Benchmarking LinkedIn? Teamable wants to make talent referrals smarter

Teamble Announced $5 million in funding led by True Ventures. This startup will help companies connect with employee social networks to revolutionize the traditional referral mechanism.

For enterprises, the efficiency of internal employee recommendations is much higher than HR's search for needles in a haystack on open recruitment platforms. In recent years, when corporate recruiters have become accustomed to recruiting SaaS to optimize recruitment efficiency, Teamable intends to use machine learning and social networks to make the already relatively efficient employee recommendation more intelligent.

The working principle of Teamable is very simple. Enterprises can build their own "talent library" on the platform, and this process requires employees to complete. Employees only need to connect their social networks such as Twitter, Facebook, GitHub, etc. to Teamable, search and recommend contacts in their social networks to the company's talent pool through the Teamable platform, and the system will recommend possible talents to HR after calculation.

Teamable uses AI algorithms to make talent recommendations more accurate. In addition to considering the basic requirements of the company, the personal experience, expertise and other factors of these network connections can be used to match companies and help find the most suitable talent information. In addition, when HR believes that a network user meets the needs of the enterprise, it still needs to contact and recommend it through internal employees.

It can be seen that what Teamable wants to create is a more accurate closed loop of talent recommendation. For internal employees, the internal referral rewards set up by the company are really attractive, but as non-professional recruiters, it is difficult to grasp the fundamental needs of the company when making internal referrals. On the Teamable platform, employees only need to serve as talent guides and middlemen. Just the role.

In addition to employment recommendations, Teamable's AI will also collect and calculate interview conversations during the recruitment process, and provide employment suggestions to companies based on factors such as interview pass rates and salary levels to improve talent acquisition rates.

Founded in 2013, Teamable currently has 36 employees and counts Lyft, Stripe and Baidu as customers. This paid SaaS platform charges different fees based on the size of the user.

Although the Teamable team believes that LinedIn is its benchmark product, unlike the closed community created by LinkedIn, the "six-dimensional space" is not the core of Teamable. Teamable, which believes in "people are divided into groups", cares about first-degree connections. In addition, the social scene has not been added to the product design. Teamable does not care about how to establish connections, because that is Facebook's business.

As more and more companies want to recruit in niche areas from the social field, social giants have also turned their attention to recruitment. In February this year, Facebook launches job search feature, the home page (Pages) can publish recruitment positions on the information flow (News Feed), and these positions will also appear on a "Jobs" page. Users can directly click "Apply Now" to apply, and then they can send application information through Facebook Messenger. Recruiters will also respond via Messenger.

36Kr once reportedTalent Radar It is also a SaaS tool that uses employee social networks and big data analysis to find potential job candidates.