Zendesk can now predict who's likely to stop using your service before you do
The latest to get in on the action is Zendesk, the $1.8 billion cloud software maker focused on customer support.
On Tuesday, Zendesk launched "Satisfaction Prediction," a new feature that helps companies predict and identify the customers most likely to leave their service. It uses machine learning to sort through things like words used or time waited in every customer inquiry (commonly called "tickets"), and serves as an "early warning system" that finds the ones that had the most negative experience and are at-risk of stop using your service.
This helps companies separate the customer comments that need urgent care from the more run-of-the-mill type of inquiries, and deal with the ones that need help faster. Then they can route those inquiries to the more highly-skilled agents who can provide immediate support, and ultimately prevent them from leaving your service.
Big tickets
In fact, Salesforce CEO Marc Benioff pointed out in a recent conference that machine learning and predictive analytics will be where the next wave of opportunity comes from for every business software maker.
"This will be the huge shift going forward, which is that everybody wants systems that are smarter, everybody wants systems that are more predictive, everybody wants everything scored, everybody wants to understand what's the next best offer, next best opportunity, how to make things a little bit more efficient," Benioff said.
Here's a few screenshots of what Zendesk's Satisfaction Prediction looks like:
