the effectiveness of streaks in motivating high churn propensity users
BUT, (there is always a but!) it could also attract unintended consequences in the longer run.
- Constant competition amongst friends and family could prove to have high social costs and thereby demotivate the user altogether, offsetting the positive effects of the feature.
- Cohort-specific effects would be apparent at the end of this experiment since the different demographics may respond differently to the gamified nudge.
- We'd also get the opportunity to learn about the optimal frequency of rewards for varied range of goal difficulty.
NEXT STEPS
Based on the learnings, refine the streaks feature and conduct further experiments to optimize its impact.
Expand to other user segments, such as users who are simply struggling to meet their financial goals while continuing to engage with the platform or those who have recently joined the platform.
STAKEHOLDER MANAGEMENT
Key Stakeholders to be aligned with the with the experiment's objectives.
Over-communicate, always! Keep the decision makers in the loop with the results of the tests at apt frequency to enjoy their confidence in the process.
Manage expectations and address concerns throughout the process.
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