Hello, everyone. Thank you for joining us for today's webinar, the total economic impact of NICE Enlighten and Nexidia's solutions. Our presenters are Chris Peterson, consultant from NICE I'm sorry, from Forrester, and Abby Monaco, senior product marketing manager from NICE Nexidia. Today, our session is recorded and you will receive the recording link. The on demand webinars can be found on nice.com/webinar.
At the end of the session, we will have time for q and a. Please submit your questions through the q and a widget. Feel free to check the white papers and research reports in the resource widget. On the right side of your screen, you can see the webinar survey questions. Please answer the questions before the webinar ends.
We appreciate your feedback on the webinar so we know where we can improve. Chris, you can begin.
Thank you. Hello, everybody. My name is Chris Peterson, and I'm a consultant with the Forrester Total Economic Impact Practice. It's a real pleasure to speak with you today about the study Forrester has conducted regarding NICE and LIGHTNEXTEDIA Analytics and Quality Central. Our agenda today will start off with an overview of what total economic impact or PEI study entails.
We'll jump into a summary of the study results from there, then we'll move on to discuss customer journeys, and then we'll dig a little deeper into the study results and close with some time DEI studies, involve a proprietary methodology that was developed by Forrester that goes beyond what traditional total cost of ownership or return on investment analyses do. The benefits and costs are so central to the analysis, but PEI studies also incorporate a discussion of the potential strategic impact of of technology solutions, such as the flexibility gained for future initiatives, as well as consideration of the relevant risks that may impact the costs and benefits of the model. In short, it is a proven, consistent, and repeatable methodology widely used to justify technology investments. PI studies are conducted in a multistep approach starting with due diligence.
We spoke to internal subject matter experts at Forrester as well as internal stakeholders at NICE Nexidia to understand the solution and value proposition from their perspective. From there, we spoke to four current customers that are using the solutions provided by NICE Nexidia. We dig into their journey as a customer and distinguish the differences between their current operations and the state of their operations prior to deploying the NICE and Expedia solutions. We hone in on the benefits they have observed and how we might quantify those benefits. The key takeaway here is that we're not theorizing about the benefits companies could see from NICE and LIGHT and Expedia Analytics and QualityCentral.
We are talking about real customer experiences and the benefits they have actually approved. We create a hypothetical composite organization based on the experiences of the interviewed customers to convey the resulting financial analysis in the case study. All of the information we collected during the interviews is consolidated and reconciled, and we apply those experiences to the composite, which is intended to simplify comparison to organizations considering this solution for their journey. The experience of the composite organization provides a moderate and, in some instances, intentionally conservative approximation of what other organizations might experience. After the model is complete, the case study is written, peer reviewed, client reviewed, and customer reviewed to ensure accuracy, quality, and reach.
A full case study, which can be accessed through this webinar interface, provides context around the customer journey and has lots of quotes and great anecdotes to give you that firsthand account of how this technology and these solutions have made a difference at organizations like yours. Let's move on to some of the results. Based on our analysis of customer feedback and quantified benefit cost, risk and flexibility factors, the composite organization in this study over a three year period accrued an ROI of 268%, 25 and a half million dollars in quantified benefits, and a net present value of $18,600,000. So to understand how these benefits came about, let let's take a look at the customer journey. We interviewed four decision makers at organizations that have deployed these solutions.
The organizations were involved in media and technology, telecommunications, travel resorts, and broadband communications and entertainment. These organizations have call centers ranging from 3,500 agents to 50,000, and the volume of customer interactions was greater than 1,000,000 per month. One of the challenges of running a customer support operation is noted here by the telecom executive. He said, there's a big chunk of unhappy customers who never leave a survey, never tell us, or call us back. Portion of them are really horrible.
They're telling, but how do we find them? This outlook typified to the four state of the other organizations we spoke to as well. They talked about the hassle of dealing with one off manual and decentralized solutions, and finding those coachable interactions was a real challenge as many just selected a tiny fraction of random interactions to review and prepare feedback rates. The other notable challenge of the before state was that it took weeks or months to have any visibility into anomalies or trends that are emerging from customer interactions. As far as pain points, the result of these before state challenges was that the organizations had limited visibility into the performance of call center agents, and the noted lag before product or service issue trends were realized and appropriate actions were taken.
