Conversation Analytics

UC Today and CallCabinet discuss Next-gen Conversation Analytics

CallCabinet | March 16, 2023

UC Today and CallCabinet discuss their Next-gen Conversation Analytics and how this is Critical for Business Growth

UC Today’s Rob Scott interviews Craig Du Plessis, VP of Analytics at CallCabinet, and discusses the impact Conversation Analytics can have on your organization and your organization’s ability to remain competitive in today’s world.

Read the full transcription below.

Ryan Smith: Hello, I’m Ryan Smith, Technology journalist here at UC Today. Joining me is Craig Du Plessis, the Vice President of Analytics at CallCabinet. Today we’re going to be discussing how CallCabinet’s Conversation Analytics is a critical tool for business growth. Welcome, Craig. How are you doing today?

Craig Du Plessis: Hi Ryan. Thanks very much for the opportunity to be on your channel.

Ryan Smith: It’s great to have you with us. Thank you for taking time out of your busy schedule. I know you’re a very, very busy guy because I’ve spoken to you in the past, so we’ll jump straight on into it. Can you please just give our audience an overview of what Conversational Analytics actually is?

Craig Du Plessis: Yeah. Thank you very much, Ryan. Conversation Analytics, essentially, it comprises a number of different elements that make up the entire solution. So, the first element being speech analytics. We’ve also got voice analytics and then sentiment analysis. So, Conversational Analytics is essentially the combination of all of those and it creates a consolidated type solution, and it’s allowing the client the ability now to actually mine all of their call recordings. It should also be seen as a business tool. Now, if you look at today’s business environment, today’s business environment is incredibly fast-paced, it’s incredibly competitive, and customers are trying to differentiate themselves. And Conversation Analytics allows the client now to have that finger on the pulse of their business at all times. It allows them to be relevant, agile, competitive and allows them to differentiate their business at all times. The couple of areas that we look at from Conversational Analytics is to gather customer intelligence.

So this also from a Conversational Analytics allows the customer now to collect and see exactly what’s happening inside of their business in terms of various areas. So, things like compliance, efficiencies, productivity and so on. Also looking at external to the business, what’s happening externally to the business, but also tapping into the call recordings. So, things like your trends, your competitor insights and so on. The last thing around that is decision-making. It gives the management incredibly powerful tools and factual information to allow them to make faster, more effective decision making. And then the last element that I want to cover in terms of what Conversational Analytics is that we cover 100% of all customer engagements from the beginning to the end, whereas in the traditional environment, you take in a randomized selection of calls.

Ryan Smith: Great stuff. Obviously, you mentioned there that Conversation Analytics is obviously a business tool. Can you just tell us a little bit more about how it is essential when it comes to analyzing and recording data?

Craig Du Plessis: Yeah. Thank you very much, Ryan. That’s actually perfect because when you look at the call recordings that clients currently have today, the call recordings are essentially an untapped repository of recordings sitting there. It’s got this massive amount of customer intelligence built into it. It allows the customers to actually tap in and unlock that business value, and to leverage off those call recordings for a competitive edge area. The key indicator when typically looking at conversational analytics to address your call recordings, is you have to have that tight integration between your call recording platform and your analytics. And that’s crucial because now the amount of data and the amount of information that you pass in between the two systems, essentially, you need the metadata passed through quite tightly. Another element there from a key indicator is your automation. Now, Conversation Analytics allows to take the processes from a reactive type environment to now a proactive process.

In other words, we’re starting to look at automated things like your notifications and your alerts. And all of that is based on predefined thresholds. So, it allows the organization now to be focusing on what’s more important to the business rather than trying to worry about a manual process of monitoring. Another couple of areas in terms of Conversational Analytics in regard to the call recordings, essentially is looking at scalability, looking at the deployment process. It needs to be rapid. It needs to be incredibly fast. The other key points in terms of when you’re starting to look at your call recordings is the volume in terms of today’s engagements, or the calls passing through any contact center are just way too much for any human to try and attempt to do because essentially, it’s way too costly and it’s way too time-consuming for an individual to do it. And that is where a Conversational Analytics tool, an AI tool like Conversational Analytics allows us now to go through 100% of all engagements. We also look at the entire customer journey.

So, Conversational Analytics allows us to now to look at that customer journey and understand what exactly happened on that journey. Was it a good one? What was the last engagement with the client and how did it actually go? Then in terms of score carding, or starting to pull out reports, we now look at consolidated scorecards. So, the consolidated scorecards here essentially is taking all of the customer engagements, and consolidating them into one, whether it be on voice, whether it be on text or whatever the platform may be, and consolidating it into one. So, giving that holistic type view in terms of what that true conversation was. And then understanding in terms of what is the true context of the particular conversation with the customer. In other words, what is the customer truly saying? So, here we monitor for things like emotion and sentiment. Now, these kinds of things you cannot detect or you cannot pick up if you don’t have Conversational Analytics.

