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Jobsite Search Result: Site Search 60% More Relevant

by Louisa Bainbridge on Jan 23, 2017

Recruiters hate wasting time, so Jobsite found a way to help their clients work smarter, not harder. Good recruiters fish from the best candidate pool, giving themselves the maximum chance of placing a candidate in a role. Jobsite’s new CV search helped them receive the best results every time.

Improving search result relevancy

Jobsite realised that when using a distance-based candidate search, it ignored any CV results that were considered far away in miles, but located near fast transport connections. When recruiters could search for candidates ‘within 45 minutes’ rather than ‘within 5 miles’, they could locate the most relevant set of employees. This search, using the TravelTime API, tapped into a new set of CV results.

Jobsite-search-result-miles-radius

As well as identifying new opportunities, time-based search pinpoints which potential clients are more likely to reject or accept an offer based on commute timings. Even with results that could be considered nearby, the lack of transport connections could make them wholly impractical – but with travel time, they’re filtered out. By eliminating these misleading results from travel black spots, recruiters no longer need to waste time chasing leads that aren’t relevant. Likewise, including areas that are a greater distance away, but have fast travel connections, opens areas of opportunity that would have previously gone untapped. TravelTime search gives recruiters more relevant results more frequently, which means less time wasted, and more happy clients.

Jobsite-search-result

How time-based searching works

The image below is a demo made by Jobsite showing the difference between a radius search and a search using the TravelTime Search API. It highlights which CVs would be missed because a radius search assumes the candidate is too far away, however when travelling it's easy to reach these points. The red shows locations that appear easy to reach by distance, but aren't located on fast transport connections. 

 Jobsite-search-result

Just like a normal distance-based search, recruiters enter their usual criteria for the role – job title, salary, skills etc. Next, they specify the maximum commute time in minutes, as well as selecting the method of travel – public transport or driving. For example, a recruiter can search within a 45-minute drive of the office, and because Jobsite performs every search to arrive by 8.45am, it leaves a bit of breathing room for rush hour congestion and delays. The Jobsite search result page displays the journey time for all potential candidates, so the recruiter can quickly decide if it’s worth calling right off the bat.

How can you recreate the Jobsite search?

Firstly sign up for a free test API key. If you're not a developer and want to discuss getting started, please contact us. To create the isochrone shapes (the green travel time area in the shape above) use our time map feature which returns points to draw a shape on a map. They also use the time filter option. This feature is an alternative to a distance matrix, where you can send a single location (for example the location of the job role) and calculate journey times to all candidates in a database. This can be done using the time filter standard to get journey times from 1 origin - 2,000 locations or time filter fast for 1 origin - 100,000 locations. 

What they can tell their clients

If you call 10 candidates a day there’s a chance that many of them can’t reach the position within a reasonable time, however using travel time you’re able to find candidates that are 100% relevant. Distance-based searching doesn’t reflect a location’s context, so it ignores what a candidate knows about congestion, geography, transport modes.

What they say

The API is super fast, easy to use and quick to integrate. We received excellent support from the team.

Chris Burles, Head of Product, Stepstone

Where else would this work?

Filtering by travel time would improve the relevancy of any sites performing location-based on site search, including hotels search, classified ad search, property search and more.

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Topics:
TravelTime Search case study Case study