These pain points drove the investment in the NICE Nexidia solutions. Investment goals of the organizations included improving call center agent performance with quality coaching and reducing manual call evaluations. The composite organization that we created based on the interviewed organization is a global business to consumer enterprise with 22,000,000 customers driving 50,000 interactions per day. The customer support team consists of 5,500 call agents, 200 agent managers, and a 10 person analytics team. The composite organization has six quantified benefit categories that we will go into more detail on the following slide.
The largest benefit was an increase in sales from targeted coaching initiatives. There are also large gains in productivity of call agent managers, reduced cost of agent training through a reduction of attrition, and reduced customer churn. Rounding out our benefits were improvements in fraud detection as well as agent productivity. The largest benefit we were able to quantify was a boost to sales from targeted coaching. The travel resort organization explained that with the NICE Nexidia solutions, they were able to gain insights into the frequency of agents suggesting high margin add on services.
Some agents were not mentioning it as frequently as others, but targeted coaching and guidance was provided and resulted in a 25% increase in the mention of these add ons. The closing rate on the calls was 10%, so the call volume at 13,000,000 per year and $16 margin per sale. The three year risk adjusted present value of this benefit was calculated to be $11,600,000 The interviewee at the travel resort told me, as far as the increase of the revenue per reservation, that's not gonna sound as impressive because when you're looking at adding insurance, you're adding $79 to a $5,000 reservation. However, that $79 is huge profit for the company. The next benefit is a reduction of time spent manually evaluating calls due to the auto scoring of interactions provided by NICE and CUDA.
The manual tasks involved prior to deploying these solutions, even at just two to three calls per month per agent, is a huge train of time for call agent managers, and randomly selecting them will typically not result in the most productive feedback. The executive director at the media and technology company noted a 90% reduction in the time spent by managers evaluating calls and preparing feedback. And even more important, that feedback is no longer based on a roll of the dice, randomly selected slice of interactions. It is now based on all interactions by the agent and the NICE Nexidia solutions assist with identifying interactions that could be most impactful to agent performance as well as commendable calls offer praise and reinforcement. The executive director explained, we use it to automate some of the scoring of our behaviors and some of our quality behaviors on our interactions.
So instead of having to manually listen to a call and score calls based on the behaviors we care about, it automatically does that. The main benefit is we now get a predictive survey on all calls, which we can then use to drive better interactions. The 90% reduction in time spent manually evaluating calls results in a $5,100,000 benefit for the composite organization. The next benefit involves attrition. Call center attrition for agents can be high, and the time to get new agents trained up and taking calls is expense.
For the telecommunications firm we spoke to, it was higher than 50% at times. The customer service operations director noted a significant drop after deploying the NICE and CDS solutions. He said, the turnover rate of our representatives has been cut in half or even less than that. In the call center, you get turnover somewhere between 50% and a 100. We are now in the ballpark of 20% or so.
Rep satisfaction is through the roof. He surmised that the improved evaluation process was perceived as fair and more accurate since it was no longer based on two to three random calls per month. Other interviewees talked about how these solutions provided agents with guidance and insights into the customer that empowered them to provide better service to that customer. In other words, it helped them make it helped make their jobs easier and provided tools for them to do their jobs better. For the composite organization, we assumed a reduction in attrition from 50% to 25%.
And with six weeks of training before agents start taking live calls, this results in a substantial reduction in the amount of time training an organization needs for the agents. To control for other factors that might have impacted the reduction in attrition, we attributed only 25% of this benefit to the NICE and Excedia solutions. As I previously mentioned, this is one example where we try to be conservative in the modeling for the composite. This quantification resulted in a 3,300,000 gain for the composite organization. Another beneficial insight gained from the NICE and Expedia solutions was that for the media and technology company, they were able to identify a group of customers at risk of churning.
The executive director explained, we have a churn analysis where we surface up lists of customers that we feel could churn. We don't outbound them or give a new package, but we reach out to them and we'll make sure that they're happy. We do see a lower churn rate when we leverage NICE Nexidia. They observed a 14% improvement in the customer churn rate for these subscribers compared to the control group. And with an estimated lifetime value of $1,000 per customer, this benefit was calculated to be $5,000,000 for the composite organization.
The broadband communications and entertainment company noted also that the NICE and Expedia solutions help them identify potential attempts at fraudulent activities through the phonetic recognition capabilities of the NICE Nexidia solutions. The interviewee explained, we recover a few $100,000 a year in fraud where people are posing as customers or posing as agents, and we're able to detect that with our solution and prevent it. That was a side bonus. We didn't know that we were gonna be using it that way. This benefit was estimated to be $200,000 per year for the composite for a three year risk adjusted present value of nearly $423,000.