And this essentially pulls out and gives you down to an individual agent or individual client, you can actually determine exactly what is happening there. And the last element I just want to cover in terms of this as well is, from the call recordings, you can actually determine your employee. So, your employee experience is absolutely crucial to any business. And the reason being is you want to do that employee management, you want to manage and monitor for employees in terms of burnout and stress. Now we can actually detect from an employee perspective if they’re starting to reach that stress or that burnout level prior to the point of it actually happening because we start to monitor for those things like the emotion and the sentiment. Also from an employee, we start looking at the training. So, here we look at focus training and mentoring, making sure that the individual in that position is correctly aligned and doing what the business requires.

And that’s in terms of their particular function, but also in terms of maybe they need training in terms of a specific function, let’s say conflict resolution or product or service, or whatever the requirement may be. And we get that focus-type training that we can now start applying. Now, if we can reduce any potential employee churn, which is crucial to the organization, there we’re looking at protecting the business’s investment. Now the investment is substantial because here that’s directly linked back into customer satisfaction. So if you’ve got experienced, knowledgeable staff that can actually address the customer immediately and rapidly, that immediately equates back to better customer experience. Thank you, Ryan.

Ryan Smith: Excellent. Obviously, you mentioned there, some use cases for how Conversational Analytics can be deployed within a business. Can you just talk me through how critical of a tool it is for actually influencing success strategies for businesses?

Craig Du Plessis: Yeah. Thank you. So, from a success strategy perspective, here we look at alignment. So, for example, we can create customized reports crucial to conversational analytics. It is those customizable capabilities to create those reports that align directly through to whatever the function is, or whatever that particular management level is. So, depending on their requirement, whether it be strategic or tactical, if they’re looking for trends or patterns or whatever it is, and what is going to make them successful to understand, for example, stocking of a particular item or lack of stock or lack of customer engagement, whatever the case may be, what are the trends, what are the patterns. Under here as well, we can also start looking at what happened with this particular engagement, why did it happen, and what might happen in the future. So, for example, a predictive analytics type sort of approach. And then also from a prescriptive perspective, what should we be doing next? All of these are tightly integrated back into the success strategies and providing, as we said in the beginning there, is you’re providing that factual information for faster and more decisive decisions to be made by management.

Ryan Smith: Obviously, touch on it a little bit before as well in terms of analyzing sentiment and emotion and stuff like that, especially when interacting with customers. So can you just give us a little bit more detail just about how Conversational A nalytics can give organizations better insight into the customer experience that they offer?

Craig Du Plessis: Yeah, sure. Most definitely. So, customer experience is probably one of the most sought-after elements under conversation analytics that we encounter with our customers today. So this essentially gives the business the ability to understand the customer in terms of what are their requirements, what are their desires, their patterns, their trends, the sentiment, all of that sort of stuff. But also what is what was the last experience that the customer had with your organization? Was it a pleasant one? Was it an unpleasant one? Would that customer be an advocate of yours to actually recommend your organization to a fellow colleague or to a friend or family without any concern? So, that’s very, very important from understanding what’s going on there. But also when you start looking at the successful engagement, was that engagement a satisfied customer when they left that particular engagement? And did we actually address the customer’s requirement? Did we have the desired product or the service, which equates back to what we spoke about earlier on in terms of inventory, stocking, and so on? And did we have the desired quantity?

If we didn’t, how do we address that? We need to take corrective actions if it was an unsuccessful engagement. Here, we’re starting to look at, well, it’s a business risk. It’s a major, major business risk to my organization because that customer experience was bad. Maybe we starting to look at elements … and we can identify these with conversational analytics. So, we can identify things like your complaints, your cancellations, potential litigation threats, and market abuse. Any of these elements, we can identify and immediately from there, we can start taking corrective actions. And then the last element when it comes to customer experiences, we look at how we make improvements, and where can we possibly make improvements. So, where can we make improvements, what improvements can be made, and how do we actually indicate or how do we actually take those corrective actions to monitor and take that through to ensure that they are successfully deployed?

Ryan Smith: Excellent. Obviously, I think it’s fair to say that most businesses, if not all businesses, really obviously want to retain customers and grow their customer base. None of them really want to lose customers. And obviously, you mentioned there, Conversation Analytics can allow businesses to improve their experience by delving into it. Just talk me through how it can reduce customer churn and retain customers.

Craig Du Plessis: Yeah. Okay. Brilliant. Nice question, Ryan. Thank you. So, here we look at from a customer churn, we look at three main key areas. So the first one being to identify, then to manage, and then to analyze. So when we look at it from an identification area, so here we look at identifying the potential risk of a cancellation. Now, how do we do this? So, remember, we spoke about 100% of all engagements that we monitor here. So, how we do that is we monitor for specific keywords, key phrases, anything that is going to show a potential cancellation. Whether the customer is actually leaning towards a cancellation but he doesn’t want to say outright, I’m going to cancel … Potentially he’s talking towards it. So, from identification … so, that’s looking at the sentiment, specifically at his words. From a sentiment analysis also, we start looking now as well and tying back to what we spoke about earlier on, in terms of the combination of emotion and sentiment. So, the emotion, we actually do it pretty differently. So, we monitor the emotion, so the acoustics of any conversation.

