LinkedIn, the social network for the working world with close to 600 million users and now under the wing of Microsoft, has announced an acquisition as it continues to work on expanding the ways that people already on the platform use it.
It has acquired Glint, a startup that provides employment engagement services for businesses and other organizations.
Terms of the deal are not being disclosed. For some context, Glint had raised nearly $80 million — including these rounds for $27 million and and $20 million in the last two years — was valued at around $220 million in its last round according to PitchBook.
Investors included Bessemer Venture Partners, Norwest Venture Partners, Shasta Ventures and Meritech Capital Partners.
The news was announced both by LinkedIn and Glint itself in blog posts.
Daniel Shapero, VP of Talent Solutions at LinkedIn, said that the team from Glint will join LinkedIn and continue to work as a salient entity within it under current Glint CEO and founder Jim Barnett.
One big focus for LinkedIn over the years has been how to expand the amount of engagement — and therefore revenue — it derives from paying customers, and in particular businesses that are on its platform.
Today some of LinkedIn’s revenue generating products include premium memberships, recruitment (Talent Soutions) and education, by way of Lynda.com.
Glint is another step ahead in that wider strategy to build out more services for those users, alongside existing services like education, CRM tools and, most recently, business intelligence.
And the blog post from Shapero, who heads up Talent Solutions, is another indication of how this will fit into LinkedIn’s recruitment business.
Today a business might use LinkedIn for recruitment. Now, tomorrow, it can continue to use LinkedIn for more services around those employees once they have been hired.
Glint’s current list of products including Employee Engagement, Employee Lifecycle, Manager Effectiveness, and Team Effectiveness.
Glint works by way of employee surveys, which it then analyzes using machine learning, natural language processing and predictive analytics.
Its reports measure how employees feel about things like management, compensation and workplace culture and makes suggestions for how companies can improve their scores.>