Welcome to today's Harvard Business Review Analytics Services Webinar using data to elevate customer service. I'm Todd Przan, senior editor for research and special projects. I wanna thank all of you for joining us today, and I want to thank Salesforce and Koveo for making this webinar possible. The customer service experience is a make or break opportunity for any brand. It can solidify a customer relationship or it can do irreparable damage. Executives understand the critical importance. Of their customer service capabilities and the experiences they deliver. In a recent Harvard business review, analytics services survey, of two hundred fifty two global respondents, ninety four percent agreed that the quality of customer service affects an organization's bottom line. In today's webinar, doctor Beth Trachten Bishop, the director of research for Harvard Business Review Analytics will share insights from this survey to help guide on how to solidify customer relationships. We'll also be speaking with customer service experts, Patrick Martin, from Coveo, and Ryan Nichols from Salesforce. They'll talk about the most significant challenges affecting customer service experiences, why the standard for customer service is higher than ever. How organizations are changing their perspective on customer service how to use artificial intelligence as a tool to create optimal customer experiences and how companies can overcome data related challenges to offer consistently satisfying customer service experiences that keep customers loyal and create even greater value. As a reminder, we are live and this is an interactive webinar. So if you have questions or comments at any time, just type your question into the q and a chat box. If you'd prefer that we ask your question anonymously, please let us know that. And if you need help any time, just click on the white question mark help icon. This webinar is being recorded. Patrick Ryan, thank you so much for being with us today, and Beth. Let's start with you to discuss some of the key points from the research. Thank you, Todd, for the introduction. I'd also like to thank Salesforce and Koveo for sponsoring this research project. This was truly a timely and interesting project. Let me start out by sharing a brief summary of the methodology. We fielded the survey in November twenty twenty to. And as Todd had said, we've received two hundred and fifty two completed surveys from members of our HDR audience who are familiar with their organization's customer As you can see on your screen, we have respondents from around the world, a variety of different organizational sizes, functions, industries, and most of our respondents are an executive senior levels of management. So, let me dive in. What did our survey respondents tell us about customer service First, nearly all, ninety four percent agree that the quality of customer service and organization provides impacts its bottom line. And likewise, nine out of ten agree customer service is a critical factor in a customer's decision whether or not to do business with a company. And just over two thirds agree that their organization has made good progress in efforts to improve customer service operations over the past two years. This tells us that quality customer service is top of mind for so many organizations and a key part of their business strategy. So we asked how our respondents see customer service. Do they see it as a lever for business growth or as a cost center? And according to forty three percent of our survey respondents, their organization sees customer service as a lever for business twenty seven percent saying their organization sees it as a cost center, and thirty percent saying equally both. As we had noted in our report, The traditional perception of customer service as a call center is changing. And technology is a key piece of that. Customer service can have its strategic qualities for business growth. All that to be said, the quality of customer service is also changing over time. When we ask to respondents how the quality of customer service has changed in the last two years, six out of ten said that it was better. Only fifteen percent said that it was worse than two years ago, and twenty two percent said it was about the same. Clearly, the majority are seeing this change and that customers' experience is improving for their organization. Since this is an area of potential change, we also asked our respondents what aspects of customer service are needed for improvement? And we found that just over half, fifty two percent of our respondents selected faster response time for customer inquiries. In second place was making service interactions more personalized data driven, as we talk a lot about data today. And tied in third place was improving customer satisfaction with their service inter their service interactions. With making customer service agents workflows more seamless and efficient. These four, speak to our respondents suggesting that customer service needs to be faster, personalized, satisfying, and efficient. And there's definitely a role for data in all of that. Far, I've shared with you the ways that our respondents say customer service could be improved. But what's the goal? Where are they headed? Seven out of ten said the desired outcome was improved customer retention and loyalty to keep customers for as long as they can. Followed by six out of ten saying they're seeking to improve their brand reputation, and a little over half looking to increase their customer value from customer services actions. All of which could positively impact the business over the long haul and lead to positive customer experience. And if improvement is needed. We asked our respondents, well, what areas should your organization be working on? And we found that about two thirds of our respondents selected improved knowledge sharing between customer service and other functions. And six out of ten said, they each select selected, implement more predictive and proactive service, and invest in talent's performance and and performance customer service agents. Over half cited upgrading technology systems that support the customer agents. All in all, those add up to improving knowledge sharing being more