top of page
Financial proposals on Otto's app

Otto is a product for real estate agents. We bring together every single thing they need to do during their journey to sell a realty into a single product. Otto is currently focused on high-end realties. If you want to read more about how we built this app from scratch, you can check out the project here!


By the end of 2019, we had delivered the first major step on the real estate agent journey through the app. The real estate agent was able to look for and learn everything about a realty, and he was also able to share all of this information easily with his client. It was time to tackle the next point in his selling journey.

bottom otto.png

Once you and your client have found the perfect apartment, you need to send a financial proposal. Even though each real estate developer has their own way of doing this, most of them resort to building a very complex Excel spreadsheet where they will calculate several things in order to make a financial proposal. Our initial conversations with the real estate agents - especially the ones who were new to the field - showed us that most of them had no idea of what they were doing when they had to use this sheet. 

Actually, it was very common for them to simply pass the job to another more experienced real estate agent or manager once the conversation with the client arrived to the financial part - they simply could not do it. So, we were tasked with the really hard issue of trying to translate a very complex spreadsheet into a simple to use financial proposal builder that fit the size of a cellphone screen. You can check out here a simple example of what this sheet can look like:

The real estate agent needs to be able to see what is the price the real estate developer is asking for and how they want this price to be paid.
Then, he needs to be able to assemble the price and payment distribution of his client. This sounds simple but it's very complex, because there are many indicators that he needs to reach in order for the proposal to be accepted, and the way the client distributes his payment directly affects these indicators.
Since many real estate agents get a little "scared" with the math behind it, they don't even try to use it.
How to build this feature?
 User testing 
 UI Design 

We tackled this issue how we usually tackle new things in Otto: interviewing people to better understand the issue we are facing. Here are some of our findings:

Group 624.png
The average real estate agent doesn't have the required knowledge to use Excel at the level required for this function (and is not interested in learning it)
The clients usually require a copy of what they agreed on with the real estate agent on the financial proposal, but the Excel sheet usually has too much confidential information to be shared with a client.
There are regional differences that affect how a real estate agent makes a financial proposal. We had to go to São Paulo to test out some solutions to understand if it was universal or not.
Group 623.png
The real estate agent needs to see many different kinds of information to make a good financial proposal, but some are more important than others.

The whole process of designing this feature took around 6 months - between interviews, tests, iterations, deliveries and having users actually using it, we discovered many new things and new ways to do financial proposals.

One of our challenges is that each real estate developer has its own characteristics, so we really needed to make a "one size fits all" solution.  They look at different numbers and have different indicators of when a financial proposal is good enough. Since Otto is not a white label application, it was really important that we could develop a feature that could grow and be sold to many clients (the real estate developers) without any customization.


The process to design this feature during these months was very similar to the one we worked on during the "discovery" step of the user's journey:

Interviews: we talked with real estate agents to understand what were their major pain points. It was really important to talk with real estate agents that had very different levels of experience with Excel, because this helped us understand what was most terrifying for the less experienced ones and what were the most useful tricks for the most experienced ones. We also had to go to São Paulo because we noticed that there was a lot of regional differences in the process;

Wireframing and prototyping: This particular solution required real time calculations, so we actually had to develop a prototype. Since our user usually had a hard time with low fidelity prototypes, we ended up drawing really high fidelity screens and hired a developer to actually make it work on the front end. It was a really useful solution, it helped out a lot on the testing and we used this prototype to better explain it to the developers who actually made the final solution.

User testing: with the support of the product team, we tested this feature extensively;

Iteration: Most of the times, the user testing would result in some changes to our initial idea. We would usually share all of our findings with the team and adjust what was perceived as important on the prototype. If required, we would test again.

High fidelity design: The UI Design of this particular feature was performed by a duo, me and the UI designer were 100% involved with this. We took some time to get to the ideal solution, so we needed to be fast in this last step.

Asset delivery: All of our app was designed on Figma, and we used this tool for the asset delivery. We would also hold meetings to explain what were the expected behaviors and how we had thought out the feature as a whole before delivering anything. For this particular feature, I also created documentation on the rules, because it is very complex.

Development and delivery: Once the feature was developed, we selected a small group of real estate agents to try it out.

Group 522.png
Group 523.png

Running the user tests in São Paulo with our developed high fidelity prototype. It was my first time having the opportunity to test out a feature with this level of fidelity and it worked out really well for what we needed to achieve.

Group 521.png

These are some early stage screens we made for the high fidelity prototypes. We kept the major idea we designed here, of allowing the real estate agent to build the proposal payment through payment, but most of the things you see here were left behind.

The B2B tool
 User testing 
 Ui Design 

One of the aspects that made this solution take so long in terms of delivery is that we also required us to build a back office from scratch, and so far we had none of that.  We knew the time would come where we would need to build a B2B tool for the real estate developers to manage all the information and relationship with the real estate agent, and we decided to tackle it at this point.


Once the real estate agent finishes a financial proposal he needs to send it for analysis - so we needed to build this analysis tool. This required us to make a series of interviews with the people who were responsible for analysing proposals in the real estate development companies.

We held several interviews, watched them doing the process of analysis, tested and iterated prototypes and even read several previously made analyses to understand how much time it usually takes in between a financial proposal being sent for analysis and its actual approval. We had to create all the formal steps of one analysis to inform both the real estate agent and the analyst, and also understand all of the information that the analyst needed to see to be able to approve a proposal.


It's important to note that this process was interrupted by the Covid pandemic, which not only impacted the real estate market in several ways, but also impacted how we did our discovery process. From spending a good amount of our time inside the real estate companies to making online interviews and user testing, there was some adapting we needed to make in order to succeed. We have been working mostly like this since that.

Screen Shot 2021-05-25 at 17.04.13.png

These are some very early stages screens we tested out for our B2B solution. Our product has many new and better features nowadays.

Group 432.png

The final product back then looked like this. Today, our B2B tool is huge and has several more analysis and management features, but it began really focused on solving just the financial proposal analysis for the real estate developer.

How did we launch it?
 Beta testing  
 Data analysis 

We began testing the proposal with a beta testing group, with few, hand-picked real estate agents that helped us out during the process of building the app. Soon, we began receiving many feedbacks (both from the real estate agent and the analysts using the back office) and iterating our solution until it was ready to be available for everyone. We released the feature for everybody and waited to see the results.

So far, we have moved around (value) in proposals through our app and back office. It has not only been largely adopted by many real estate agents, but we have also received many positive feedbacks on it. One of the most common things we would hear when we talked about this feature with the real estate agents is that it was virtually impossible taking the Excel sheets that they were used to and making it work on a cellphone - but fortunately, we were able to do it in a very simple way. 


It's important to note, also, that this is a feature we are always improving. Though we moved on to tackle other steps of the real estate selling journey, we still learn new things everyday about how financial proposals are made in this market, especially as we get new clients to use the product.

Here are some examples of what it looks like currently:

App Screens Perspective Mockup.png

What I learned from this project?

The main takeaway from this project to me was the fact that sometimes you need to invest a lot of time in a research to achieve what you want. We are so used to working with time restrictions that big projects like this sometimes are not properly carried due to that. This was not the case here - the company understood the complexity of the issue and allowed us to really take the time we needed in order to achieve our goals.

It was my first time doing research that took into account regional differences, and this was super interesting for me. Traveling and being able to get different insights on how real estate sales can differ from region to region was really helpful for our product.

A very interesting point of this project is also the fact that while we built the tool for the real estate agent to build their client's financial proposals, we were also building the analysis tool for the real estate developer to analyse these financial proposals. Both researches were feeding each other and we had to take into account all the discoveries we made on each side of the coin.

Other than that, we had such a huge learning towards doing research while working from home - we were really impacted by the Covid pandemic in the middle of the project, so we had to re-learn how to make user testing, interviews and so much more from our own houses. 
bottom of page