LinkedIn is the world’s largest professional network with over 810 million members in over 200 countries and territories worldwide. It allows members to create profiles summarizing their education, work experience, skills, and accomplishments. Members can then connect with each other and build professional relationships.
One of the key features of LinkedIn is the ability for members to share their location information on their profile. This allows other members to see where someone is based and can facilitate networking and job opportunities in specific geographic areas. However, in recent years it has emerged that LinkedIn has failed to properly save and utilize the location data for all of its members. This article will examine why this failure occurred and the impacts it has had on LinkedIn members and the platform as a whole.
The Benefits of Location Information
Location information provides many benefits for LinkedIn members looking to network or explore job opportunities:
– It allows members to find and connect with professionals based in their city or region. This can facilitate in-person meetings, events, and collaborations.
– Recruiters can search for qualified candidates based in specific geographic areas for job openings. This allows them to find local talent efficiently.
– Members can look for new jobs in their preferred locations without having to sift through irrelevant postings.
– Users can join specific geographic LinkedIn groups to connect with professionals in their city. This aids community building.
– Businesses can target ads and content to LinkedIn members in their area. This improves engagement.
Overall, location data enables a localized LinkedIn experience that connects professionals based on geographic proximity and interests. Members can build networks and access opportunities in their specific area.
The Failure to Save Location Data
Given the clear benefits of location information, it may seem surprising that LinkedIn failed to properly retain this data. However, in 2018 it was revealed that LinkedIn was likely only saving location data for around 50 million of its over 500 million members at the time. This equated to around 10% of profiles having an associated location.
This failure was due to issues with LinkedIn’s infrastructure and database systems. As the network rapidly expanded, adding millions of new members every month, their systems were unable to cope with the volume of information being stored. Locations relies on sophisticated data joins between profile information, IP data, and geocoding APIs. With their exponential growth, LinkedIn engineers failed to build scalable systems for reliably managing this.
The result was that location information was only saved for a fraction of members. Furthermore, even when a location was saved it was rarely updated or kept current. This meant the available location data was incomplete and inaccurate.
The Impact on Members
This failure to capture location had significant impacts on the LinkedIn experience for many members:
– Networking and connecting with nearby professionals became more difficult without reliable location data.
– Opportunities for local in-person events and meetings were reduced without accurate locations.
– Recruiters struggled to effectively source location-specific talent and candidates for openings.
– Fewer geographically relevant jobs were recommended or surfaced to passive job seekers.
– There were fewer location-based groups and discussions they could participate in.
– Businesses found it harder to advertise roles or products to people in specific areas.
Overall, the lack of saved location resulted in a more disconnected, randomized LinkedIn experience versus the localized networking that was promised.
LinkedIn’s Efforts to Improve
After the issues around location emerged, LinkedIn did acknowledge the problem and began efforts to improve their location capture and storage systems. Some of the key initiatives included:
– Investing in expanded infrastructure for their member database to handle location entries at scale.
– Building more automated workflows for entering and confirming location during signup flows.
– Using profile activity data like sign-ins and engagement to infer locations where possible.
– prompting existing members who lack location info to add it within profile settings.
– Acquiring other location data providers to fill in missing location data.
While these initiatives have improved LinkedIn’s location data capture, they still have significant work to revive the location-based experiences many members expected. Today it is estimated 15-30% of profiles have reliable location info – better but still insufficient.
Best Practices for Location Data
LinkedIn’s struggles provide some key lessons for any digital platform looking to leverage location data:
– Build scalable data systems from the outset to handle rapid user growth. Don’t tack it on later.
– Use multiple signals like self-reported data, APIs, WiFi signals, etc to derive locations. Don’t rely on just one.
– Actively prompt for user location during onboarding flows. Don’t assume they will provide it unasked.
– Set up ongoing monitoring to keep locations updated. Locations change as users move.
– Enable user control over location sharing. Don’t force it. Provide privacy options.
– Limit use of location data to core workflows only. Avoid extraneous usage without clear benefit.
Conclusion
In summary, LinkedIn’s failure to reliably save location data for the majority of its members severely limited the ability for localized professional networking the platform was designed to provide. Despite awareness of this issue, LinkedIn neglected scalable location infrastructure during their hypergrowth phase. This resulted in diminished value for many members, recruiters, and advertisers. LinkedIn still lacks comprehensive location data years later. This serves as a cautionary tale for any digital platform looking to leverage location-based services. While the data can provide immense value, it requires deliberate engineering decisions early on to realize the full benefits.