Mateus Peixoto

Nubank
personal loans

Transparency drives better decisions

Role
User research
Product design
Year
2019

Nubank's personal loan is one of the projects I'm most proud of. In this 10-month project I was responsible for product design and UX research (we didn't have a UX researcher at the time).

It was a quote-unquote “textbook design project”. An example of the double-diamond in use.

That's why I structured this case-study in “discover & define” and “design & deliver”.

Discover & define

Market analysis

Day one of the project and noticed we didn't know much about personal loans. So we went after market reports. Thing is we found only one. It wasn’t much, but enough to have an idea of the market landscape.

These are some numbers that got us thinking:

13%
gets the one with the fastest approval

17%
don’t have time to do research

21%
look for instalments that fits their income

Surveys

We needed to check that info and what the report didn’t inform us or what was different between our customers and the general public. To make things faster and cheaper, we focused the research in our customer base.

Here are some interesting knowledge we gained:

The majority hire at their own bank

The majority research in 1.5 institutions

User Interviews

Now with the surveys responses and analysis, we wanted to understand the why's, so we invited 14 people that answered the survey to come to the office to talk to us.

Here are some of snippets of those conversations:

“I can’t understand why they treated me so bad? I went there to pay it.”

“I asked for 1000 reais and they charged me 1200.It’s an absurd! If I asked for 1000, I should pay 1000.”

Personas

To design the personas we used Cooper's methodology. This types of personas are based on heavily in user behaviour. Demographics are only used if it's really necessary.

To turn user behaviour into personas, we make a behaviour map, based on users answers. These are the steps:

  1. First we define behaviour rulers. Their have to be agnostic and clear. We found behaviors such as tech-saviness, account manager dependency, family communication, etc.
  2. based in their answers, we position every interviewee in the rulers.
  3. We identify clusters and patterns eg. interviewee 2, 5 and 9 share a close position repeatedly through the behaviours.

Two personas emerged in the mapping, one primary and a secondary. This means that the solution we design for the former also benefits the latter. Maybe not completely, but with some customisations we could have a great product for both types of user.

Research took us to three main attributes we believed our product should have. These attributes would guide throw all design phase. Well, not only the design phase, I think they turned to be the teams mission in a sense.

Design & deliver

Information architecture

Users can mainly do 3 things in a human-computer interaction: consume information, manipulate information and navigate throw information.

So here's what I did.

  • The green blocks represents what input we need from users.
  • Yellow blocks represents the information we need to provide to users so they can may make a decision.
  • White blocks are groups of information. It doesn't mean the need to be shown at the same time. It just represent the relationship.

Hiring flow

First we tried experiment 3 interfaces: A simulator, a chat bot and a list of proposals.

Simulator iteration 1.

Simulator won. Chat bot would be interesting for the emotional aspect, but the user interaction could feel to linear and lack the control we wanted people to have. For the list of proposals we found out that the amount of information was kind of overwhelming.

Simulator iteration 2.

After deciding for the simulator, we iterated a few times and went to user testing. The winner was the one with the stepper. The minimalist design made it the most responsive.

The simulator in details.

Vertically responsive.

The complete hiring flow.

The whole thing

I focused in the hiring part to avoid a long article, but here's a grasp of the whole product.

Title message changes to better inform users.

By grouping paid instalment, We give users a sense of completion.

Instalment anticipation flow. This part should have a case-study of its own.

Results


the benchmarking, hitting 10× during roll-outs

4+
was the NPS for customers that got to the simulator

“I want to thank you all for this dream made true. Yeah, we bought the land-lot! I just wanna say thank you, thank you, thank you.”