Cleo / Goal creation

Streamlining Savings Goals with data-backed insights

Company

Cleo

Year

2024

Project Type

Optimization

Scope of Work

Research, Data, UX, UI

Timeframe

3 Weeks

Platform

iOS, Android

Cleo is an AI assistant designed to change its users' relationship with money. With a simple chat, Cleo can automate your money life and remove the stress of decision making with data-driven and deeply personal insights based on your specific needs and financial history to help users in ways their banks struggle to.

Executive summary

Context

Our initial Savings MVP launched in December 2023. We established a power user group to maintain an effective research loop with end users, and we closely monitored data to find learnings and optimization opportunities to drive the product forward. Cleo's Savings USP was a goal-based Savings approach, keeping users engaged in their journey to save towards something that is important to them, and keeping their goal top of mind.

Problem

We learned that our original goal creation flow was very user-driven with an overwhelming amount of options to choose from. We gave users free rein over the type of goal, amount, and timeline they can set, resulting in users setting unachievable goals. Our data showed that only 10% of users were on track to reach their Savings goals.

How might we empower users to set realistic, achievable savings goals?

Objectives

Update the flow with to ensure more successful goal setting

Increase percentage of users on track to meet their goal

Outcomes

65%

of goals created are achievable, up from 10%

22%

uplift in goals created with new flow

Challenge

In the initial flow, Cleo Savings users were given complete freedom to set their own savings goals, including the target amount and timeline. While this flexibility seemed empowering, it often led to unrealistic goals that users struggled to achieve. This misalignment not only discouraged users but also contributed to retention challenges for the business.

The core value proposition of Cleo Savings is to help users get started with their savings journey and build sustainable savings habits through automation. However, when users set goals that are unachievable from the start, the effectiveness of our tool is undermined.

Data

From our research into forecasting a user’s ability to hit their goals, we found that 90% of goals set are not realistic, with the median user having to save $90 a week in order to reach their goal.

In order to come up with an improved flow, I've asked for support from the Data Analyst on my team, specifically a deep dive into the goal setting to understand how users are interacting with this part of the flow.

TL;DR

Users are not interested in setting goals for more than 1 year, irrespective of whether that goal is achievable or not

An achievable goal is generally between 3 months and 1 year in length

80% of achievable goals are for $1,000 or less, which is generally less than 1 month of a user’s income

There is less of a correlation between higher incomes and the achievability of goals than we expected

Deep dive

Users don’t set longer term goals

The distributions for both goal hitters and goal missers are broadly similar - the percentage of users that set goals for longer than a year is in the low single digits

A realistic savings goal is a maximum of 1x your monthly income
‍
79% of users who are forecast to hit their goal have a goal amount less than one month’s earnings. We see quite a different curve for user’s that are forecast to miss their goal amounts. Whilst 33% of these users have set a goal at less than 1x their monthly income, two thirds of users forecast to miss their goal have set an amount multiple times higher than their monthly income.

No achievable goal is more than $5k
‍
80% of achievable goals are set at $1,000 or less, with the maximum amount being set at $5,000.

Achievable goals are generally between 3 months and a year long
‍
A lot of users who are setting unachievable goals are trying to save too much, too soon, achievable goals are in the 3-12 month range.

It isn’t just a case of users that earn more money are more likely to hit their goals
‍
It appears that whilst there may be a slight preference towards higher income
users being able to hit their goals, there isn’t as stark a difference in the income
profiles between those that set achievable goals and those that don’t.

Ideation

In collaboration with my PM and Data Analyst, we came up with three key focus areas for improving the user flow. Guided by our data and informed by Hick’s Law, which highlights that an increase in options can lead to decision fatigue, we decided to streamline the flow. Our approach focuses on reducing choice overload and providing clearer guidance.

1. Provide fewer options for goal creation

2. Suggest a timeframe for the goal

3. Suggest a target amount for the goal

To make an informed decision for the Goal Selection screen, I turned to the available data we had from our initial flow to identify the most frequently chosen options among the 10 shown to users. This allowed me to streamline the choices, ensuring we maintain alignment with user needs while simplifying the experience.

I took the general game plan and created some rough wireframes, focusing on UI variations to display the reduced amount of 4 choices.

Convergence

I presented my initial sketches to the team, and together we refined them down to a single concept. Our decision was guided by factors such as estimated tech effort, alignment with existing design system components, and copy requirements. The wireframe we landed on allowed us to use existing design system components while maintaining focus on the choices without additional overpowering elements on the screen.

Prototype

Collaborating with a content writer, we drafted four simplified choices to move forward with and incorporate those into the Goal Selection designs.

For the second part of the goal creation flow, the Goal Setting, I retained the existing layout and components, leveraging different states of the input fields to pre-populate time and amount data as a quick win solution.

The long-term vision for this flow is to enable dynamic, personalized goal setting driven by a user's transactional data; however in the spirit of keeping the experiment lean, we defaulted all user goals to $250 over a 12-week period, translating to a target savings of around $20 per week.

Test plan

Given the tight timelines and minimal engineering effort, as confirmed by my Engineering Lead, I chose to forgo user testing and instead proposed an A/B test in production. We ran a split test with a control group and a test group to evaluate the new flow.

Results

After two weeks, we've seen significant improvements in the area we wanted to address, namely the amount of achievable goals created. We have also seen improvement in the overall amount of goal being set thanks to a much lighter goal selection and creation process.

As a result, we promoted the test and set the new experience live to 100% of users.

65%

of achievable Goals created

22%

Uplift in Goals created

Next steps

I continued to explore the goal creation flow further. Due to a shift in priorities, these designs as well as making the goal setting dynamic didn't make it into production.

Exploration: Customizing a goal