Today we’re going to talk about using speech analytics data to enable better B2B marketing and a better customer experience.
To help me discuss this topic, I’d like to welcome Eric Williamson, Chief Marketing Officer at CallMiner.
About Eric Williamson
As CallMiner’s Chief Marketing Officer, Eric oversees all global marketing functions from brand and events to demand generation. Eric’s marketing team works very closely with channel and sales to drive pipeline and CallMiner’s explosive growth. Eric has over 20 years of experience in both technology and consumer products marketing from both the vendor and agency side. Before joining CallMiner, Eric was VP Brand & Digital Marketing at Acquia — an open DXP platform built around Drupal — where he led brand, creative services, webops, editorial, and demand generation. Prior to Acquia, Eric was on the agency side of marketing working as SVP Digital & Social at MullenLowe, and before that as VP Digital Strategy at The Martin Agency. During his career Eric has worked with a variety of B2C and B2B brands including Google, Microsoft, Intel, GEICO, Walmart, P&G, Pizza Hut, Acura, Royal Caribbean, and Hyatt. He earned his undergraduate degree from Texas A&M University and an MBA from The University of Texas at Dallas.
Resources
CallMiner website: https://www.callminer.com
The B2B Agility podcast website: https://www.b2bagility.com
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B2B Agility with Greg Kihlström is produced by Missing Link—a Latina-owned strategy-driven, creatively fueled production co-op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. https://www.missinglink.company
Transcript
Note: This was AI-generated and only lightly edited
Greg Kihlstrom:
Today, we’re going to talk about using conversation intelligence data to enable better B2B marketing and a better customer experience. To help me discuss this topic, I’d like to welcome Eric Williamson, Chief Marketing Officer at CallMiner. Eric, welcome to the show. Hi, Greg. Hey, thanks for having me on. Yeah, looking forward to talking about this with you. Why don’t we get started with you giving a little background on yourself and your role at CallMiner.
Eric Williamson: Sure thing. So as you said in the intro, my name is Eric Williamson, and I’m the Chief Marketing Officer at a company called CallMiner. CallMiner is the leader in conversation intelligence, which I think we’re going to spend some time talking about today. In terms of my role there as Chief Marketing Officer, I oversee our global marketing team. And that spans everything from brand to demand gen to events, as well as product marketing, and the BDR team.
Greg Kihlstrom: Great, great. So yeah, let’s dive in here. And we’re going to start by talking about what marketers can learn from conversation intelligence data. So first, just to define terms and make sure everybody’s on the same page here. What exactly is conversation intelligence? And what kind of data is collected from this?
Eric Williamson: Certainly. So I think a lot of your audiences is enterprise level organizations. So most of these companies have a variety of different ways that they’re interacting with their customers, or if you’re in health care, your patients. So everything from, you know, voice people calling into large customer service centers or contact centers to text and chats, whether it be the website or some sort of support chat, but hundreds of different ways that they’re interacting, even surveys that they do in post call, things like that. So all of that data is out there and available. But what typically happens is an organization, you know, marketers especially are generally just relying on surveys quite a bit for a lot of their insights and the things that help them measure customer experience. Whereas you’re missing a vast majority of unsolicited data from all those interactions. So conversation intelligence, like our platform, ingests and then uses artificial intelligence and machine learning to analyze 100% of all those interactions, all those different forms that I talked about. And it analyzes all that to provide real-time guidance to a customer service agent. And then the bigger proposition is if you think about all those interactions and the data and the valuable insights that are there, it’s able to find those root causes and those insights and level those up to, let’s say, a CMO or a chief product officer or somebody in operations. And these insights help them improve their business.
Greg Kihlstrom: Yeah, and to build on that, could you give us an example or two maybe of some of the insights that that can be gained? You know, what are these? What is this data kind of leveling up to those those leaders?
Eric Williamson: Sure. So thinking above the customer service agent, because I think we’re going to talk about that a little bit. But if you think about the insights that might be valuable to a chief product officer, so several of our customers, if you think about this, you know, what’s the what’s one of the main reasons you’re calling into customer service? It’s because the product or service something’s wrong with it. They need support. And so if you’re able to analyze 100% of all those interactions at scale, you’re going to get a much better trove of insights that will be valuable to the product team to optimize their product or service. You’re going to get a lot of valuable information based on those interactions that could lead to product development. So that’s just an example from a product experience standpoint, that a lot of our enterprise level customers are using those insights to improve their business.
