Walk Score was founded in July 2007, inspired in part by a Sightline Instituteblog post that proposed the number of establishments within one mile as a simple test of walkability. The company's mission is "to promote walkable neighborhoods" with the belief that such neighborhoods are "one of the simplest and best solutions for the environment, our health, and our economy." In January 2012, the company announced that it had recently raised $2 million from investors. On October 22, 2014 the company was bought by the residential real estate companyRedfin.
Consumer products
Walk Score
The company's flagship product is the Walk Score, a walkability index and the namesake of the company. Walk Score is a type of automated efficiency model focused on location efficiency. The company serves more than four million scores per day to over ten thousand participating websites. A Walk Score may be assigned to a particular address or an entire region, and the company maintains a ranking of the most walkable cities in the United States. Josh Herst, CEO of Walk Score, has stated that he wants Walk Score to be a part of every real-estate listing in the future. He envisions the Walk Score of a home to be as important as how many bedrooms or bathrooms the property has. According to the site's creators, "The Walk Score algorithm awards points based on the distance to the closest amenity in each category. If the closest amenity in a category is within.25 miles, we assign the maximum number of points. The number of points declines as the distance approaches 1 mile —no points are awarded for amenities farther than 1 mile. Each category is weighted equally and the points are summed and normalized to yield a score from 0–100. The number of nearby amenities is the leading predictor of whether people walk." Relevant amenities include "businesses, parks, theaters, schools and other common destinations."
Other features
Similar to the Walk Score, the company also assigns a Bike Score and Transit Score to points on the map. Walk Score can generate a commute report that shows the time required to travel between two points, providing a visual representation of the changes in elevation during the trip. Commuting options include walking, bicycling, driving, or taking public transport. In 2011, Walk Score unveiled an apartment search tool that locates available housing based on commute time to a given location. The tool calculates commute times for various modes of transport including walking, cycling, driving, and public transit. Walk Score has developed a variety of tools for real estate professionals, such as neighborhood maps and APIs. Multiple independent studies have demonstrated that above-average walkability correlates to increased housing values: in the metropolitan areas studied, higher Walk Score typically added US$4,000–$34,000 per home. The company also provides data to leading research institutions, academics, and city planners including:
Walk Score and Transit Score for all U.S. and some international addresses
Road metrics such as intersection density and block length
This data is available for download or accessible through an API.
Criticism
Walk Score has received some criticism in the media, particularly from urban planning professionals, for the limits of its accuracy and relevancy in methodology and results. Specifically, Walk Score doesn't calculate whether there are sidewalks, how many lanes of traffic one must cross, how much crime occurs in the area, or what the weather is typically like. It also doesn't differentiate between types of amenities, for example a supermarket grocery store versus a small food mart selling mostly chips and liquor. Walk Score does not accurately score areas adjacent to international borders. The algorithm prioritizes locations across the border which leads to low and inaccurate scores.
Professional products
Travel Time API
Walk Score's Travel Time API provides a programming interface to get travel times between an origin and a set of destinations. Travel Time API can sort multiple destinations based on walking time, taking a public transit, driving time, or biking. Suggested applications are ranking points of interest nearest to multiple destinations, such as hotels near multiple meetings or attractions; ranking multiple destinations nearest to a specific location, such as sorting of local deals; and for maps and visualizations.
