Index for Case study
Introduction
Problem Identification
Research Methodology
Key Insights
Solution Concept
Challenges
Implementation
Results
Key Learnings
Future Directions
Introduction
User churn can feel like a slow leak in an otherwise solid ship, especially when it comes to fintech, where keeping users engaged is critical to success. Our app was facing this exact challenge, with churn rates climbing to alarming levels, acquisition costs rising, and more than half of new users abandoning the app within just two weeks. If that wasn’t enough, our Net Promoter Score took a sharp nosedive in one quarter. It was clear we had a retention problem that couldn't be ignored. This article dives into how we used a comprehensive UX research approach to diagnose the problem, identify key insights, and develop a solution that reduced churn by more than half and revitalized user engagement.
Problem Identification
Our journey began with a realization: user churn the nightmare for every app rather any busniess is.
The key indicators that turned a chill Friday to a very hot day:
· A monthly churn rate starts to rise to 25%
· New user acquisition costs increasing at a rate of 40
· 62% of users can stop using the app within 14 days
· Net promoter score such scale has reduced from 42 to 28 in one quarter
A serious issue arising out of the use of the APP is with user retention.
The critical thinking in this process arose from cause and effect of these various data inputs to give a comprehensive view of the app’s health status.
Research Methodology
To tackle this problem, we went with a multi-faced research approach:
1. Quantitative Data Analysis: With 30000+ accounts we researched actual users’ behaviour patterns. It means that the wide coverage of users was aimed at attaining a large sample size for this we looked into broken journeys, abandon orders, specific screen drop off.
2. Qualitative User Interviews: Including both the churned and the active category, we gained 30 qualitative interviews. Hence, we decided on the following; we took users who had totally left the app which we are within the top 10% for the past quarter, we also took 15 users who were within the top 10% but had reduced their trade substantially.
3. Large-scale Surveys: We conducted surveys both to engaged and disengaged customers where we reached out to 3000 users. Using such an approach, it was possible to reach a large number of students and confirm the results of the interviews received at the initial stage.
4. Competitive Analysis: We examined 5 competitors. This step was necessary and essential given that it helped in determines if there are any gaps within our industry.
The justification for using this combined quantitative and qualitative approach was to be able to get the ‘what’ and the ‘why’ of user behavior in equal measure.
Key Insights and Analysis
Our research showed us several crucial insights:
1. Value Perception Issue: Thus, lack of perceived value got the highest response rate at 70%, which users identified the main cause as to why they churned. This was the most important observation: maybe the value proposition for our app was not clearly defined, or maybe, the value proposition was not very persuasive.
2. Feature Underutilization: Thirty percent of the users were using over two features out of the offered six features. This was an indication that perhaps what we presumed as adding competency was instead confusing users with numerous choices or that we were not properly educating them on the functionalities of our full feature set.
3. Engagement Correlation: More specifically, those who interacted with educational content were 4x more likely to stick around. This hinted the need for improvement on this area through sensitization and instruction or training of the patient.
4. Holistic Financial View: Abilities of long term users included at least one linked bank account signifying that a more detailed snapshot of the user’s financial situation was beneficial in retaining the users.
The breakthrough came when we synthesized these insights with a comment from a user interview: This app was not making me any better off in terms of my personal finance and there wasn’t a clear way of seeing how it was doing that. This led us to hypothesise that the users required a more finite, easily comprehensible indicated of how the app is helping their financial situation.
From here, we thought through a comprehensive theoretical measure called financial health. The thought process behind this solution was:
1. To overcome the value perception issue the organisation needs to offer customers a tangible value proposition.
2. Increase the feature engagement by including multiple aspects of financial health into the metric.
3. Incorporating learning material into the user’s personal finance process with no external distraction.
4. When it comes to financial health, you want to provide your customer with an overall picture to help keep them engaged with your business moving forward.
We paid special attention to whether the final set should be too narrow but deep or broader but not very detailed, trying to strive for the middle way which is fit for application.
The challenges we face during design and development includes:
Several challenges emerged during the design phase:
1. Metric Complexity: The challenge of boiling different types of financial elements down into one easily intelligible number score without misrepresenting the complexities of the financial world.
2. Actionability: Making sure that the end of the score wasn’t just educational and left users with knowledge of the ways in which they might be failing financially, but empowered the users with actionable steps towards bettering their statuses.
3. Personalization: Addressing massive differences in finances and people’s targets and objectives.
4. Engagement Balance: Applying game design features in the context of monetary activities but at the same time, not oversimplifying rather sensible topics.
Some of these issues forced stakeholders to fine-tune the applications and undertake user interface testing to get the right balance.
Implementation Strategy
We opted for a phased rollout:
1. Alpha testing of the product through the use of legitimate power users about 500.
2. Beta trial involving a large sample of users including 5000.
3. Full rollout with a re-engagement campaign
This helped in eliminating possibilities of exposing the feature to risk while enabling feedback to be taken at every level of the approach.
Results Analysis
Post-implementation, we observed:
· Churn rate with a reduction from 25% to 9%
· An up-to-date two months ROI for this interactive service increased by 150% in regards to user activity.
· Today, 70% of the users actively use 3 or more features on a regular basis
Hypothesis: These results validated our hypothesis that providing clear, actionable financial insights could significantly impact user retention and engagement.
Key Learnings
1. Value Visibility: When it comes to applying fintech, one has to understand the direct link between app utilization and the resultant financial value from it.
2. Education Integration: A company’s financial literacy content will enjoy remarkable increased traffic and user stick rate if the content is inserted in context.
3. Holistic Approach: Consumers prefer integrated solutions over feature-based concepts, in terms of financial standing.
4. Balanced Gamification: The authors also pointed out that there is still a problem in the way fintech gives fun to the financial management process.
Future Directions
This project opened up new avenues for research and development:
1. Discussing how the financial health kind of probabilistic index in order to be optimized to certain developmental phases or spare objectives.
2. Exploring the possibility of examining the effect of increasing the level of financial literacy on users’ continued engagement and their financial results.
3. Searching for best practices in the application of competency-based big data analytics to offer preventive financial management.
These directions stem from our core learning: implied in the concept of user retention in fintech is the realistic financial value that users can make with the help of the application.
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