Imagine, for a moment, a contact center without a human in sight: artificial intelligence tools predict and solve customer problems before they prompt calls. A vast knowledge base is supplemented by smart chatbots that give customers the power to self-resolve the majority of their issues. The ringing phones that remain are intelligently routed and answered by virtual service desk agents. Can you picture it?
While we’re not quite there yet, the reality of AI in the contact center is capable of simplifying the more arduous tasks and achieving some impressive productivity gains that also make their lives easier and their jobs more enjoyable.
With a rich body of customer interactions and a continuously growing body of data to draw from, help desks are one area of business that are ripe for an AI transformation. Together, AI technology and machine learning are powering faster and more effective customer service resolutions, taking humans largely out of the equation when it comes to the mundane, rote tasks that take up time, slow productivity, and negatively impact morale.
Here, we’ll explore a few of the many use cases for AI-powered help desks that are already well on their way to becoming the norm for customer service businesses.
How AI and Help Desks are the Future of Customer Service
Use of Predictive Analytics to Proactively Solve Problems
Today, it’s hard to imagine how we’d do our jobs without being able to Google the answer to any question in a matter of seconds. In the not too distant future, it’ll be hard to imagine a world where customer service interactions take place without the help of predictive analytics.
Predictive analytics are already making it possible for help desks to forecast the volume—and in some cases, the nature—of service requests preemptively. In the coming years, AI will get even better at analyzing past data and using it to make accurate future projections.
AI-enabled help desks can use predictive analytics to proactively solve problems by examining:
- Historic and seasonal trends
- The customer’s profile, including the products and services they use and their historic support requests
- Service request patterns by customer persona
- Service request patterns by product type
- Likely surges based on software or hardware upgrades
- Random variation
These predictions can be leveraged to plan adequate staffing with a high degree of precision and provide proactive troubleshooting that reduces, and in many cases, eliminates the need for the customer to contact support in the first place.
Improved Collaboration with Smart Ticketing
When you can combine self-service via web widget forms on your site, you have the ability to offer service round the clock and front load the information gathering process, which on average, takes about 11 seconds per call according to LiveVox analysis. When you take that capability further and combine it with a ticketing system that’s integrated with your channels and CRM, you can automate needlessly convoluted backend systems that grind resolution rates to a halt.
With these automated processes, agents can manage multiple customer conversations and tickets at once, so customers get their issues resolved faster and contact centers can more accurately staff, spending less on scheduling agents because more is done with less.
Ever-Growing Knowledge Bases
Customers find knowledge bases extremely useful, preferring them over all other self-service support channels. With AI, you can build a knowledge base that’s constantly expanding based on continued learning from your human staffers and other available information channels.
An AI-powered knowledge base consolidates information from disconnected sources across your enterprise, like your CRM, agent training materials, call transcripts and even the web at large. Then, it uses natural language processing to understand what a customer is really asking about when they type a support query into a search bar or live chat. A virtual agent can then deliver a resource selected not just based on keywords, but its likelihood of actually solving the customer’s precise problem.
At the end of such an interaction, an AI-powered knowledge base brings the experience full-circle by assessing whether the resource in fact solved the customer’s problem. In this way, your knowledge base gets smarter and more nuanced with time until eventually you have a robust and highly effective channel by which customers can almost always find the answer they need without having to call upon a human agent.
Substantial Business Impacts
The argument for integrating AI and help desks is a no-brainer when we look at the potential organizational impacts.
For starters, it can dramatically reduce the overhead needed to meet customer service demands. More self-resolutions and faster interactions mean fewer support agents are needed at any given time. This, in turn, means staffing can either be reduced or agent time redirected to revenue-driving activities like upselling.
Lower call volume means wait times are shorter, allowing you to serve a greater number of customers in the same amount of time. This increased bandwidth might help you make the case for growing your customer base more aggressively, like through new product development or expanded marketing. More customers equal more revenue.
The greatest impact of AI-powered help desks by far, though, is to the customer experience. Better, more effective self-service tools and more accurate call routing lead to better service outcomes. This improved experience breeds greater customer loyalty, which ultimately leads to a higher lifetime value for every satisfied customer.
In most organizations, a small segment of loyal customers account for a disproportionately high share of revenue. It makes sense, then, to deploy strategies that will help you keep customers around longer, and outfitting your help desk with AI capabilities is one such strategy.