How Centre is Using AI to Improve Customer Experience

While in many ways AI seems to be looming over us with more and more automation, at Centre, we're focusing on using this powerful tool to help us better serve our customers. Our goal is to use the enterprise level tools we already have and pair them with the power of automation to give our customers an experience that addresses their unique needs with the local touch we're known for. 

At Centre, we have 3 pillars we stand on every day: provide enterprise experience and personalized service with a local touch. We're passionate about quality solutions that build lasting relationships over time. But as AI has come into the foreground of every conversation, in some ways it's getting difficult to sift through the industry noise without sacrificing relationships in the name of progress. Nevertheless, in order to remain relevant in the industry so we can provide a truly enterprise level experience, AI had to start edging its way into our service delivery model. 

So how do you maintain relationships and customer trust while still using AI? 

problem: aging support requests and delayed communication

When customers submit a support request, we have a proven track record of 83% solution delivery and closing that ticket within 1 day and 90% of them within 3 days. But sometimes, requests take a little longer. Maybe we need to loop in a Subject Matter Expert (SME) or another Technician or maybe it's a problem that requires an internal meeting to accomplish effectively. Those actions just take longer. 

But, as with anything that takes longer, there can be negative emotions from the customer's side. Our goal is to keep customers in the loop with constant communication on what we're doing to solve their problems, but as requests age with more and more resources required to accomplish them, communication expectations can be delayed. 

Still, delayed communication isn't acceptable for our normal expectations. We strive to provide a quality experience every time, so as negative reactions started to pop up more, we turned to AI to help. 

Solution: Using AI to Conduct Root Cause and Sentiment Analysis

Through our ticketing system we use for all support requests, there are multiple modules that do things like track communication, log internal help requests (like for an SME), and show action plan steps, just to name a few (there's a LOT more).  A new feature we've added to our tool set is the use of AI as a baseline for customer satisfaction. Here's how it works:

• When a ticket ages to around 1 week, we want to take a closer look at customer's perception of their experience based on what we've provided so far.
• Based on the logged communication between customer and their dedicated technicians, an AI module scans the correspondence and provides a score of how customers are feeling about their experience with their support requests. 
• This AI module then provides a "Sentiment Analysis" score, which gives a holistic view of our customer service.
• Based on the sentiment analysis, we culminate with a Root Cause analysis. Basically, we ask ourselves and the support team, "what questions do I really need to answer based on the problems I have?" By asking this, our team is accountable for doing a deep dive into the problem. It's there we find answers.
• We then strategize how to improve the customer experience using our 3 main ways of service delivery:
  • Attack Plans:  Attack plans are more holistic, looking and prioritizing all tickets. The first thing we do every day is take a look at our internal dashboards which tell us how many open tickets we have to "kill." Based on those requests, each team creates a daily plan of attack for solving all open tickets assigned to that team and address the problems quickly.
    
    

• • Action Plans: Action plans then look at each specific issue. This includes things like do we need to escalate this ticket? Should we get an SME involved? Do we need an internal meeting to brainstorm how to solve the issue? If the answer to any of these is "yes" then we immediately create the necessary actions to solve the support issue. 
    
    

• • Solution Plans: Each ticket then requires a solution. These plans are based on questions like when was the last time we reached out to provide customers with a status on their issue? Have we produced a summary of our work so far? After this, we allow the customer to provide feedback on their experience, further helping us understand where our strengths and weaknesses are. 

Impacts on Centre and Your Business

Better Communication When You Have Issues ✅

With a better and faster way of understanding how customers are experiencing our support, we can learn where we have gaps. This includes delayed communication. We're working to completely eradicate this problem so you feel the true partnership we take pride in offering customers. 

You Get a Say In How Your Support Is Going ✅

Since we're focusing on increasing customer connection, you'll get more opportunities to provide feedback. Thanks to our tool set, this can then help us understand not just how your experience is with that specific request, but with your requests as a whole. Your experience improves every time! 

Enterprise Tools, Improved Customer Experience ✅

Using AI ethically and responsibly while building relationships is our sweet spot. AI is helping us understand your needs better so we can provide more dedicated technicians with a personalized solution for your business in a timely manner. We're excited about how this will improve customer experience in the long run! 

Want to learn more about how we're using ai?

Contact us and we'll show you.