predictive, investing in talents, and upgrading technology systems. And there's a rule and data for all of those as well. So maybe you're asking yourself. So the survey respondents have a desired outcome, and the ways they think the customer service should be improved. So what's stopping them? What are those greatest barriers in getting in the way of improving customer service? And the number one answer we found was over from over half of our respondents was day to day work takes precedent over making widespread improvements for customer service teams. Followed by forty four percent saying inefficient or outdated customer service technology, and another forty four percent also saying talent issue. So let's let's stick with technology here for a moment. We asked our respondents about the number of tools that their their customer service agents use to resolve customer inquiries. And we found that seven out of ten of our respondents report their customer service agents use three or more digital tools for resolving customer inquiries. Among them, eleven percent are using seven or more technologies. So that's telling us how many, but what type are they? What our respondents told us is that forty four percent said that they have a mix of different modern and legacy one off applications. And eleven percent are using modern best in class platform of integrated applications. Given all of that, Where are organizations headed from here in the next couple of years? And we asked our respondents what aspects of customer service they're working on over these next one to two years. And sixty two percent said that they are looking to improve customer satisfaction with their service interactions. A little over half are looking to improve investors response times to customer inquiries, and just about half are looking to make their customer service agent workflows more seamless. As we noted in our report, having the right people have the right data at the right time can increase efficiency. Given the changing nature of customer service, the role it can have as a lever for growth and the barriers to overcome. Here's what a respondent say their organizations are focusing on. Eighty eight percent agree that in order to be competitive in their industry, organizations need to embrace data driven personalized customer service. And three fourths agree that their organization needs to be better at tracking revenue generated or lost by customer service. And seventy two percent agree that their organization is committed to investing in improving its customer service. I think those are great points to end this data portion of our session say that almost nine and ten of our organizations need to embrace data driven personalized service or look to embrace data driven personalized service. And that just about three fourths are at organizations that are committed to investing and improving their customers. And with that, I'd like to turn this back to Todd for our panel discussion. Beth, thanks for taking us through the survey data and analysis before we start with our guests, is there anything about the that data that really really stands out for you in in all that research? Thanks, Todd. You know, what I think the thing that really stood out to me most was how many of our respondents said their organization is prioritizing and planning to improve their customer service. In particular, we found that just over a third, thirty five percent of our respondents say, that their organization is currently implementing more automation in their customer services processes, and another third or so said they're planning to do this within the next year. The result leaving about meaning just about three fourths are saying they're implementing more automation now or in the next year. Okay. So Beth, with with so many different types of systems that are that are in use, what what customer service capabilities did the survey respondents say they need in today's marketplace. I'm really glad you asked that. That was a really interesting question and answer in our survey. Or we asked our respondents what advanced technology and data enabled customer service capabilities, their organization has adopted to date. And we found that over a third, thirty seven percent of our respondents said that storing all relevant customer data in one one accessible place. Was what they were doing. I followed by about a quarter who said customer profiles with a single view of the customer is what they have done. Great. Thank you. Ryan Nichols from Salesforce and Patrick Martin from Coveo. Wanna start off with a question for your both and maybe Ryan, maybe you could lead off. But how effective do you think those companies overall are with their their current customer service practices and policies? A GREAT QUESTION, TOD, AND THANK YOU BATH FOR WALKING US THROUGH THAT DATA, BECAUSE I THINK THE DATA IS PRETTY CLEAR It matches what I hear from service leaders in our innovation center here in Salesforce Tower every day. Service organizations are struggling. We're all being asked to do more with less. And Walt's encouraging that things are better than they were two years ago, that was the depth of the pandemic, and the fact that half of all service leaders still say that they're working to improve response time in CSAT, that really is just a baseline of what a great service experiences. And customer expectations are higher than ever. They expect proactive personalized that meets them where they are and helps them achieve success without a whole lot of effort. And that means that service leaders have to not just get the basic response time right. We need to use that as a foundation to do a whole lot better at meeting our customers' expectations. Yeah. And on on my end, just piggyback on what Ryan said. I think for the most part, companies have been mostly efficient in implementing foundational practice and policies. I mean, you know, customer service is There's nothing new. Right? It's been around for a long time, so these foundational practices and policies are pretty well understood by now. So every company will have a variety of channels for customers to communicate with them. Most of them are gonna have self-service channels, were applicable, and they all have