Manual orders and case resolution were slowing down customer support

Before, Iron Mountain’s service agents had to switch between multiple apps and databases to gather enough context for each customer’s order or inquiry. The order process was manual and information was located in different places, forcing agents to swivel chair between different systems. Agents also had to search the knowledge base manually, resulting in long lead times and a growing backlog of inquiries. Despite massive amounts of customer data, agents couldn’t easily access it and use it meaningfully.

Service agents keep cases moving with predictive AI

Iron Mountain service agents handle a high volume of cases across phone, email, and chat. Einstein looks at the details of each case to recommend the best article to help close it thanks to predictive Article Recommendations. This saves agents from having to manually search the knowledge base, so they can close cases faster.