LinkedIn, owned by Microsoft, has started to roll out a new feature for users’ DMs, called Focused Inbox.
Focused Inbox employs an AI relevance algorithm to separate incoming messages into two tabs, “Focused” and “Other”, so it’s easy for members of the professional network to sort and respond to the important messages.
Users can switch between the “Focus” and “Other” tabs at any time, with the former containing most relevant messages while the rest remain easily accessible on the Other tab. “You can also easily move messages between the tabs. Over time, your inbox will become smarter and smarter based on how you use it,” LinkedIn says.
The company anticipates that this new DM feature will provide its users better ways to organise and manage their LinkedIn messages, hence aiding in user productivity.
The Focused Inbox comes at a time when the company says its users have demanded “a better inbox”; seeing that more of its users are turning to its instant messaging feature to communicate.
It started testing the feature in September and now it is rolling out gradually to members worldwide, with the option for members to switch back to the traditional inbox.
The company is also turning on new automatic spam and harassment detection and a new feature to report unwanted messaging.
According to LinkedIn, there are some 21 inMails — direct messages — sent every second with job opportunities at the moment. My LinkedIn inbox, for example, is always bombarded with unwanted messages, the vast majority that aren’t even worth your time to read and others that promise you new jobs and network opportunities.
The compnay says as you read or sort through the messages in your inbox, a new option to “report an inappropriate message” will be presented to you so that you can report spam.
The automatic systems, which is also rolling out gradually, “warn you when harassment is detected within private messaging.” It goes right to the spam folder, or if it’s suspicious, it stays in your inbox with a label you see before opening. You can respond to these messages the same way you would to typical spam or abuse reports.
