Redesigning a complex loan calculating website was a very exciting challenge. I am going to discuss one interesting snippet of the redesign as a case study about how quantitative user research can guide UI design and dramatically increase user retention.
Bankmonitor is an online calculator helping users compare loan offers of different banks. Banks hate that it makes choosing the best offer so easy, and that it makes it impossible to win customers with sub-standard offers.
The loan calculator worked in the following way:
1) Users arrived from organic search to page1 where they could fill out a simple calculator form to get some initial results: top loan offers.
2) They arrived at the results page (page2). At the top of the results page there is a more advanced calculator in case the user wants to fine tune their search.
Discovering the hidden loop, where users are leaving. In Google Analytics’ User Flows we noticed that users were going back and forth between Page1 and Page2, and there was considerable user drop-off.
We did a couple of user tests to follow-up on the issue. It turned out that the calculator on Page2 looked so different from the calculator on Page1 that users simply thought it was something else, not a more advanced calculator. They didn’t take a second look. As a result, whenever they wanted to refine their search, they went back to Page1 and resubmitted it.
In the new design we merged Page1 and Page2. A simple calculator was readily available at the top and advanced features hidden under a link. Rather than two different calculators, the site now had a single calculator with extendable features.
Another challenge was to understand how individuals actually choose a loan when they need money for a new home.
The assumption was that the process of choosing the best mortgage offer was to:
1) look for the ideal house
2) realize that you don't have enough money to buy it
3) visit Bankmonitor.hu to find out which bank would loan you the missing amount for the best conditions.
Therefore Bankmonitor.hu asked for the amount of money the user needed and the duration of the loan - then calculated the best offers.
To get started, we did a couple of user interviews with people who have recently took out a loan. As it turned out the actual process of buying a house looks more like this:
You don't have a dream house in mind, but you want one as big and nice as you can afford.
How big and nice can you afford? That depends on how much banks are willing to lend you, which is dependent on a number of things, but most importantly on the size of the installments you can pay.
So you go to Bankmonitor.hu to calculate mortgages based on how large installments you can repay safely.
Once you know how large of a mortgage you can get, you go out and find the best house in that price range.
You find the real estate and agree on the purchase price.
Go to Bankmonitor.hu to compare mortgage offers for exactly the loan amount you need.
We came up with a simple calculator design that serves both use cases well.
To wrap up: assumptions are great to start with, and often assumptions are correct. But they are correct in a way that they are only part of the story. UX research can reveal the rest of the story, and provide a big advantage over your competitors.