a set of operational metrics to measure efficiency and performance SLAs, feedback loops to measure CSAT and all that front. I think we're we're gonna be challenged as an industry, like where Ryan was saying, is to be prepared for for what's coming. Know, as as an industry we're faced with a shift in customer expectations, you know, customers now expect the same type experiences they get on on Netflix, Amazon, Spotify, etcetera. So I I don't think that most companies are are ready to make that shift. And prepare the organizations with the right tools and processes to adapt this to adapt to this change. You know, the customer experience now becomes front and center. So we need to rethink our structures, processes, offers being more customer centric than we've ever Great. Thanks to you both for that. Ryan, question for you, the number one barrier to improving customer service. Is the day to day work of customer service. So what what's the way out of this catch twenty two? Well, the this is where you gotta make the you gotta make the investment in the basics in order to make the improvements. And that does start with the data, not shockingly, even the title, right, of this webinar. I mean, we saw organizations using what? Three tools, seven tools. I met with a retailer whose agents needed twenty tools to help solve customer issues. And that's what causes that additional day to day work that gets in the way of actually making improvements and leading data in your service experience. Solving the the data challenge used to require it used to be very difficult. Right? It used to require moving all your data together into one place, but that's not required anymore. I mean, with with their modern data lake architecture like Salesforce data cloud, you can keep your data right where it is and still use it as part of a great customer experience. But but what do you do with all that data? Right? And I think that's the the the new part of this. Right? Because it used to be all about getting that data in front of human agents, that proverbial single pane of glass. But increasingly, it's really about using that data to ground your prompts for large language models, like what we're doing with Einstein GPT, and then deeply embedding that into your CRM. We're workflow for use with all your integrated applications. And once again, right, that's an investment, bringing your data together, making it available not just to human agents, but also to artificial intelligence and workflow, that's an investment that that removes that barrier. Right? That reduces the day to day work that your agents have to do. And again making resources available for further improvements in the service experience. Really interested to hear, Patrick, your point of view on this one from Verint's perspective. I mean, I totally agree. That's that's exactly, you know, what we're seeing and what we're hearing from our our customers as well. I mean, you know, we we're all about improving the customer experience across the entire journey. And if if you're not if you're not leveraging that data, you know, and then using AI to fuel that customer experience and make it as as frictionless as possible. You're gonna be in a challenging place, especially with how this whole GenAI story is gonna completely shift customer expectations. Patrick, I'm I'm glad that you I'm glad that you you set that up because we we did get a great question from Autumn Lee that I wanna ask you both about gender AI, which is whether you you see it helping to make the customer service more customizable as the as the customers want it to be. Pat, Is that is that your feeling about generative AI? Is that that way you see it working? I think it's gonna play its part. But, you know, what we need to kind of understand around GenI is that it's it's only as good as the information you're gonna feed it. Right? So you have to think about, you know, you know, if you're if you're leveraging these large language to enhance your customer experience, you want to make sure that you have this trust layer or this security layer that you make sure that what is being generated is is accurate. You're able to manage the privacy and the security of your content. But it's definitely gonna take it to another level. I mean, you know, we have further questions in this webinar that we're gonna touch on, but it it to me, it's gonna transform the whole experience. I really think that even support organizations are gonna have to transform the tiered model is gonna be challenged. I think think organizations will have to to transform or migrate to a more collaborative model and and leverage generative AI or at every step of the journey. It can be completely transformational and and drive this this level of personalization and frictionless experiences that customers are gonna effect today. Ryan, I still don't think I'd add. I think it's great great answer, Patrick. I'd I'd have the concept of of effort, right, and kind of bring us back to that because look at the end of the day, what our customers want to achieve is success with the product or service that they're using with as little effort as possible. And I think that that's where a generative AI can really take some of the burden and the effort that used to require agent involvement in order to assemble a an answer to a customer question from multiple different knowledge articles. Well, instead, let's just generate a novel response, right, that combines that's deeply grounded in that knowledge article. It's not hallucination. Right? It's it's grounded in your source of truth. But that can be conveyed with so much less effort than is typically required. So I think when you view it through that lens, it's it's a little different than just look, the customer's prefer to, you know, have a chatty bot. No. They just want the answer to their question, and that's where I think generative AI can have a lot of impact. Yeah. The challenge there will be that I'm sorry. I was just gonna add that the challenge there is that generative AI will need to know when, you know, when it makes sense to transfer this over to to channel, or else you can go on and on and on on the conversation. But, you know, it it should be smart enough to know that, okay, I don't have