LinkedIn taps Microsoft’s Bing for new Commute Time feature targeting job seekers
LinkedIn is becoming increasingly integrated with the other platforms and services in parent company Microsoft Corp.’s portfolio.
The latest example of this arrived this morning in the form of Commute Time, a new feature in the social network’s widely used job search tool. It relies on Bing Maps, Microsoft’s Google Maps alternative, to give users information on how far a position would require them to travel on a day-to-day basis.
The capability checks off a big box for LinkedIn. In a recent survey conducted by the social network, over 80 percent of the respondents said they would take a pay cut for a shorter commute. Making information about travel times available to users will allow the Microsoft subsidiary to become that much more competitive in the crowded online recruitment market.
To check commute durations, a user must navigate to the Job Detail page of a position for which LinkedIn provides travel details. There, professionals can bring up a “See your Commute” tooltip to generate a time estimate.
LinkedIn calculate trip durations based on a user’s starting point and the time of day and expected departure time. The feature generates a map showing the fastest route to the job site, along with a breakdown of estimated travel times. Prospective workers can check how long it would take them to reach the location by car, bus or foot.
LinkedIn will let users save their commute settings so they can quickly check commute times at a glance when browsing openings. Listings for which this data is available are now marked with a pin icon.
In a blog post, LinkedIn engineers Jeffrey Lee, Austin Lu and Minhu Nguyen said their team has plans to enhance the feature over time. One of the improvements in the works is a new search filter that will let users narrow down listings to only those positions with a commute time they find reasonable. That would help LinkedIn match the similar capability that Google Inc. already provides with its rival job search engine.
Image: Ben Scholzen
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