Hannah Kalma
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KiwiSaver Recommendation Engine

Helping New Zealanders make smarter retirement fund decisions

Role: UX/UI Designer|Timeline: 8 weeks|Tools: Figma, Maze, Hotjar|Team: 2 designers, 3 developers
KiwiSaver Recommendation Engine

Project Overview

What we set out to solve

The Challenge

KiwiSaver is New Zealand's voluntary retirement savings scheme with over 30 fund providers and 200+ fund options. Users were overwhelmed by choice, leading to decision paralysis. 67% of users abandoned the fund selection process before completion, and most defaulted to their provider's conservative fund regardless of their actual risk tolerance and retirement timeline.

The Solution

An intelligent recommendation engine that guides users through a personalized 5-step questionnaire, analyzing their risk profile, retirement goals, and financial situation to match them with the most suitable KiwiSaver fund. The solution includes clear fund comparisons, educational tooltips, and a streamlined sign-up flow.

Research & Discovery

Understanding the problem space

12 user interviews conducted with KiwiSaver members aged 25–55. Key findings:

Decision Paralysis

78% of participants felt overwhelmed by the number of fund options and couldn't differentiate between providers.

Knowledge Gap

Only 23% understood the relationship between risk level and potential returns over their investment timeline.

Default Bias

62% stayed with their default fund because switching felt too complex, even when it mismatched their goals.

Research artifacts

Design Process

From wireframes to final design

01

Information Architecture

Redesigned the fund comparison flow into 5 clear steps: Risk Profile → Goals → Timeline → Preferences → Results.

Information Architecture

02

Wireframing & Prototyping

Created low-fidelity wireframes, tested with 8 users, and iterated on the questionnaire flow based on usability feedback.

Wireframing & Prototyping

03

Visual Design & Testing

Applied the brand design system, conducted A/B tests on the results page layout, and refined based on user feedback.

Visual Design & Testing

Results

Measurable impact

+64%

completed sign-ups

-45%

drop-off rate

4.6/5

user satisfaction score

50K+

users served

"For the first time, I actually understood what fund was right for me. The recommendations felt personalized and trustworthy."

— User Research Participant