Ned Hayes [00:00:01] Welcome to SparkPlug, where we talk to smart people working at the intersection of business and technology. Brought to you by SnowShoe, your smarter loyalty leader. Today, Spark Plug is happy to welcome Mariam Reza to the podcast. Mariam is a senior vice president of Enterprise Solutions at LivePerson and LivePerson makes life easier for people and brands everywhere through trusted, conversational A.I. so Mariam is an expert in cross-functional collaboration, customer retention and customer success management. She holds a diploma of customer contact leadership from Customer Contact Solutions, and we are really happy to host her today. Welcome, Mariam.

Mariam Reza [00:00:41] Thank you. It’s so good to be here, Ned and Ashley. Looking forward to our conversation. 

Ashley Coates [00:00:47] We are as well. Thanks so much. Will you start off Mariam, by telling us a little bit more about yourself, possibly both about your personal background and professional background? 

Mariam Reza [00:00:57] I actually started in information systems, that’s what I ended up doing my university in. Technology was the space I was going to get into back in the day, back in the 90s, that was the place to be. But funnily enough, as I started my work journey, it ended up being in sales initially and very quickly to selling on behalf of organizations and running those teams via their contact centers. Right. So ran quite a few of those in my early years then decided we’re going to start a company. You know, why not young and make great decisions like that in your early 20s? We built a company and we found this amazing organization called LivePerson, and this is when I was out in Australia at the time, actually, we found out about LivePerson offering this amazing live chat technology out in the U.S. to major brands and we really wanted to bring that digital engagement to the Asia Pacific market, and that’s where my journey with this innovative company began back in 2009. Ever since then, of course, LivePerson acquired the company we founded, and here we are years later, but completely in new spaces, and I’d love to share a little bit more about what that means in the whole life person trajectory over the years. 

Ashley Coates [00:02:19] Yes, we would actually love to hear more about the history of the company and your mission at life sentence, so please. 

Mariam Reza [00:02:26] Sure. It’s best said by Rob Locascio, our founder. He’s got a fantastic background and life person in an effort to solve the fact that he could not get help online, right, at the time when dot com was new. The whole idea of websites were fairly new just could not get help. You’d have to pick up the phone or go into a store, you know, as and when you were buying. There was no one to chat to or just to have a conversation with them. What he did see in the mid 2010s or around 2014-15 is that people are moving into these other channels. They’re no longer just web centric, right, you’re not just going to the website to buy. I think all of us, as consumers were starting to do that right, we had mobile phones that were enabling browsing anywhere from anywhere at all and then slowly messaging just caught fire. Right, the fact that we were now texting with everyone but not businesses at that time just created this space for us to say that today enterprises or businesses have a website presence or a store presence and you can get live chat, but you still have to call to get any help or walk into a store. But they’re communicating on messaging channels like iMessages or WhatsApp. So we really wanted to enable these conversations between brands and consumers in these channels. And that’s where we made a massive pivot around the 2016 mark with our first customer at the time, T-Mobile, who took that leap of faith where we ourselves knew and said that chat is just going to service only a small percentage of your customers. You really need to be where all of them are, and that’s literally where we are with our friends and family in text messages, that feels like centuries ago. Today you can have a conversation on any of these channels all the way from, like I said, iMessages, which is Apple’s, Apple business chat to Google business messaging, WhatsApp, of course, Facebook, the website still, of course, the difference being it’s no longer this synchronous session. You know where as soon as you stop having the conversation, it disappears and you have to reengage. It’s continuous. That’s the whole idea of messaging, right? When you look at any of your WhatsApp threads or messaging threads, you can scroll far enough to know where they started. 

Ned Hayes [00:04:48] So one of the key changes in the technology is that people have moved away from bots to actually making customer service people smarter. So being able to give them real time insights  rather than just providing a chat bot that has a limited set of functions. So can you speak further about that shift in the industry? 

Mariam Reza [00:05:07] Absolutely. Making your people smarter, using technology to make people smarter. I think that has been one of the key focuses for us where we are in a conversation, as agents are solving or resolving these customer questions, they’re getting information fed to them from the wide sets of data that already exist. So having technology that actually detects what is happening in the conversation to then give you whether it’s predefined content or information that can enrich that conversation even faster is something that we invest a lot on. In fact Ned, what we can do, which is really unique there is you could actually have a bot take over parts of a conversation. Now you’re not only making that agent more intelligent in servicing, but faster, and the customer is always getting a very consistent experience. You take an example of, Hey, I really need to check on this order. I’ve called several times I can’t find it. A bot can actually take over. Give me your order status. Let me look that up. Give you a full breakdown of where it is in terms of the tracking and the agent is there overseeing the conversation, but does not have to step in. That consumer is getting this consistent experience every single time, as opposed to an experience dependent on a human’s level of competency or knowledge or experience. So using AI in that way, where you can provide these very consistent, trusted experiences actually makes the human look better as well. They’re utilizing the AI in a way to just always provide the right information or have the AI take care of all the repeatable tasks while they can take care of really more complex scenarios. 

