When consumers need assistance from your customer care team, they use many different channels to engage with your brand — social media, emails, chat logs, calls, and more. But for large bands, it’s especially difficult to establish a scalable process for supporting customers across channels and time zones.
Automatically surface relevant customer care inquiries
Dramatically accelerate inquiry response time with a prioritized stream of requests for easy routing
Increase the capacity of the customer care team to engage in quality interactions by automating the sorting process
Improve customer satisfaction by detecting new opportunities for engagement
How GM earns customers for life with faster customer care responses
With a large number of brands and car models under their umbrella, General Motors faces a difficult problem when trying to identify customer cares issues on social. People use the term “Cadillac” to refer to more than just the car with that name and the Chevy model “Malibu” could reference a city or a brand of rum. This makes it a real challenge for GM’s customer care team to sift through a sea of irrelevant posts to find posts from customers that actually need a response from the team. Using machine learning to train the platform on what relevant posts look like, GM’s customer care team can identify customer care issues 3x faster than before, allowing them to respond to customers 3x more quickly.
AI-Powered Customer Care
The Crimson Hexagon Platform leverages state-of-the-art AI technologies, image analytics, and the world’s largest data library. We help our customers quickly identify and prioritize care issues to drive efficiencies for their customer care teams.
Machine learning automatically identifies and classifies requests according to user-defined categories.
Access to the industry’s largest data library allows for historical analysis of customer care issues.
Image analysis allows users to analyze visual elements in care posts at scale.
Easy enough for everyone to anyone in the organization to identify insights based on customer care issues.