For both renters and property managers, time is of the essence when it comes to getting a lease signed and a move underway.
Findigs, a real estate fintech company providing a digital screening platform, recognized the need for more streamlined and efficient decision making throughout the rental process. As its team responded to property manager feedback and expanded Findigs’ offerings, they set out to develop a new feature — Group Insights.
“Prior to the implementation of Group Insights, we didn’t have the ability to display an aggregated view of an application group on our dashboard,” Software Engineers Ariel Ng and Parth Patel told Built In. “This lack of visibility made it challenging for property managers to efficiently evaluate and decide on rental applications, causing delays in the overall process.
“The goal was clear,” they continued. “Provide a comprehensive and easily digestible view of applicant criteria, empowering property managers to make faster and more informed decisions.”
“The goal was clear: Provide a comprehensive and easily digestible view of applicant criteria, empowering property managers to make faster and more informed decisions.”
In order to keep the product process moving quickly, Findigs is committed to a cohort of engineers known as the Quick Reaction Force. The small group of experts comprises engineers with expansive product and engineering domain knowledge to quickly troubleshoot issues that may otherwise disrupt process for team members.
“As the company’s needs have evolved, the QRF team is also now tasked with quickly tackling any urgent, high-value product feature requests with ambiguous requirements and short deadlines,” the engineering duo shared. “QRF has the autonomy and skill to take the requests, plan product requirements, develop, QA and deliver 🤠.”
The cowboy emoji at the end of their statement is in keeping with QRF’s get-it-done approach, which Built In dug into further in an interview with Patel and Ng.
Findigs was able to deliver a new design that provides a clear and concise view of important criteria for each applicant in a digestible format for our clients to use. The Group Insights feature has greatly improved our clients’ decision-making experience and has helped our renters get into homes faster.
What role did you two play in developing and launching Group Insights? What tools or technologies did your team use to build it?
The team led the frontend and backend development of the feature. We first designed and implemented the backend to generate the insights and return them back to the frontend in a manner that was easily renderable.
The backend work was successfully accomplished by carefully creating Django schemas in Python that were both reusable and scalable for different aspects of the applicant, including credit reporting, income and identity verification. It was critical for us to understand all possible outcomes of each applicant’s insights that we stored and make sure we had all of these cases covered to be handled gracefully.
On the frontend we primarily used Typescript, React and React Table for the build. Based on the design pattern, we built a set of reusable components and mappings that were flexible enough to handle a variety of states, colors and associated text that were then mapped against specific keys returned from our internal API. Given the variety of cases and outcomes that are possible across our system, the table had to dynamically render the data and account for any inconsistencies. We were also involved in the project management, product knowledge and documentation.
“Given the variety of cases and outcomes that are possible across our system, the React Table had to dynamically render the data and account for any inconsistencies.”
What obstacles did you encounter along the way?
Neither of us had strong domain knowledge of the original legacy feature; therefore, discovery was the first big obstacle. Throughout the development cycle, we both ran into outcomes for our insights that were not originally accounted for, and these insights then led us back to design discussions which ultimately changed project requirements. In order to overcome these obstacles, we had to not only dive deep into legacy product code but also had to educate our cross-functional team members to make informed decisions.
What teams did you collaborate with in order to get Group Insights across the finish line?
We collaborated closely with QA, product and design. In order for the project to move smoothly, it was crucial for us to be highly communicative and provide clear documentation for our team. We utilized daily standups and Slack channels for consistent touch points and also held focused meetings with key stakeholders from each team to tackle the unknowns that were discovered during development. The focused meetings were used to discuss new findings and to talk through how we could best make design and requirement changes. It was helpful for us to document our agreed-upon decisions to ensure clear alignment from all sides.