Trulia Makes Data Visualizations Key Aspect of Home-Hunting Service

by   |   July 24, 2012 5:35 pm   |   1 Comments

Anyone who has ever been house-hunting knows the excitement of the search can quickly turn to eye-glazing confusion as shoppers become overwhelmed with information, much of which has no context and therefore is of little value—a slender thread upon which to hang a major life decision.

Trulia, a San Francisco-based real estate company, is offering house- and apartment-hunters an opportunity to harness analytics to make their quest for a dream home easier informed by data. “The road to finding a place to live doesn’t have to be frustrating—in fact, when armed with the right tools, it can be downright pleasant,” the company notes. In Trulia’s case, the right tools are interactive charts based on data analytics that show users real estate information in ways they likely haven’t seen before.

For example, home shoppers who aren’t in the 1 percent often don’t bother looking in affluent areas because they assume they can’t afford to buy there. So Trulia created an interactive graphic that shows the comparative ranges of house prices in particular ZIP codes.

In the graphic below, house-hunters can see that the least-expensive properties in Boston’s affluent areas (Beacon Hill, downtown and Back Bay) are priced higher than the most-expensive properties in almost all of Boston’s less-affluent neighborhoods.

Snapshot of Trulia's study of Boston home prices

Users of Trulia’s visualization can compare price ranges for homes for sale in Boston by ZIP code. In this view, neighborhoods around Fenway Park cost less than affluent Beacon Hill (line on far left). While some homes from both areas fall within the same range, buyers need to check price per square foot, Trulia notes.

Granted, home shoppers could get this information by doing a lot of research and working with a real estate agent, but Trulia’s visualization provides a self-service way for house hunters to grasp the larger reality of the city’s housing market.

Trulia get its data from a number of sources, but mainly proprietary data from the company’s research, says spokeswoman Daisy Kong.

Data visualizations are a key component of Trulia’s service. The company posts a number of visualizations on its Trulia Trends blog that also use U.S. Census data and data from partners, such as foreclosure data from RealtyTrac or job data from Simply Hired, Kong says.

The data visualizations on the blog are time-frame specific, so they’re not updated in real time. On the company’s home page, however, where house- and apartment-hunters can search for properties, it’s a different story.

“On the main Trulia site, all of the data in our visual products (such as the interactive maps on Trulia Local for crime, school ratings, property information, commute times and neighborhood amenities) are updated as frequently as our data sources are able to update their data,” Kong says. “For example, the crime maps are updated daily, but different cities report crime at different frequencies. Some update every week, some every month and some every day, so as soon as there is new data, it will be reflected in the map.”

A Cross-Functional Visualization Team
Trulia’s data visualizations such as the Boston and San Francisco price-range presentations are built using standard web technologies such as HTML5, CSS and JavaScript. “We’ve made heavy use of D3.js, a JavaScript library for data visualization, and also jQuery,” Kong says. “D3.js uses a Web technology called SVG (scalable vector graphics), which allows you to draw objects like basic shapes and also more complex things like maps onscreen and manipulate them in the browser.”

Presentation decisions are a collaborative effort. “The team behind Trulia Trends is a cross-functional team made up of design technologists, data analysts/economists and writers,” Kong says. “We work together to decide what story to tell and how to tell it in a compelling way. Typically, we start with the story [and] data to figure what’s our punch line and from there figure out what’s the best way to tell that story visually – long before our design technologists start coding.”

The team will do internal quality checks along the way and make corrections and changes as needed, she says.

Trulia’s Trends blog team brainstorms weekly to come up with new ideas, which can be sparked by a data set or, more broadly, by a story the team wants to tell using data visualizations. On July 24, the team noted that research based on search queries from users in 15 countries shows that rising U.S. home prices are starting to turn off house hunters from abroad. Other pieces have used data to examine what time crimes typically occur in 25 major U.S. cities.

Since unveiling its service more than six years ago, Trulia has seen the traffic on its Trends blog grow to more than 27 million users each month. Kong says the website’s demographic is a “mix of people who love design and data visualization as well people who work in or love real estate.” The overall website’s demographics, she says, “are mostly transaction-ready home buyers and renters.”

House-hunting can be an emotional affair. And while Trulia allows comments on its presentations, the feedback has been quite civil. One commenter on the San Francisco price-range visualization notes that ZIP codes, while a useful data tag, are not a precise descriptor for neighborhoods. Another reminds readers about a consideration for homeowners all over the country: The data does not include real estate taxes.

Chris Nerney (cnerney@nerney.net) is a freelance writer in upstate New York. Follow him on Twitter @ChrisNerney. 

Editor’s note: This original version of this story has been updated to reflect a clarification about website traffic to the Trulia Trends blog. 

Tags:

One Comment

  1. Posted October 25, 2017 at 10:02 pm | Permalink

    Awesome issues here. I am very satisfied to peer your article.

    Thank you so much and I am having a look ahead to touch you.
    Will you please drop me a e-mail?

Post a Comment

Your email is never published nor shared. Required fields are marked *

You may use these HTML tags and attributes: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <s> <strike> <strong>