Greg Kihlstrom: And then what about those those customer service agents, you know, what kind of insights are they able to do that that might improve their work and the results from their work?
Eric Williamson: Sure. So yeah, in a in a large contact center, or a customer service center, there’s a couple different layers there, the the agents themselves, who, you know, in this case, if you’ve got a platform, like ours, that is analyzing in real time all of the, let’s say it’s a call, all the conversations, and it’s, you know, giving guidance back in real time, it’s allowing that agent to do a better job because it’s tapping into, let’s say, the knowledge base. So as these questions are coming up, or the conversation is going on, It’s spitting back out the appropriate product information, answers, guidance on how to solve the problem, which is key for the customer service agent. A level above that in the customer service centers, you’ve got business analysts or analysts in general that are analyzing some percentage of the calls, and they’re able to, I guess, better assess at a larger scale some of the agent performance. give them guidance. So part of our platform is a product called Coach, and it’s literally what it sounds like. It provides the ability by analyzing all those interactions, it provides the ability for those analysts and the contact center leaders to provide coaching back to the agents so that they can do their jobs better. Beyond that, some of the fundamentals of contact center is compliance. So you’ve got a lot of heavily regulated industries like banking or health care, where compliance is really, really critical. And so it helps to track a lot of that compliance as well.
Greg Kihlstrom: Yeah. And so taking a step back then to marketing strategy and, you know, those CMOs out there know, knowing that they have access to this conversation intelligence and, and the insights available, you know, what, what does this enable marketers to do that they might not have previously been able to do, you know, knowing they have these data and insights capabilities? Sure.
Eric Williamson: Uh, well, I think the first one would be. And knowing that that’s available, a lot of enterprise level organizations, in fact, we do an annual survey of CX professionals and customer service professionals across the globe, and only 50% of enterprise level organizations are actually tapping into this unsolicited data. A lot of it is just mostly still survey-based. So first and foremost, knowing that exists. If you’ve got multiple large contact centers, that data is there and you may not be tapping into it. Once you have begun to tap into it, then it’s just organizational. Let’s make sure you have those connections with the CXO or the contact center leaders who can give you access to this information. Once you’ve got that project going, then I think there’s a variety of different things. Just thinking right off the bat, a lot of large, you know, a lot of large marketing organizations for like an enterprise level company, they’re largely using survey based efforts in order to find the insights that are going to drive future product development, future marketing campaigns. You’ve got a treasure trove of information just coming from a lot of the interactions that are already happening. So you could be tapping into that just to inform what sort of marketing and messaging you should be doing. Beyond that, once you’ve launched these campaigns, there’s a ton of insight you can gain from hearing the interactions that are happening or analyzing those and seeing the insights. For example, a lot of enterprise-level organizations might have direct-to-consumer or direct-response type campaigns out there. These are perfect for the types of one and done, you know, was this a successful transaction or not, that can be analyzed at scale using conversation intelligence. Beyond that, you look at things like brand sentiment, which, you know, generally a large marketing organization for enterprise is going to be using some sort of semi-annual brand survey, or they’re going to be using NPS or CSAT or something like that. That is great, but that’s survey-based. So you’re missing out on a ton of additional data that can give you true insight into what your true brand sentiment or the emotion and sentiment of your customer base is. And then I think lastly, when you think about just campaign effectiveness. We talked about the direct response, but you can also look through all the interactions and analyze through to find out if your message is resonating, if people are saying some of the same phrases and terms back. And it gives you a better, deeper understanding of whether the message that you’ve been putting out into the market, whether it’s TV ads and some of the things that are harder to track, are actually starting to make an impact with your consumer.
Greg Kihlstrom: Yeah. And I want to follow up on One thing that you brought up early on after I asked that last question, because I think for those that maybe are not as familiar working with, let’s say, Fortune 100, Fortune 500, it might seem like, okay, well, these CMOs, they have access to all these tools and this data. But I want to follow up on what you were saying about a lot of times the stuff is there, but not known. And again, it’s, I’ve been there, and experience that, that very thing of, you know, there’s a wealth of information. It’s just, you know, it’s, it’s inaccessible, for one reason or the other, you know, sometimes it’s technical issues. But you know, just, I guess the question for you would be, you know, a CMO sitting out there, you know, what would your advice be to them? You know, they’re, they’re, they might not have everything that they want, everything that you mentioned, perhaps, but there’s probably some of this stuff sitting out there, you know, what would your advice be to them to, you know, what’s a question that they should ask? And should it be to their customer service team, or, you know, to get a little more of these insights, even if they’re not all the way there? Sure.
