Problem statement

Bank of America's credit card sales department wanted to rethink its credit card sales strategy. It wanted to attract sales base on user's needs . Bank offers many types of credit cards to it customers and users were not sure which one suits better for them. Also users were not sure if they were prequalifed for a particular card offer. So bank wanted to proactively reach out to its user for their card needs. 

Research

I reviewed  the existing card comparison tool that was used to compare various features like intro APR, Bonus points, cash back offers etc. I also analyzed other sites that compare cards.

I did a small guerrilla testing with users who took part in another card related study. Users were asked asked few questions about how they select or apply for a card. Did they do any research ?  How do they usually search for cards? What did they like/dislike with bank's comparison tool ? Did some one guide them ? Did they take their expenses in to consideration ?

Here are some of the finding from the research:

• Most of the users were exploring cards on their own without any guidance
• Users were comparing or searching cards based on the offers and not on their previous spending data
• The card comparison tool did not work well on a mobile screen
• The bank was not utilizing online banking customer's spending trends to recommend a card
• Users had no idea if they were pre-qualified for a card offer.

 No guidance - Broader search - difficulty in browsing on mobile screens- Spending trends were not considered - no personalization - No pre-qualification

Design Process

Based on the research and feed back from the previous user testing conducted for credit card  we found that there was no personalized card offers. So I framed the product one liner to this:

"To create a more personalized card offers system that is easily accessible through all devices."  

Drawing board

I decided to explore the different types of process through which personalization can be achieved ie a process that will help the user to focus on a particular category but at the same time provide various card options.

I considered gamification where the user can answers their card needs in an interesting game format. This included question and answer session with interactive UI elements.  This approach would funnel the user to a desired card. But the drawback with the approach is there is no guidance and user would have to answer different set of questions to view different recommendations. So I tried to conceptualize an approach that would give guidance to the user but also would allow the user to freely explore their card options.  

User can be given guidance with their card selection using their spending pattern. For example if an user spends a certain amount on travel every month then that user would benefit more from a travel rewards than cash rewards card. Based on this I decided that leveraging online banking users spending data would fasten the process of card recommendation. So an existing bank user the flow became really shot.

Existing bank user flow

• Select a card category  
• Use online banking id to login
• User gets a recommendation

Now I moved on to recreate a the flow for a non bank user (new user)

New user flow

• Select a card category
• Enter expense patterns
• Enter basic information (personal details, SSN)
• User gets a recommendation

Sketching

In this phase I tried to come up with quick sketches for existing and new users. When i tried to create sketches for how user enter their expense patterns, the form stated getting complex. And I also observed that most users would not be aware of their spending patterns and it was also very subjective. I also got a similar feedback for design leadership. We feared that user might abandon the form because of the length and complexity. So I decided to remove the "Enter expense patterns" step.

New user flow

• Select a card category
• Enter expense patterns (Removed)
• Enter basic information (personal details, SSN)
• User gets a recommendation

A simple form that would work for all the devices and screen sizes were explored in the sketching stage. I also conceptualized how the recommended offers screen would look on various devices. A high-level sketch on what information needs to go on the card recommendation pages was also created.

Interaction Design

• I decided to keep the form as short as possible. 
• I designed a simple form that requires the user to input basic information like name, address and date of birth.
• Sensitive information like the last 4 digits of the SSN, date of birth were designed to be masked.
• I employed error validation and messaging standards.
• I decided to pre-selected card categories when user lands on the form based on their access points (eg-if the user is coming to this form from a cash back credit card page relevant category would be pre-selected)
• Based on the conceptual design, we created interactive wireframes for the card recommendation result screen.
• I created different tabs (offers/ advantages/ rates) to categorize useful information for the users.
• I also added "other cards you might be interested" section to provide an alternative for our recommendations

Access Points

• One of the major considerations for this product was to channel users from different hubs and platform in to card recommendation system.
•  I created multiple  access points through various channels like promotional emails, research pages, online ads/promo, mobile banking app and other marketing pages.

Visual Design

• The visual design exercise mainly focused on the card recommendations page.
• We designed the page to feature different card images and also highlight important rates and offers information.
• Brand guidelines and visual style guides were used do decide the look an feel of this page. 
• Mobile screen designs were designed to factor the small real estate. 
• Extensive access point visual designs were created to capture users attention.

User testing

• The overall screen designs were tested in the user testing phase and to specifically check if the card recommendation made sense to the users.
• In addition to the onscreen testing, users were given a survey to fill in  what they liked and dislike about the process.
• We mostly got positive response from the users. Most users liked the fact that they were pre-qualifed for a particular card. 

Result

• The product was launched with extensive marketing strategy in the online space.
• The result saw increased number of users applying for the credit card compared to the user using card comparison tool. 
• The conversion rate doubled because most of the users were applying for the card that they were pre-qualified.

"The conversion rate doubled and user's confidence for applying credit cards increased (pre-qualified)."