Finally, the interviewee from the travel resort company noted that several times per year, an event or issue comes up that will drive 50 to 75,000 calls that take a minute or less each but could have been more efficiently handled through other means. The insights gained from NICE and Expedia allowed them to identify these emerging issues earlier than they would have otherwise and avoid a significant amount of handle time for their call agents over four thousand hours per year for nearly two FTEs resulting in a benefit for the composite organization of more than $93,000. In addition to the quantified benefits we just discussed, the interviewee also discussed additional benefits that were not quantified in the study, but nevertheless, still impactful to the organization. The interviewees talked about how the NICE and Excedia solutions provided an enhanced customer experience resulting in improved customer satisfaction. As I previously mentioned in regard to the reduced attrition, agents are provided more insights and guidance as to how to most effectively interact with that person on the other end of the interaction.
The telecommunications firm had undergone a culture journey in which agents were connected with more customers in their region or locality, and the tools and guidance they got from the NICE and Excedia solutions advanced this journey to a great extent. The customer service operations director explained, our representatives truly feel they own their customers and their business owners, that they drive it. Nexidia solutions really help everyone understand what customers are talking about or what their pain points are. NICE Nexidia also serves as a partner to organizations that take on the transformation that is enabled with their solutions. They offer guidance and assistance in implementing the kind of programs we have discussed today.
The broadband firm noted that NICE Nexidia provided burst capacity and support for big initiatives. And when asked about this assistance from NICE Nexidia, the travel resort manager commented, they were absolutely phenomenal. NICE Nexidia was smart enough to assign people that were enthusiasts and resort visitors. They came in and brought up things that we hadn't even thought of. We still pick up the phone today and call them, and they'll help us think it through so that we can figure out what to do next.
That's one of the things that they're really, really good at. For the use cases discussed here for the composite organization, NICE Nexidia provided a quote of $40 per agent per month. For the composite with 5,500 agents, the cost of the NICE Nexidia solutions over the three year period was $6,900,000,000. The license cost represents the vast majority of the investment associated with the benefits we've discussed, while a small amount was related to some internal training and optimization of the solution. An hour each for the 200 managers and a couple weeks for the 10 person analytics team to learn about the various features and options and optimize the deployment in their call centers.
It should be noted that these costs will vary across organizations due to variations in the deployment configuration as well as the complexity of the implementation. Some other relevant facets of the study dimension are the flexibility and risk factors. In terms of flexibility, the data that is captured from interactions by the NICE Nexidia solutions can be leveraged in other areas of the enterprise and promote cross functional collaboration. For the travel resort, the marketing, public relations, and even restaurant teams took an interest in feedback and potential insights regarding promotions, events, and even new menu items. For the telecom, it was the ability to examine pain points across thousands of calls that could be leveraged by the engineering department to facilitate product improvements.
The media and technology firm tied the interaction insights to operational data and pushed it out to their business intelligence layer to drive operational improvement. Risks are also factored into the quantification of benefits and costs to account for ways in which deployments and results might vary across organizations. In addition to moderate and conservative assumptions for variables in the calculation. Discounting benefits and inflating costs is another way in which the study could be considered intentionally conservative. Impact risks cover the possibility of organizations experiencing benefits lower than the composite organization.
For this study, these factors included industry and customer factors that affect the achievability of selling add on products and services, the frequency and structure of agent coaching programs, factors that affect attrition for particular call center, business model and recurring customer factors that may impact churn, and the prevalence of fraud for a given industry. Implementation risks cover the possibility that the investment in NICE and Expedia solutions deviates from the expected requirements, resulting in costs higher than the composite organization. The nature of the NICE and Expedia solution configuration, including the particular components deployed, the complexity of implementation, and the composition of the analytics and call center teams are all relevant considerations. In summary, these benefits accrued by the composite organization compared with the incurred costs generate a three year ROI of 268% and a net present value of $18,600,000 And with that, we can start turning to questions. Before we do that, I just wanna encourage you to to download the study and and take a look at the the full TEI study itself.
The the full study goes into all the detail of the calculations and provides a framework in which you could estimate total economic impact of these NICE Expedia solutions on your organization. That being said, we now have some time for questions.
