If you use popular online services like Netflix, Amazon, or Facebook, you’re benefiting from the power of recommendations — a common form of artificial intelligence. These recommendations are, of course, based on user data and activity. Though these pieces of functionality are common in consumer products, they can also drastically reduce resolution times from the service desk, creating a better customer experience.
This functionality deals with large amounts of dynamic data (meaning, more data is being added all the time) to present the user with suggestions. This could include whether a user has “liked” a product or content on a site. You’ll see it in language such as, “because you watched The Office.”
While Netflix is collecting user bio and data on content you’ve watched, SaaS products can collect user data and activity just the same. They can use this data to push users toward time-saving knowledge or activity at their jobs. This functionality is perfect for SaaS products since they’re typically used as business tools, collecting data and using it to drive tangible value. These suggestions can save time and money in measurable ways, making business applications a perfect place to leverage them.
“Suggested Solutions” For the Service Desk
The service desk is set up to maximize the efficiency and productivity of the organization. The power of artificial intelligence, and this specific functionality, can certainly contribute to that goal. Service recommendations enable users to find the answers to their problems before having to turn to support staff.
When a user has a problem, he or she can navigate to a self-service portal. This concept isn’t new, but “suggested solutions” are. Previously, users could search through the knowledge base at the service portal, looking through related articles. Now, through this power of suggestions, your service desk solution can actually do that for you. Based on the user’s past activity, location, department, keywords in the subject of the request, and a number of other factors, the user can actually receive a suggested solution without lifting another finger.
Self-Service and Lower Resolution Times
Think about your current resolution times at your service desk. How long do users have to wait for employees to respond, let alone to resolve their tickets?
“Instead of constantly turning to IT for non-urgent problems, they can find the solution themselves.”
A self-service portal powered by suggested solutions will improve those metrics. Instead of constantly turning to IT for non-urgent problems, users can often find the solution themselves, with the help of this technology. It creates a net to catch repetitive problems — an experience many users have grown to appreciate in the consumer world. Now, they don’t have to wait for a response or a resolution.
But more than just a benefit to the users, these suggested solutions will simplify technicians’ lives in a number of ways. First, increased self-service will cut down the number of tickets and requests. Naturally, this will allow the support staff more bandwidth to respond to incidents quickly. Of course, tickets are still going to come through to technicians, even with this added technology in place. Your technicians have access to the same suggested solutions as a first line of defense, which gives them a set of resources they can use to resolve tickets in real time. Organizations are always looking for ways to better arm their technicians (and avoid solving repetitive problems), and this is a great way to accomplish that.
Though these AI-powered suggestions have their origins in e-commerce, it’s clear that their application is considerably broader. When correctly deployed at the service desk, you’ll find tangibly quicker response times, resolution times, and CSAT scores. To learn more about how automation can have a positive impact at your company, download our white paper: 101+ Ways to Automate Your Workplace.
About Brendan Cooper
Brendan is a Product Marketing Manager at Samanage. He works closely with customers to connect them with beneficial functionality in the Samanage application. He also works with developers to build an application that meets customer needs.
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