Put.io installed a free version of Intercom, which allowed it to immediately extract live data, such as a user’s last login, signup date, number of sessions, city and country, and much more.
“Being able to filter users by geography and behavior is great, but my biggest revelation was sorting users by the number of Twitter followers — we had some high rollers, by Internet standards!”
After getting a clear picture of users in their application, Put.io began using Intercom’s messaging features. Put.io installed Intercom’s in-app support widget so users could launch an in-app conversation without exiting the application. From Put.io’s perspective, it was easier to respond to customers thoughtfully and efficiently thanks to the additional context of live user data alongside each incoming message.
After doing this for a few weeks, things got more interesting. Put.io began proactively solving problems or warning customers of potential issues.
First, it grouped common support grievances that might be improved with the right information. Hasan’s team composed auto-messages targeting users before a problem arose. For example, one common issue customers faced was slow Internet speed, so Hasan sends this in-app message to active users.