The Spending behaviour of credit card user’s has been changed dynamically over the past few years where in the user’s attracted to offers the bank’s provide are something that the user can't deny.
The credit cards also have a sway over the people as they have a tendency to to increase their expenses by using credit cards over debit cards or other modes of payments. There is also a relationship that has been found between credit card ownership and usage behaviour, where the former has a significant influence on the latter and vice versa.
A group of 80 people from age 21-55 were interviewed and their spending patterns were analysed . They were grouped into personas and each persona was analysed deeply to tap into their emotional state.
To synthesise all the information I had gathered from the user interviews, I wrote my findings on sticky notes and created an empathy map. By identifying common patterns across my findings, I was able to uncover key insights which helped me understand who the users are and what they truly need.
Mapping their expenditure, spending behaviour, and their ideal personality based on interview data
Finding patterns in the users and grouping them to understand their
spending behaviour
Brainstorming and ideating how these spending behaviour maps to the users’ personalities
This phase is where the data gathered in the research and discovery phase is segmented , user persona is deduced from affinity and cognitive maps, user journey is traced and RCA - Root cause analysis is drawn out.
A mental model of the user’s was devised to understand their spending patterns. Decoding information about the users and attributes of phenomena in their everyday environment in a spatial pattern. This allows us to get a stronger insight into their mind and trigger points that make them spend.
From the personas, we wanted to derive the root causes for different problems which we can use to design the solution around
The journey map aims at recreating the user’s footsteps while using his credit card for any purchase, capture his emotions , pain points , challenges and places where there needs to be an intervention to help the user control his impulse buying.
The user’s idea of credit card being a go to solution for money and with trigger points of offers , credit scores , his impulsive nature towards over spending has increased.
The user here mostly uses his credit card in e-commerce buying online and has an impulse tp use his credit card practically everywhere he goes because he believes credit cards lets him afford everything without breaking a sweat.
-The main design focus is the application / product shouldn’t be a just a credit card manager but an advisor helping and guiding them to understand their spending nature.
-Understand their trigger points and nudge them in the right direction.
-Make them understand their own spending behaviour.
-The product should focus on how to save rather than how not to spend.This will help users not only change their spending nature but involve them in helping change their spending behaviour.
Almost every credit card user experiences a spike in their stress levels when they make impulsive payment using their credit card. In research it has been associated with the fact that its because of the feeling of borrowed money and a compulsion to return it back.
The credit card is equipped with a stress meter and a sensor matte (beneath the card) which records the stress levels of the users when he pulls the card out of his wallet itself. Once the stress is recorded the results will be shown in the place allocated. The card is bluetooth enabled which helps the card to get connected to the application provided.
The application helps the user to sync all his credit cards, debit cards, and savings accounts to his profile once created. This helps in making user immediately get aware of his mental status during the time of payment and make an informed decision when using his credit card.
After the conceptual model, we derived all features to be applied and laid it on Eisenhower matrix to determine the hierarchy of the app's features and placements.
After careful analysis of Eisenhower matrix Information Architecture and Low fidelity mock ups were done which were improvised to high fidelity prototypes.
Using my understanding of the user, our goals, the architecture, and the user’s interaction with the app, I worked on making informed decisions on how to design Curb's screens by sketching low-fidelity wireframes.
After analysing the mock screens and testing with users using card sort method and heat maps, few conclusions were derived.
The user wants more privacy and doesn’t want anyone to know how much he spends / saves.
Most used feature was the to check their stress levels as they too believe spending using credit card gives more anxiety.
But that also too more time for the user to make each transaction which became a pain point also.
With respect to further studies and usability testing there is more room for insights and development and always upheld to learning and understanding.