the answer to this. I don't have the right amount of relevant content to drive this. So let me transfer this. Let me do a smooth handoff to the assisted panels, and take that context, and send it over to the agent so that they can pick up where the actual conversation left off. That's a great point. That's definitely a a much more seamless experience than it might be. Patrick, do you think most companies are still conducting customer service. Do you think they're looking at it as a problem resolution and and maybe not as a not opportunity to improve or to deepen the customer relationship? Totally. You know, service and support have been built on break fix mentality. It's it's in our nature to wanna fix the problem the customer is reaching out to us for. All of our metrics are based on this. Average handle time, medium time to resolve, first contact resolution, etcetera, you know. So everything we do and measure rotates around this concept. But if if we shift our mindset, the outcome based support, it completely changes the experience. So let me share an example of So I'd send the support agent in the software company. And I get a customer that calls in and has an issue trying to get from a to b. So I'm gonna help them get to b. And then what happens, the customer might need help to get to c, so they're gonna call back. You know, some might say that the customer's calling for a completely different reason, different issue. But, you know, really, it's it's the same thing. If the agent who got the initial call would have asked the customer what they're trying to achieve instead of focusing on the problem at hand. They could have prevented the potential callbacks and helping the customer get to see on the initial But let me push this one step further. What if the customer clearly didn't know what they were doing? And to get the desired outcome, it wasn't from a to c that they needed to go, but more from x to y. So if the agent would have understood the out come. They could have quickly just redirected the cut the customer in the right path, avoiding a lot of confusion, frustration, callbacks, etcetera. So we we definitely need to switch this mind shift from break fix to outcome based support and all of the metrics and everything we we measure ourselves against needs to go into that direction as well. I I'd love to ask you both a question. We've got got some great questions coming in, but there there's one that couple people are asking here's here's the way Tau Davidson is asking it asking your view on the the quick the quick chat features that that a lot of websites are adopting. Chat bubbles on on web pages popping up. How do you feel about that? And more importantly, how do customers feel about it? Ryan, maybe start with you. Yeah. It's a it's a great question. It's again, I think we need to view it through our customer's lens. Customers love of having to chat. What they what's key about that though is to have it not be disconnected experience. Right? People and there's no technical reason why a chat experience can't pick up right where a customer is in their experience. We're oftentimes those are embedded in a product or service, right, where so you know exactly where the customer is or on a self-service experience where you can see that they've already they've already been trying to solve this issue on their own. They've been on the self-service page that diagnoses one potential answer, don't have the customer start over. Right? So there's ways of building the customer experience where where chat can be delightful for customers And then when you flip it over to the other side, it's oftentimes somewhat of an intimidating channel, right, for for companies to offer, just because the expectation, right, to have somebody available there is is real. That's also something that you can overcome. Right? Agents especially when trained can handle multiple conversations at a time via chat and still deliver a great customer experience in a few arm agents with with the right set of tools, right, including those from from Coveo, including those from Salesforce, then they could be highly, highly much more so. Right? Then the alternative oftentimes is not, you know, create a case. Right? Oftentimes, the alternative is I'm gonna call in, and that, of course, is the most expensive channel and a very difficult one to deliver a fantastic experience on. So huge fan of all sorts of conversational channels, including in app in app messaging? Yeah. To add to that, you know, we see them more and more often And and the challenge, as Ryan was saying, is you don't want your your customers to have to jump through self-service hoops to get to to get to the assistance they need. So you wanna make sure that it is a unified experience regardless of channel. So if I start with search, and I don't find what what I'm looking for. If I go through the chatbot and you're giving me the exact same experience without taking into consideration what I've done on the search channel, It's the same thing as if you call your phone company or your ISP provider, and they ask you the phone number or your account number to dial it in. And then you get to someone, and they ask you, can I have your account number? Can I have your phone number? I mean, I gave it to you. Right? So you need to make sure that you unify this experience across all nails all the way from self-service even to assisted channels. Your agents shouldn't have to ask the same information that customer gave you through their cell self-service journey, you should have all that insight right up front, and you can really pick up the conversation where it left off. Thanks, great great answers from me both. We have a few more minutes for a couple of other questions, but one one I wanna ask Ryan seventy one percent of the respondents in in the in the survey said that agents are using three or more tools for resolving customer inquiry. So what what are the cost of this kind of swivel chairing? How can how can companies reduce that number? Well, I think we've we've all experienced the cost of it in our own service experiences. Right? As agents struggle with that context switching. Right? If needing to go to a different tool and then not having the context of the conversation