Ashley Coates [00:06:51] So can you tell us more about your AI chat feature technology? What is meant by conversational AI and how is that different from another kind of chat technology? 

Mariam Reza [00:07:03] So chat with AI or bots have been around for a long time, and there’s a reason why maybe a decade ago they really did not get traction. It’s because us as consumers of that technology, it takes a few bad experiences, maybe a handful of bad experiences for us to completely disregard bad bots really trying to give us answers. But just breaking the idea is building an AI that one understands you very effectively and to knows what they can handle, and three knows where to send the conversation if they can. Is a lot more to think about when we’re building these AI. With LivePerson’s conversational AI, the idea behind it is, our goal being making the conversation easy and trustful is using these massive sets of data to build around the intense customers in any industry like let’s talk about retail for a second. If you’re going to get help from your retailer when purchasing, there’s only that many types of conversations you’re going to engage in, so you can design very strong, very well-renowned out experiences around each of those intentions. I think I was talking about an example before, like checking up on an order which is very common in 30 or 40% of all the customer service inquiries come from Where’s my order? So you can build a very good conversational AI experience very easily on our technology. We’ve tried to make it easy enough for even an agent to design this conversation if need be. So you’re making it not only easy to design because while, they’re the ones having the conversation they know best how a customer actually wants to get a result. They’ve had the conversations thousands of times with an end consumer, so giving them a tool where it’s called the conversation builder actually on our platform to be able to build that flow very easily an NLU proprietary NLU engine that gets enriched with every additional conversation, we’re enriching it even more. So now you have not only very strong NLU that can keep detecting new words against any type of intent, but you also have a platform where you can continue redesigning the conversation and improving it as need be. So that’s only the tip of the iceberg. There’s so much more. 

Ned Hayes [00:09:23] I love the example of retail because retailers are dealing with so many customers that being able to triage that flow of customer inputs and being able to offload some of that onto a bot or on to a pre-built conversational flow, as you indicated, could be really helpful. I was curious if you had any surprising moments that you’ve really seen somebody use your system and be surprised by the efficiency of it or the help that it provided. 

Mariam Reza [00:09:50] I could quote so many of those, especially because when you come across good AI or good conversation, it is really now a delightfully experience, there’s not a lot of them out there, but one that comes to mind straightaway Ned, that is during the pandemic, a lot of big brands that have Stortford print needed to shift, right, shift strategy to continue engaging with customers, one such is one of the largest diamond jewelers in the world. What they did is they actually became a customer during the pandemic, so until last year, they wanted to make it possible for consumers to buy, while they’re not even in the store, such as Apple business chat and on the website, so you go to the website, you start a conversation with a bot, with this AI would enable is not only for you to pick but customize, as well as buy and then schedule a pickup. So once you’ve done all of that, you go into the store, it’s already ready for you. So it’s all integrated into the system to know when you’re coming for the pick up and it’s ready at the door when you walk in. So if you think about this whole experience, for me, as someone who’s buying a high value item, I need a lot of trust in this solution. I am going to spend several thousand dollars to if I’m going to buy diamonds and having that constant engagement and knowing I can go back to this channel any time. I don’t have to go through a call center, wait for another representative who does not really know until they look up what my last conversation was about. I can pick up my conversation anywhere I left all through that journey till I reach the store and pick it up. That whole experience in an environment where you needed that security or safety and you’re spending money delivered something very unique that we saw, you know, was over a million conversations immediately that that we’ve had already with this customer and an average conversion rate of over 15 percent, which is factors higher than what they would get with just online sales or self-service sales. 15 percent, you can imagine that’s high in any retail environment, but it was just the ease of that experience and the fact that none of those million conversations led the consumer down. 

Ashley Coates [00:12:02] That’s amazing. Well, in keeping on the topic of retail. How do you determine what kinds of conversations are suitable for AI? I know you mentioned pick up, does it work best for very direct action? Better simple questions about returns and order status. 