Eric Williamson: Well, uh, and as I mentioned earlier, you know, at least half of the organizations that are in our annual report, a lot of it is what we found from, from that, uh, research. A lot of it is organizational silos that is causing the problem. Um, another factor in this is, Many times, CX spans multiple departments. So you may be lucky enough to have a CXO, but a lot of times, CX lives a little bit in marketing, a little bit in customer support. So it spans it, which makes it organizationally difficult. But let’s just step back and say, all right, you never even knew this data was available, but you know you have five customer service centers, and then you work with two different BPOs for handling all of your customer interactions. How can you start tapping into this? I think the first thing to do would be to make a connection with some of those department leaders. Or if you’re looking for your peer levels, you know, customer service centers may roll up underneath customer support or sometimes operations. So make a connection with your peer. And instead of trying to boil the ocean, focus on a couple easier, smaller projects to start some of the things, some of the solutions we’ve talked about today, and start with that and get a couple of few quick wins where you’re tapping into that data as opposed to just survey-based data. And I think then you can grow from that as opposed to trying to do all of the things we’ve been talking about.
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Eric Williamson: Sure. And I think you sort of mentioned it, but both to be clear, both post, but Santa of a call, both post interaction, or both post call analysis, and then, you know, conversation intelligence, analyzing this is important, but also the real time aspect of it. I think where the real time aspect of it ultimately improves customer experience is because it’s improving the agents, customer service agents ability to do their job and solve problems. So you know, we talked a little bit about it, but When when a company is using our platform or another platform that has real time agent guidance, it’s giving it’s it’s listening to transcribing and analyzing all that at those interactions in real time and being able to provide back the tools needed for an agent to actually solve problems and do their job and which is going to benefit the customer and their happiness with the outcome of that call. For example, beyond that, from a coaching standpoint, What happens in most big customer service centers is the analysts are really only sort of spot checking in a manual way two to three or 4% of the interactions that are happening and looking for compliance, quality assurance type situations. when they could be tapping into 100% of that pool and being able to analyze that at scale. So just the sheer volume of interactions you’re able to access and use as insights that then make the agent’s job better and their experience better improves customer experience.
Greg Kihlstrom: Yeah. And so, you had touched on the idea of, or the challenge of data silos and everything, but obviously the opportunity to connect not only the data channels, but the marketing and communication and CX channels is tremendous here. So, how can conversation intelligence be combined with other, you know, multi-channel analytics to create that, you know, that North Star of the omni-channel customer experience?
Eric Williamson: Sure. So, depending on which customers, we have customers that have a variety of different ways that they are combining all this data together. First and foremost, when we think about conversation intelligence and, you know, our platform, et cetera, it is omni-channel. So, it’s able to ingest pretty much any type of interaction a large enterprise organization, typically, they’re probably already well into some sort of digital transformation effort, which means they either have a large data lake where they’re pulling all this stuff in together, or they have a daily CDP, that’s helping provide a rounded view of the customer. So integrating a platform like ours, that’s doing a lot of that analytics, The ideal scenario is that by pooling all this information together and all this data together, you’re able to map out this beautiful customer journey. But what’s missing a lot of times from that is the actual context and emotion, the sentiment that happened in each one of those interactions. You may have had a really amazing chat with the chat bot, but then when you talk to the agent, they didn’t know any information. things went downhill. So a platform like ours helps provide more of that meeting and context to each of those touch points, which can then be ported into whatever, you know, massive data lake or a CDP, your main CRM, whether that be Salesforce or whatever, that can help be the central point, but you have to have something that’s providing that meeting.
Greg Kihlstrom: Yeah. So last topic I wanted to talk about is based on a trend in B2B marketing, I’ve been seeing for years, and I’m sure you and those listening are seeing it too. And that’s a move towards co-opting more approaches in B2B from the B2C marketing world. And after all, B2B marketers and B2B buyers are consumers, at least when they get off work. And so there can be and is a lot of crossover in the thinking and approaches. So I wanna talk a little bit about what B2B brands can learn from B2C marketers. So, you know, what are the top one or two trends that you’re seeing in B2B marketing that maybe originated in B2C, but are becoming more popular in the B2B world as well?