or the the information that was available and the other tool. So let's first step to that is the single pane of glass, right, is bringing all those together, figuring out what not just information, but also actions from other systems need to be embedded in a centralized service console, right, in order to prevent that sort of swivel chairing those sort of investments in integration, again, pay for themselves, right, with with agent productivity as well as the ability to deliver a better customer experience. But really, that sort of UX level integration is the starting point, right, that that actually bringing the the data from other systems in to the customer experience as well with a deeper integration is is also really important. Right? That's how you can use the same data from those other applications to do automated triggers and flows as part of the self-service experience as in addition to the agent assisted experience. So don't stop with the single pane of glass. Don't stop with UX level integration. Really think about how you need information from data and workflows from other systems as part of the full customer journey. We've got a couple minutes left. I wanna make sure Beth that we can just go back to the research for a second was anything else that you saw on the data you'd like to highlight? Oh, thanks Todd. Sure, one of the findings I found most interesting was, you know, more than nine out of ten of a respondents, I did you know, how important customer service is, not only for their organization, but for their customer, all the things we're talking about today. But especially when it came to customer, you know, ninety four percent of our respondents agreed that this created a a better or deeper relationship with a customer. Ninety four percent said customer service is a critical factor in ensuring customer satisfaction. Ninety one percent agreed that customer service is critical of ensuring customer loyalty and retention. And all of this speaks to all the things that we're saying today, the long term relationship with the customer throughout the entire customer journey. Thanks, Beth. And Here's a broad question for for both Patrick and Ryan. What do you see coming down the pike? What's in the future of the cost of customer experience in customer service interactions. Patrick, you wanna kick that one off? Sure. And I think we we touched on it just a little Pretty much. And, you know, Jenny, I, as I mentioned a little bit earlier, to me, will really expedite the transformation of their customer service and support. The technology has so much potential to streamline the experience, make it frictionless and on all fronts. Whether it's how to questions, configuration issues, troubleshooting assistance, guided options, document creation, and the list goes on and on and on and on. So, you know, self-service experience will completely be transformed to what we have today around, you know, the siloed channels, because, you know, what Ryan talked about around unifying the experience, think we can all relate to the fact that most of the self-service channels that you interact with today are disconnected. They're not using the same the same documentation or they're not they're not unified. They're not connected. So I I I really think that search and chatbots are great example, these are gonna converge into one experience. So you're not gonna have a search experience and a chatbot experience. You're gonna have one experience that you're gonna put your your intent or your query in, your question, you're gonna have this conversational experience with the search results that you wanna be go further. And all this context needs to be carried over to assistive support if we're not able to do this on on self-service. And and that will mean that, you know, a huge impact on the assisted side of things, because I I personally think that the tiered model will be challenged, and we're going to see more and more organizations migrate to a collaborative and swarming model as we talked about earlier. Yeah. I totally agree with that, Patrick. I I think that the key, though, to realize what unlocks generative AI in a service experience is really that it's back to the topic of this webinar. Right? It's having the right data to ground what's coming out of these large language models. Right? That a lot of times, I talk to service leaders who have in mind kind of the the naive prompt, right, of hey, how what should I say next to this customer? Or what should I how should I respond to this customer? And when you really think about what's required to get the most out of a large language model, you have to do them. A much better job of augmenting that prompt with everything you know about this customer based on a customer who is like this, who's at this stage in their journey. Right? Who's already asked these three questions based on this corpus of knowledge that I think is related to what the customer is asking about now how should I respond? You know, of course, nobody's gonna type that into a a prompt or at a checked GPT style of prompt. So that's where you need help. Right? From your software providers to augment the prompts feeding into large language models to get the most out of them. So I I saw one of the questions. We're not gonna get a chance to get to what can you do today, right, to get ready for this future of generative AI, and it's to to get your customer data and to get your knowledge sources in in to snuff. Right? So that you can use that to get the most out of these large language models. And that's something that I know we'd both be very happy to partner with you on. Yes. Totally agree. Well, sorry to cut you off. Ryan and Patrick, this it's been a great conversation. I wish we had time to continue it because I know we could keep talking about it, but we are out of time for today and I wanna thank all of you for joining us Thank you especially to Patrick Martin from Coveo and Ryan Nichols from Salesforce. Thanks also to Dr. Beth, Track and Bishop from HBR Analytics Services. Our producer at HDR today is Alex Shore, thanks to her and to our partners at On24 and a big thanks to Salesforce and Coveo for making this discussion possible. This concludes our presentation. Have a great day.