B2C · Finance
Although the number of funds on the platform was growing, the investment funnel wasn't converting at the expected rate.The problem wasn't simply discovery.
Users were reaching the mutual fund experience, exploring their options, and interacting with filters but many weren't confident enough to make an investment decision.
What the data told us
I started by looking at funnel data and usage patterns to understand where users were struggling.Three patterns stood out
Popular funds received disproportionate attention
Filters were being used but weren't helping users decide
Users were scrolling rapidly
01.Funds appearing in the top section received significantly more investment activity than funds further down the page.
02. Users frequently interacted with filters and search, suggesting strong intent to find a relevant fund. However, this interaction wasn't consistently translating into selection or investment. Also, the placement for search was creating unnecessary clicks and scroll issue.
03. Users spent time scanning through multiple investment options rather than confidently progressing with one.This suggested that the problem wasn't a lack of choice.
For a better understanding, here is the screen with the list of mutual funds
Understanding the users
Research through surveys and user interviews helped uncover the reasons behind this behavior.
We found two broad user groups:
The informed investor : Already understands mutual funds and knows what they want to invest in.
The uncertain investor: Wants to invest but lacks confidence in choosing the right fund and needs more guidance before committing.
The second group was particularly important for conversion.
The unsurity gap
Lack of clear next steps
Users didn't always know what action to take after finding a fund.
Low awareness
Some users weren't familiar with which funds were appropriate for their investment goals.
Information overload
The experience presented a large amount of information, increasing cognitive load rather than building confidence.
Weak decision support
The existing experience relied heavily on users researching and interpreting information themselves.
Drop off rate reduced from 38% to 24%
Investment conversion rate increased from 6.8 to 9.4%
The process
The outcome
What more we did
To boost more conversion and help users to make easy decision, we added a basket curated upon different requirements
After multiple iterations, we decided to launch a lean version to track how customers engage with the monthly tracking feature. This approach allows us to gather insights with minimal friction and refine the experience based on real user behavior.