Artificial intelligence for customer experience: 5 key use cases

If you aren’t already using artificial intelligence (AI) to improve your customer experience, you’re already behind.

I know it sounds controversial, but there are already a ton of different ways in which businesses across a wide range of industries can—and already do—use AI to enhance the customer experience.

As someone who’s leading a contact center support team and also working in a company that’s building an AI customer intelligence platform, I’ve seen these use cases from not only our customers but also our own agents and supervisors. I’m going to walk you through a few of these below.

How is artificial intelligence used for customer experience?

Artificial intelligence (AI) can be used in a number of ways to improve the customer experience. Here are just a few of the most common use cases.

1. Deflecting calls

Today, there are many customer service AI tools that help deflect calls in a variety of ways. One that you’re probably familiar with is conversational AI (kind of like a very advanced AI-powered chatbot).

Similar to how IVR (interactive voice response) menus on the phone can provide simple pre-recorded answers to frequently asked questions, conversational AI can do the same thing, only it’s on your website’s live chat window and even digital channels like WhatsApp.

In Dialpad, for instance, we can set up this Ai Virtual Assistant to answer different questions (with text, images, and even video!) with the drag-and-drop builder—no coding needed:

Unlike traditional chatbots, AI can deflect more diverse calls (not just basic questions)—and even suggest where we have gaps in our knowledge sources!

2. Helping agents in real-time

Whether you have a team of outbound sales reps or customer support agents, you’ve probably got a mix of skill levels. How can you make sure that all these agents are providing a consistently high level of service to customers, no matter if they’re new hires or seasoned vets?

AI can help with that. Dialpad’s real-time Ai Agent Assist, for instance, can automatically search all your connected knowledge sources (even unstructured ones like PDFs and past customer conversations) to pull relevant information right onto the rep’s screen:

3. Automating tasks for agents

Something that almost all agents have to do after they end a conversation with a customer is disposition the call, among other after-call work (ACW).

It shouldn’t take more than a minute or two, but over time, this can really add up. AI can help with these types of tasks by suggesting dispositions instantly, based on the content of the call, to give agents a head start on their ACW.

Similarly, AI can also transcribe and highlight key moments, questions, and action items from a call, which allows agents to focus on the conversation instead of trying to jot down notes. This is what Dialpad’s AI-powered call summary looks like, as an example:

4. Empowering supervisors to make good staffing and training decisions

Beyond helping agents live during customer calls, AI can also help supervisors with monitoring common questions and issues that come up, so they can improve their contact center training materials and the overall customer experience.

For example, with Dialpad Ai’s speech recognition ability, our supervisors can create “Custom Moments” to track specific keywords and topics. Want to see how often customers are asking for refunds? You can create a Custom Moment to track every time “money back,” “refund,” and/or “cancel” is said by a customer on a call:

And for supervisors who are overseeing a large number of agents on simultaneous calls, it can be difficult to quickly see if an agent needs help or if a call with a customer is going badly.

In these cases, AI can do live sentiment analysis and instantly flag calls with negative sentiment to the supervisor. That’s what Dialpad Ai does—if we see a call with negative sentiment, we can just open up the live transcript to get more context before deciding if we need to listen in or barge the call:

It’s also incredibly important to evaluate how supervisors grade calls to provide feedback with agents over time. It’s not possible for supervisors to listen to every single call, but they still need to provide meaningful feedback to agents as much as possible. That’s one way Dialpad's Ai Scorecards helps customer service teams scale operations.

With Ai Scorecards, supervisors and admins can create an objective scoring criteria across all customer calls. As the agent behavior is observed by Dialpad Ai, it's automatically checked off—so when the supervisor reviews the call later, they can easily see the agent is doing what they're supposed to.

This makes it easy for supervisors to grade calls without listening to a full call recording or reading a transcript, and gives them the ability to evaluate far more calls in far less time. In turn, this means a higher volume of effective coaching for contact center staff.

5. Gathering more customer insights, automatically

Finally, AI can help you provide a better customer experience by surfacing valuable insights, without you having to manually dig through a bunch of different dashboards and reporting tools.

For example, our contact center platform, Dialpad Ai Contact Center, comes with built-in analytics that show everything from call volumes to average speed to answer and average handle time.

But not only that, it can also infer customer satisfaction (CSAT) scores without the need to run surveys. As anyone who runs a customer support team knows, one of the biggest challenges with doing customer satisfaction surveys is that not a lot of people actually fill out those surveys.

And usually only the angriest—and happiest—customers actually bother responding, which means your CSAT feedback is likely to be very skewed and not representative of how your customers feel overall.

Dialpad's industry-first Ai CSAT feature is designed to solve exactly that, by inferring CSAT scores for 100% of your customer calls thanks to its hyper-accurate transcription feature. The result: a much more representative sample size for CSAT scores, and a more accurate understanding of how satisfied your customers really are:

And this kind of data analysis superpower that AI gives us goes beyond just reporting on performance. One of the most tedious, but important, parts of a contact center manager’s job is to do QA (quality assurance) on agents’ conversations with customers.

But to do this, normally you’d have to listen to countless call recordings from beginning to end and grade them. AI can speed this process up significantly by automatically checking off if agents did what the QA scorecard listed—did they greet the customer at the beginning? Did they let the customer know that they’ll be put on a brief hold before actually putting them on hold? AI can check to make sure that these conversational “checkpoints” that contribute to a good customer experience are all there, which takes a lot of the manual work off supervisors’ plates.

The benefits of artificial intelligence in customer experience

Again, the role of artificial intelligence in customer experience is constantly evolving. But even now, we can already see measurable improvements in terms of productivity and customer satisfaction.

If you’ve been following along so far, these benefits of artificial intelligence in customer experience won’t come as a surprise.

More productive agents and supervisors

One of the biggest advantages of using AI in the customer experience is that it can automate manual tasks for agents, which not only saves time and money, but also frees up agents to focus on the conversations that actually need the human touch.

And with real-time assists, AI also helps agents talk through challenging questions without having to scramble to look for information manually.

In fact, in our State of AI in Customer Service Report, we found that contact centers using Dialpad Ai reduced average call duration by 10.06% and lowered abandon rates by 17.36%.

A national car rental company using Dialpad Ai in its contact center even found that its agents took about 50% more calls with the help of AI:

A better customer experience

Alongside a better agent experience, a related key benefit of AI is that it ends up helping businesses provide a better customer experience.

You’ve got agents with AI sidekicks that instantly give them the answers they need to help customers. Then you’ve got better conversational AI experiences that can actually answer questions effectively on their own. Ultimately, this gives customers more avenues to solve problems, on their own terms and on their own schedule.

Cost savings

Finally, all this leads to time savings and cost savings. With AI, both agents and supervisors are more productive and can do their jobs more easily, which helps with more efficient staffing, increased customer retention, less turnover… Which all leads to benefits for your business’ bottom line.

Want to improve your customer experience with AI?

If you have overwhelmed agents and/or supervisors, low visibility into customer feedback, or just a nagging feeling that your contact center could be operating more efficiently, it’s worth looking at how AI can help.

The examples I went through above are only a few of the countless ways that Customer Support and Customer Experience teams can use AI to help agents in real time, gather more conversation intelligence, and give their customers an experience that sets them apart from competitors.

See how forward-thinking companies like RE/MAX and the LA Chargers are doing this with Dialpad Ai Contact Center!