Mariam Reza [00:12:18] The answer is yes. So there are definitely by industry over the years. You know, we’ve obviously been doing this for several years. We’ve been able to fine tune what intense out of for every vertical are well-suited to AI. And it’ll be ones that in the simple category are ones that can be a dialog where you can ask certain questions to give specific answers depending on which path to go down. It is those simple, repeatable dialogs that can be designed. That is definitely one category, but more and more we’re finding actually that we can engineer more complex conversations. Something we’re working on is this whole idea of holding memory, bot having memory, which is really innovative in this space because you’re going to now try to correlate the conversation we’re having with something that the customer has conversed about in the past and their profile. So now you really are delivering AI aren’t you, to where Ashley comes in and says, Hey, I want to follow up on this particular purchase I made two weeks ago. It’s just been delivered to me now the AI can pick up what was bought obviously, they can check what was bought right? They can go to the last conversation. This is where the memory comes in and realized that it was not a good conversation. Potentially you were upset about what you bought and now you wanted to organize an exchange and what you wanted was not in stock. Here, the AI can now make a determination of, instead of saying, the generic put in your order here, let me look it up. It can actually go down a different path and say, I see that you’re coming back to ask about the exchange you wanted to make, and we were going to give you a status on the availability of that product. This is a much more complex example that I gave, but it’s really possible when you integrate AI into different platforms. It’s not easy what I’m talking about, but it is very possible over time. More and more of these customer intents can be resolved. I will go as far as to say that as high as 80 percent of retail, intense can be resolved by a bot. 

Ashley Coates [00:14:25] That’s absolutely incredible. Also, I want to talk about omni channel platform. What does that look like for customers today and what changes have you seen over the last two years in particular? 

Mariam Reza [00:14:37] That is definitely a phrase that can be used. It’s like, choose your adventure. What is omni channel? So I will choose my own adventure game as a consumer for me today. Omni channel is still hey, if I want to get in touch with my favorite clothing store, I will want to do that at my pleasure on the channel I want, right, if I want to go to their web site, don’t want to keep browsing, I start having a chat with somebody. I like to use a real example. I love shoes and Tamara Mellon is one of these brands that I really loved. They happen to be a customer as well. So if I want, I could engage in a conversation on chat, whether it’s on Facebook Messenger, which I use or WhatsApp, and then go to the website to look at products. And then for whatever reason, I need to call, I pick up the phone. Now, one thing I will say is that I, as a consumer should not, and will not do all these things and channel hop unless I’m getting a really good experience in one channel. If I’m getting a great experience with that first conversation or on WhatsApp with this brand, I’ll stay there. So the whole idea of omni channel is of making experiences available in all channels. This makes it quite complex for businesses to maintain the same experience in all these channels. So we are proponents of the channels that your customers really follow are on, or your driving adoption, I’ll do that very well. So they don’t have a reason to move. And if they do try to actually follow our customer through the different channels, we do find more and more. And it is one of the key goals of any of these programs is channel shifting like reduce the channel shift, reduce it, service them, help them very effectively in the channel they’re in. So I go back to my example. I will say I had a different view to omni channel pre-pandemic, which was omni literally happens entirely on the phone. So Omni has become mobile, whether it’s browsing or it’s messaging, it’s all happening here. So you need to enable this device right to be effective. We weren’t going to the web as much on our desktops. We just weren’t. And then we have the pandemic and all of a sudden website volume has just gone up and back up. We’re buying more online. We are buying on a bigger screen because that’s easier for some of us, and not all websites are mobile optimized. So that shift happened, that’s where Omni came back, but my view there is pick the channel that you really want your consumers to have a great experience and pick a channel that they’re already used to using and then make it amazing and really manage down on the channel shifting double down on actually not having them have to shift measure that make that a metric because it’s not only expensive, you’re also now disconnecting those engagements if you cannot, if you have not built an integrated model where you know when a customer is moving from one channel to another, that’s not easy for any brand out there to build a customer profile. But even if you do again have the experience in one channel and offer different experiences in that in that messaging thread, for example, if I want to have a voice conversation, enable that for me. If AI will service me better, give me an AI to service my inquiry all in the one thread. The idea of having it in one place is magic, because not only is all your data in one place, you also know how they’re interacting. All boxes are ticked for the consumer, the platform and the brand. 

Ned Hayes [00:18:06] So we’ve heard about AI in the news a lot lately, and a lot of it is hyperbole. It’s over the top. How do you distinguish actual functional A.I. that helps people day to day from this kind of hype quadrant? 

