May 20, 2021
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The Evolution of Speech Technologies and the Influence on CX
A conversation with Chris Hodges and Ellwood Neuer at Noble Systems
Part 2: Speech Technologies and the Impact on CX
Voice Technologies encompass a broad scope, from speech and analytics engines, IVR, and self-service solutions including chatbots, headphones, and voice-activated applications and services that maximize NLP, NLU, NLG, AI, and more. The global Contact Center Intelligence Market, including speech solutions, is expected to see a CAGR of more than 25% through 2027.
Chris Hodges (SVP sales and marketing) and Ellwood Neuer (SVP solution engineering) of Noble Systems continue their discussion, sharing their thoughts on the impacts of speech technology for business and the CX. (Missed part 1? Read it now.)
With the growing acceptance of speech tools and AI, what are companies able to do with their IVRs today that can positively impact the customer experience?
Ellwood Neuer: I mean, it’s a combination of almost everything we’ve already talked about. But certainly the biggest change in terms of positively impacting the CX is that ability to start a conversation with, “Thank you for calling Noble Systems, how can I help you?” as opposed to “Thank you for calling Noble Systems, press one for sales, two for service, three for billing.”
You can ask ‘why are you calling me?’, and then just let them tell you exactly the reason why they’re calling in their own words, and apply some form of intelligence to understand their business need. And hopefully you can contain it in the IVR and let them self-serve – and they may not even realize it. They just know they’re getting their question answered quickly.
Or as soon as you realize that you don’t understand what they want and need to get them to a live body, get them to the live body. Don’t make them jump through hoops, just get them to the live body.
Chris Hodges: And make sure that live body has all the pertinent information that the agent needs to solve their problem, sell them the widget, answer the question, etc., without asking the customer to repeat it.
Where does AI fit into the picture? How is AI being used to enhance the customer engagement?
AI is what gives you natural language understanding. It’s taking that fuzzy content and getting the actionable content out of it.
So, when someone opens up with, “Thank you for calling Noble Systems, how can I help you?” and they go on a diatribe of how upset they are, because their widget’s not working, and how difficult it is to try and get service on your web portal, and so on. But ultimately what they want to do is talk to somebody to fix the widget. Having AI look at that and be able to make that decision is invaluable, because that’s what actually gives you actionable content from what the person is speaking, to get them to whatever it is they need to get to, that IVR tree, a real person with all the information, their account information, etc.
And from a big picture standpoint, that’s just going to get smarter, right? So, AI is going to be used in the future to not only recognize what the person is saying, but the person who is saying it, using voiceprints, etc. So that now, not only am I talking about making sure that the content is there to help Ellwood, but it actually is Ellwood, and I don’t need to ask him more questions to authenticate it further, I can just move directly to helping get him the answer to his question.
Maybe Ellwood is calling in and, you recognize that Ellwood is calling. And you know that Ellwood is in an outage area. Instead of just saying “Hello, how can we can help you?”, you can say, “Are you calling about the outage? Thank you for calling in. We’re aware of it. The time to resolution the six hours.” You’ve quickly shown Ellwood that you recognize him and his problem; so he may not be happy about the power being out, but he’s satisfied with his call experience.
Speech analytics is another branch of speech technologies. How can speech analytics be used to improve customer experiences?
So, I think the way speech analytics can be used for customer experiences, is by looking to see what your customers are asking for and how they’re engaging you verbally. And then you can make sure that your IVRs and your agents have the appropriate information to resolve those questions or concerns, or whatever they happen to be calling in about, quickly and accurately, which can improve the experience and also reduce your costs.
Say there’s a specific issue — an error in the last billing cycle that was sent out. All of a sudden, you get this influx of calls into your IVR, and everyone’s calling in because their bills are wrong. Having speech technology automatically route them to the billing department for resolution is one thing. But using speech analytics can help you realize that ‘we just got an influx of calls about billing’, which is a different type of problem that needs to be solved.
If you know that it’s me calling and you know that I just received the bill, you may want to start with, “Are you call it in with your billing issue?” And then you can treat those calls differently, because now your billing department is overwhelmed and they can’t handle all the transactions. So you can quickly add something to the IVR to help resolve the billing issue.
