Designing for Behaviour Change
Background
A financial services client wanted to increase customer trust and loyalty by helping customers avoid bank charges caused by accidental overspend.
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Repeated charges were eroding confidence in the brand. The goal was not simply to notify customers of low balances, but to understand the behaviours driving overspend and design interventions that could realistically support change.
Approach
The client had generated multiple potential solution hypotheses.
To test early concepts efficiently, I created paper-based stimuli sketches that allowed participants to react to and critique potential interventions.
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The focus was behavioural: not what people said they intended to do, but how they actually managed money in practice.
Research Objectives
1.
To understand current attitudes and behaviours of customers who have previously incurred bank charges
2.
Evaluate which elements of the proposed solution aligned with existing behaviours and would effectively help users avoid charges.
User Groups
I designed and facilitated 15 x 60-minute in-depth interviews in a lab environment with two distinct user groups. Despite this difference in capability, both segments incurred charges.
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Low Ability
Have not been successful in making a sustained change in their financial behaviour in the past
Not confident in financial matters and quickly overwhelmed by too much detail
Less aware of and engaged in their financial situation
Use rudimentary tools to track spending, do not create detailed forecast budgets
Have been successful in making a sustained change in their financial behaviour in the past
More confident in financial matters and more engaged in detail
More aware of and engaged in their own financial situation
High Ability
Use more sophisticated tools to track spending, create detailed forecast budgets
I created a series of sketches based on the client's hypotheses, to evaluate which approach would best suit all users.
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Participants evaluated stimulus concepts including forecast balances, forecast payments and timely warning messages designed to intervene in these moments.
Current Behaviours
1.
Being habitually unaware of their spending and balance
2.
Failing to spot that expected income hadn't arrived
3.
Failing to forecast larger than expected payments
4.
Failing to include a regular payment in their forecast
5.
Failing to accurately forecast the dates of payments
6.
Losing track of spending while on holiday
Findings
Money Management Methods
Low ability participants tended to use more rudimentary methods to manage their finances:
1.
Focus on tracking current balance using tools like internet banking and mobile banking app
2.
These tools helped increased awareness of their current financial situation but were not effective in helping them avoid charges
3.
Did not use tools to create budgets or forecast future spending
4.
No correlation between frequency of logging in to Internet Banking and ability to avoid charges
5.
Failing to accurately forecast the dates of payments
High ability participants tended to use more sophisticated tools that helped them track and forecast spending:
1.
Used Internet Banking and Mobile Banking App to monitor balance on the move
2.
Kept lists of all typical income and outgoings, including regular cash expenses (e.g. weekly cleaner)
3.
Created spreadsheets to forecast their budget of spending for the coming month
4.
Created diary entries of all direct debits
5.
Kept a small buffer in account to cushion against overspend
However, even structured forecasting did not eliminate exposure to unexpected events such as delayed income or unusually high bills.
The behavioural gap was not purely about access to tools, it was about anticipation.
Reasons for Being Charged
Charges were frequently linked to forecasting errors rather than reckless spending.
1.
Salary or expected income not arriving on time
2.
Regular payments omitted from forecasts
3.
Bills higher than expected
4.
Direct debits landing before salary
5.
Overspending while on holiday due to reduced monitoring
6.
High Ability participants tended to respond with renewed vigilance
7.
Low Ability participants often experienced reduced confidence and loss of perceived control
Outcome
This research reframed the problem from “showing balances” to preventing predictable behavioural failures.
Instead of investing in broad budgeting tools, the client gained clear, evidence-based direction on where intervention would actually reduce charges.
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The key insights for the client included:
1.
Clear behavioural segmentation that explained why some customers repeatedly incurred charges while others recovered
2.
Evidence that balance visibility alone does not prevent overspend
3.
Strong validation for timely SMS warning messages as the most effective preventative intervention
4.
Clear prioritisation guidance, reducing investment risk in low-impact features
5.
Strategic direction for the next phase of development
The recommendation to prioritise timely, actionable SMS alerts gave the organisation a focused path forward: intervene at the moment of risk, in the channel customers perceive as urgent.
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By aligning product decisions with real behavioural triggers, the client was able to move forward with confidence, investing in interventions most likely to increase customer trust and reduce avoidable dissatisfaction.