Eric Williamson: Sure. I mean, I spent, you know, good half of my career on the B2C side, actually. So it’s a good observation. And I do think that B2B marketing can learn quite a bit from B2C. First and foremost, I do think that on the consumer side, large marketing organizations, whether they are client side or on the ad agencies, they generally, they build their career learning a lot of the fundamentals of brand in a much better way than I think most B2B, especially B2B tech does. And that could just be the nature of how marketing evolves as the company grows. But I think one of the biggest things would be the increasing importance that I’m seeing in brand and not just, not talking about, you know, the visual identity, although I do think that B2B tech in particular is, is starting to get better at this part of the overall brand identity, but more, more specifically being very, very clear about what your, what your unique point of view and positioning is, and being able to articulate that using a lot of the same brand fundamentals that I think B2C brands are much better at. So what I’ve seen in B2B is that it becomes a lot more formulaic. They think of it, the marketing, it’s an engine that’s delivering pipeline for sales, for example. And the value of brand in the past has, I think, been forgotten or missed quite a bit from some of the CEO or some of the CFO who’s delivering the budget availability for marketers. I do see that improving quite a bit in B2B, but I think there’s a lot more work to do. And I think you’re missing a huge opportunity. It’s very hard to… connect that to ROI sometimes. But I think it’s a huge opportunity missed if you’re not building a strong brand.
Greg Kihlstrom: Yeah, yeah. And is there anything I know that’s something that that a lot of B2B brands still need to, to adopt more of? Is there anything maybe a little further out that it might not even be on on many B2B marketers radars, but still that they should start paying attention to?
Eric Williamson: Obviously, from a tactical standpoint, I think any B2C or B2B marketing marketer should be, if you’re not already, you should be figuring out how to integrate gen AI into your work and process with your teams. For example, from a B2B standpoint, the marketing team, one big part of our remit is that we are enabling sales and customer success with all the materials and information and taking complicated technology type situations and providing the right positioning and messaging around that. And it’s a constant battle to try and enable the field. Essentially, you’ve got tons and tons of inventory of existing materials, but inevitably the Slack channel is like, hey, do we have one of these? And you’re like, yes, we have 5,000 of those. So one of the things is leveraging Gen AI to create some sort of help bot that’s able to, they can prompt it, ask questions, and it’s not able to just go retrieve it, but it provides them a summary using your own inventory of all the assets your team has worked so hard to create to provide summaries. And then there’s the link. So tapping into things like that, or even at a much, much smaller scale, our content team, for example, The hardest part of writing a great blog post or white paper is the blank page. So it’s a pretty great way to get the ball rolling in terms of the writing process. Have it write a V1 and then you can take it and it either inspired you and you can build on that or at the very least it got things going and you can go through and massively edit it, which you absolutely should. Don’t ever just use chat GPT alone, please. But so those are some of the tactical things that I would recommend. The only other thing I would say is your team and your marketing tech stack, you’ve probably been around using AI through a lot of the software you already use anyway. So talk to those vendors and ask them how Gen AI is integrated in with the solution that you’re already using and ask them for some advice too, as opposed to taking it all upon yourself.
Greg Kihlstrom: That’s great. Well, Eric, thanks so much for joining the show. One last question before we wrap up. You’ve given a lot of great insights and advice already. What’s the next best action you recommend for B2B brands to stay agile?
Eric Williamson: Um, I think don’t forget about, we talked about the importance of brand and, uh, I think, you know, a key part of that, that gets missed in B2B. I think we, we, whether it’s you’re a tech company or whatever, you tend to get sort of feature function and a lot of your messaging. And I think that misses a really vital part of, of don’t forget about emotion. Uh, whether you’re a B2B brand or a B2C brand, there’s still a human that’s, that’s looking at your ads, that is engaging with your salespeople that are using your messaging. So look to in your headlines and some of the key differentiating points, look to evoke emotion, whether that is tapping into a known pain point, or you know that there’s a particular need. So those are the types of things that solve problems and those evoke emotions. So I think don’t ignore that part.