Speech analytics has helped you identify a new issue so that you can put a strategy in place to help handle the volume spike without burying your billing team in an avalanche of angry customers.
And that content can be guided, whether it’s through the IVR or the live agent, and while the consumer is on the line. Speech analytics can be used to drive frequently answered questions and shorten the timeline between the customer asking the question and the agent having the answer available.
If you take it to that one step further, you could also use it to see if they’re using words that indicate that they’re frustrated right now, and feel they’re not being taken care of and having a bad customer experience. So that then you can guide the agent to show more empathy, so that the hopefully the customer experience is improved, as one example.
That can go on both sides. The agent can be using triggering words that cause a poor customer experience or potentially can cause consumer action, so you can also guide the agent to improve the interaction.
How do all of these modern speech technologies impact business productivity?
Well, time is money, and speech technologies can reduce average handle time and potentially speed up resolution of customer issues. Even better is when the consumer can resolve their issue by interacting and being contained in the IVR, and doesn’t have to speak to an agent. The IVR time is a lot less expensive than the agent time.
The IVR can also interact with the systems of record, such as the CRM systems and whatnot, updating information in the customer record. This can help improve marketing efforts and outbound communications to a customer, and potentially even offer up complimentary products or services that the customer may want based on the interactions they’ve had with the AI and the IVR.
Some companies are using speech technologies to transcribe the calls. They can attach the transcription in the CRM as notes. So not only are they keeping the recording, and can gain actionable data from the transcription.
And now you can use data analytics on that transcribed call to do things like you just talked about. What was said on this call? What should we offer this person based off of their account, what their spending habits are? The words in this call appear to have a negative connotation, let me go ahead and offer them additional reward points or some package.
All right, last question. Do you have any interesting speech technology use cases you can share?
We’ve already mentioned a few, such as authenticating callers, providing self-service opportunities, anticipating the caller’s need, and identifying potential trends. Many companies, especially in collections, use speech to help identify non-compliant calls.
Another exciting area is for Automated Scorecards. Most contact centers only have the resources to review a very small percentage of their call volume. So when you start talking about customer satisfaction, how can you really analyze CSAT when you’re only looking at a fraction of the calls? Instead of needing a live QA agent to listen to and score a call recording, you can use speech analytics to score 100% of your calls, and at a much lower cost, to really impact your quality. Management can then quickly see the actionable calls to determine if agents need more training or need access to certain types of content, or if they’re having a specific type of problems in the call center, or with product or services they may be selling.
Companies can also see what’s really happening on calls in near time. Why are all these calls happening? Oh, there’s billing issues or there’s a service issue. Or maybe there’s a problem with the new widget you’re selling, because the knob falls off and children are choking on it. That’s really valuable information that you don’t want to wait until you hear agents talking about it in the break room to find out. Speech technology allows you to get the actionable data to solve those business problems in near time so that you can respond quickly to customer issues.
For Noble, one of our unique speech analytics tools is the Insight Comparative Cloud. The ‘word cloud’ is a common analytics element that gives you insight into what’s happening in your contact center. It shows trending data and targets common keywords so you can identify issues. The Comparative Cloud takes that same information and adds even more value, allowing you to use those word clouds to look at success stories.
How come these calls are a successful sale or a successful collection? Why does this customer’s calls or this agent always have high CSAT, and this agent tends to have a lower score? Noble lets you compare those agents and those different types of calls to see what the successful calls are doing – or not doing – that separates them from the less successful ones. You may find a need for more training or to change the scripting, because when you use these words, they always buy the widget, but when we say these words, they never buy the widget.
And then, once you determine what the best practices really need to be, you can use real time speech analytics to help put guardrails up to keep agents inside the lines, and to course-correct them during the call if they go astray.
The use cases for speech technologies with natural language and AI are growing every day, as more companies incorporate them into their call center software mix and find new ways to apply the tools in their operations. With the wide range of benefits and efficiencies, they create a demonstrable ROI. And the cost of NOT using speech technologies in today’s environment may be higher than ever.
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