So, in other words, your pitch, your tone, your cadence of that particular conversation. And we create a score. We then take the sentiment and that runs on the linguistics. In other words, the specific words that are said. And we take those to create scores and we combine those two together to create the true context of that particular conversation. So, you may have a customer saying, well, I’m happy with this particular engagement, but the tone and the pitch actually don’t say exactly that. And you get that true context and that leads back to a possibly dissatisfied customer with a potential cancellation coming up as well. So you can actually preempt the churn and actually take corrective action. When we start looking at the management in terms of churn here, here we looking at monitoring the way or the processes that we follow or the organization follows in terms of their staff. So, is the agent is the agent following the corrective or the correct procedures in terms of handling a potential cancellation.

So, did the agent encourage the client to possibly reconsider? Did the agent possibly offer, for example, elements such as maybe I’m offering you a benefit or a value-add package or a discount or whatever, whatever the case may be, just to try and get them to pull them back in? Now, if none of that happens, or if none of that actually converts the customer back, and changes the customer’s mind to get them back to say, well, actually I’m not going to cancel, then then the last step in that particular process obviously is the escalation through to the retention team. So, now it’s a multi-tiered level in terms of managing that potential churn and reducing the churn. So, we’ve actually seen instances where we’ve actually been able to reduce the churn quite significantly in that area. And then in terms of analyzing … So, the last element in analyzing here, we analyze the calls. So, we analyze them for success, failure, and also from the agents, where they’re struggling. So, from a success successful call, for example, what are the techniques or processes that a successful agent has followed in terms of making sure that they actually close that successful process?

Now, can we take that technique and replicate that process across the rest of the team? And immediately we can actually elevate the entire team to start delivering more in their particular function. From a failure, here we start looking at where did we fail, in what step in the process did we actually fail and why did we fail? Was the agent not assertive enough? Did they struggle to handle the conflict side of things? What exactly was the problem there? And then from that, from the failure side, is to implement corrective actions. So, now we’re implementing corrective actions to say, as I said with a successful side, it’s taking those successful techniques and replicating that across the rest of the team. And then just identifying from an agent level as well, as we spoke about from an employee element earlier on, is what training does the agent require?

Maybe they’re struggling in terms of I don’t understand this particular product or I don’t understand this particular service. Or as I mentioned just now in terms of conflict resolution, maybe they just don’t have that nature to handle a conflict and they need to maybe be allocated or reassigned from in their organization because they’re just in the wrong role. So, maybe they should go to a role where they don’t have to handle that particular element. But essentially, now we’re making sure we’ve got the champions in the right seats to handle that particular churn. And that also leads to better handling and reduction in churn.

Ryan Smith: Great stuff. Obviously, most customer interaction happens through the contact center. As you mentioned there, obviously conversational analytics helps businesses and organizations provide better training for agents and stuff like that. And can you just tell me a little bit more about how the solution increases productivity within the contact center?

Craig Du Plessis: Yeah, most definitely. So productivity … There’s a number of different elements we could cover, but just in the interest of time … so, essentially what we look at there is from an efficiency perspective, the most important thing to a contact center is obviously the silence, the silence in any conversation. So, every single contact center encounters this. But high silence time is considered unproductive time. So, silence time essentially is any time, that dead time, between the agent and the client. So, essentially what we’re looking at there is music on hold, any IVR, or I’ve just put you on hold and I’m asking a colleague for assistance. If we can weed out, if we can minimize that amount of silence time on any particular call, if I can save a customer a minute for every single agent across their contact center, that minute saved immediately goes back into productivity. Now, that productivity also feeds back into savings.

Because from a savings perspective, now we’re saying, well, essentially we’ve got, let’s say, 100 agents, I’ve saved you a minute per agent across those 100 agents. That’s 100 minutes a day that essentially we’ve saved. That could equate back to either more calls being handled or could equate back to a shift allocation where I can actually bring in less heads than what would typically have to do in terms of the normal function. So, this pushes back directly onto the particular function conducted by that particular set of agents. So, whether it be sales or service or collections or whatever their function is, immediately now they can handle more calls, they can do so much more, they can service so many more customers in terms of customer experience. And so, overall it increases your entire productivity. And as I mentioned, there are a lot of other instances that we could look at, from conversational analytics looking for productivity improvements, but that I just wanted to leverage on because I know it touches everybody across the board.

Ryan Smith: Great stuff. Well, Craig, thank you very much for joining me today. As you said, there is plenty more to conversation analytics. And if you wish to find out more about CallCabinet’s Conversation Analytics, then head to where you can find out a lot more about the topic. This is actually part one of two videos on conversational analytics, so make sure you look out for part two. Please don’t forget to like and share this video. We really do appreciate it. I’m Ryan Smith from UC Today. Thanks very much for watching.

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