Hi, Chris, and hi, the to the audience. This is Abby Monaco, the senior product marketing manager with NICE Nexidia. I've I've been sitting quietly because I feel like Chris had some really great some really great things to present, and and I didn't wanna interrupt him. So, Chris, I have a a quick question for you. You had mentioned across the composites, one of the ones was the savings and the training, and you had mentioned a team of 10 analysts.
Do you remember across the various companies that you interviewed, what what did their analyst teams look like? Like, what how big were they? How many were there? Was it disparate, some somewhat the same? What did that look like?
Yeah. Well, so 10 was on the lower end. I believe a couple of them had teams closer to 50 analysts. So this model is is actually quite conservative when it comes to that.
Yeah. So okay. So you were talking about 10 analysts. So I guess if you applied that if you took that same number and said times five, that's a pretty substantial number. That's fantastic.
Absolutely.
Okay. So, Allison has a question. What was the tool used to prevent fraud? Was it Nexidia speech analytics or a different tool?
I believe that from my understanding, that was, they were able to look at some of the speech patterns and phonetic recognition as well as particular phrases that they were able to to identify that indicated that this person was not who they said they were.
Interesting. Okay. So, Allison, on on my end, I can also tell you we have a, this is what was so interesting about this study is that we the fraud prevention was a complete, what would you say? Nobody expected that one. It was really cool that it came out in the study.
But we actually do have a really great tool for fraud prevention. It's NICE Enlighten for fraud prevention. And what it does is it uses several things. So Nexmedia can do, I guess, some certain things in the patterns of the speech. But this can use AI, and it will figure out It uses both AI and voice biometrics.
So it'll figure out, number one, if the same voice has called in under a different name, and that's an indicator, and it'll flag it. And then the other is that it the AI behind the Nexidia and the analytics can do its job trying to identify strange behavior. People who are trying to get around the questions and not able to like, if you can't answer, you know, that first security question, you're already a red flag. And then if you can't answer the second one or the third one and then you try to convince the agent, oh, you know, just let me through, that's likely a fraudster. So the AI will flag that and identify it.
So nice and lightened for fraud prevention is a thing. Look into it. It's really cool. Alright. So the we have another question.
Did the solution allow for a reduction in analysts?
We didn't hear that from any of the customers that we spoke to. They were all able to use their their current analyst staff or team to to really maximize the benefits they got out of out of the solution.
Yeah. And I can second that. So that was your experience in in doing the report. What we've experienced is all of these incredible time savings and efficiency improvements, all of those things, they what what they're doing is they're making the people's jobs better. So it's not reducing headcount.
It's actually making headcount more valuable using their time in much more valuable ways instead of having to search in a manual way for, something valuable.
Yeah. And and and just to add to that, I think what we heard was that this sort of the sense of empowerment that they were just trying to keep up with with the current workload, and and this enabled them to start to consider and examine other things that they were never able to get to before. And so it challenged employees in a way that that was good, that was that enriched their jobs and and and and work experience.
Absolutely. And something else that I can attest to as well is one of the really neat things about these solutions that we've really you know, we're trying to help businesses, but we're also trying to help everybody's, you know, general lives. You know, you don't manual work in general is a pain. Nobody wants to do that. But what's really neat is the employees the agents that are taking calls all day long have responded so positively to this because we've been able to reduce not only the amount of time that these managers are shifting through calls trying to find the coachable moment for an agent.
We've actually, you know, used analytics and used enlightened AI to to pinpoint exactly where an agent needs to improve in a way that they agree. They you know? And so there's this this uplift from all of the agents are just like, gosh. You know? The organization sees me.
The organization can show the way so that I can even get better at my job. I'm no longer sitting around, you know, knowing how broken the system is. The system's working. That's
been
a really quite honestly, it's been a really fun kind of a a feedback to be getting.
Yeah. I I think we touched I touched upon that with the the improved customer satisfaction and the reduced attrition, but it it's a it's this loop that that reinforces and then strengthens the organization as a whole. Agents feel that they're treated more fair. They get commended for positive performance, and they're guided exactly how to deal with that that particular person on the line. That makes the customer experience better, and it's more rewarding for the agent.
And I think it it's a really positive, loop here that that is enabled.
Absolutely. So alright. I don't see any more questions, and I wanna remind you that you can get the study. We have several links to several resources that are available on your console. So go ahead and check those out.
And I think we're gonna go ahead and wrap it up. So, really, thank you everyone for joining us today. The recording
will