Radian Home Price Index

Project Scope

Radian is an industry leading real estate valuation and data company. Boost Labs was tasked with designing and building a modern interactive landing page that visualizes for users how Radian HPI (Home Price Index) application functionality operates. The website was to allow Radian to convert web traffic, and compete with enterprise competitors such as Freddie Mac. The site contained interactive content, captured user metrics, and other marketing objectives.

Description of Work Performed

Boost Labs designed a landing page to educate users about what the HPI product is all about. Within the page, a multi-step wizard was built for users which captured basic information about what types of market comparisons they would like to make. Based on the user’s selections, multiple home price indices are generated, based on Radian’s HPI cohorts. The selected cohorts are then plotted visually and supported with other statistical summaries and details. The webpage was tooled for an API connection, allowing live data to be used.

PROJECT DURATION

4 MONTHS

Discovery / Data Analysis: 1 Month
Minimal Viable Product (MVP): 3 Months
MVP w/ New & Improved Report: 4 Months


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Services We Provided
  • Data Visualization
  • Application Prototyping
  • UI/UX Design & Development
  • Product development
Project Challenges

The biggest challenge was enabling users to quickly and easily build several cohorts (including market and attribute) within a few clicks, in order to present visually appealing data to users quickly. In order to accomplish this, Boost Labs had to dig in and learn as much about the home price index calculations as possible, in order to pitch viable ways to lead the user to gain a lot of insight without needing to input a lot of fields. Afterall, the webpage is responsible for converting users who wish to pay for a more robust tool, so the interactions had to remain very easy. Another challenge involved hooking the front-end developed site up to a data API which could quickly and easily serve the complex data quickly.

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