Mariam Reza [00:18:19] I think when you look at it for the purpose of customer service or retail assistance, all the what we’re hearing about in the media is more around how AI can displace humans and jobs and whether it can be trusted. There’s a lot, right? If I start, you know, we can have another podcast entirely on that. But that’s where trusted A.I. is such a big part of our mission, making it trusted because you want to be able to know that the AI you have one, it’s servicing the needs it says its services, right. It’s not trying to get information for any other purpose. So while all of that exists, brands will continue to replace a lot of these conversations with proper, trusted, convenient AI is because consumers like us are actually distinguishing the two as well. When we get a two second response to our question versus having to wait for a human to figure it out and then go and call us back. We are giving permission as consumers to brands to keep giving us better AI. It’s very different to us not trusting what certain big initiatives are out there when it comes to commerce, when it comes to are, whether who we bank with our favorite retail places or telcos. We are looking for anything that gives us a convenient, trustworthy answer and the information we share we feel is safe and a lot of investment is going into that data protection all over the world. So when you build that into your technology, the adoption we’re not seeing at all impacted by the wider community of AI hyperbole and say, as you said Ned. 

Ashley Coates [00:20:05] Also I’d love to get your thoughts on customer loyalty and how live person can assist with building loyalty. Our sponsoring company, SnowShoe, specializes in customer loyalty solutions for retailers. Yeah. And so how does LivePerson help companies build loyalty within their customer base? 

Mariam Reza [00:20:25] So if you think about the application of what we provide, it can apply across, you know, as I mentioned, helping consumers buy helping them with any inquiries. Loyalty is a very, very important part of that customer service  retention. And yeah, we’ve actually got some really great use cases for loyalty. So it’s one of the more visible use cases for conversational AI and messaging as a whole. So I’ll actually articulate it to an example Ashley. Dunkin’ was looking for new ways and new channels to build this continuous connection with its customers, so they really wanted to increase their customer footprint and retention by giving the added QR codes on their food packaging, and they wanted customers to have the ability to easily scan that code. Download the app and sign up for the loyalty program via SMS. So once they did that, they would get a free donut. So they’re giving out these free donuts for people to sign up this program. And this rollout has actually resulted in over 9000 Dunkin stores now having done this. It’s amazing as in having offered the download get a free donut and they’ve just expanded their loyalty network. What’s very cool about that is how they did it, the ease of having the customer just download the app. We all know that’s really easy. Sign up, get your free donut. But having done it through SMS was smart because everyone, every single phone is enabled with SMS. So that’s what you need to look for when it comes to loyalty. You’re looking for what’s the best way to reach my customer? And when you think about messaging, everyone’s doing it. If you have technology that can enable you to reach out to them via SMS, and this is not a SMS where they’re just sending an outbound unsolicited text you’re scanning, you’re getting a text message, then you’re downloading the app. The whole thing is consented, right? 

Ashley Coates [00:22:24] Absolutely. To a dialog with your customer. 

Mariam Reza [00:22:27] Yeah. 

Ashley Coates [00:22:27] Speaking of getting feedback from the customer and communication from the customer, last year saw a huge acceleration in the evolution of how consumers shopped, presented a huge opportunity for change. And so I’m curious what you learned from customers since the beginning of the pandemic with that two way dialog. What have you learned from consumers during this time? 

Mariam Reza [00:22:48] I would say if I wanted to synthesize what we learned one I think they were looking for over the course of this massive shift of how we buy and where we buy. They were definitely looking for virtual help while in a store or online. I think one big shift that has happened is they have been much more accepting of all these technologies that are helping them where they are. The shift from store to online has definitely happened. People like myself who did not really want to buy online are now buying much more because we’ve had to so that investments in digital and back on websites has to go back in. However, one of the things that has made us consumers is a lot more sensitive that I’ve seen, as we don’t accept, you know, waiting on hold as easily anymore. We want answers now because we know, you know, maybe five out of 10 are giving that to us. So why can’t the other five catch up? So we expect that the organizations we’re doing business with have answers immediately when we wanted, where we wanted. This is an expectation that consumers have amplified over the last year. We, as consumers, retail consumers, we just want to be able to buy very easily. This is something. Thank you, Amazon, and thank you all these big retailers have made us used to, I want to be able to buy quickly, and I want help and assistance wherever I can get it. So for brands to fulfill that at scale, they cannot just keep adding more humans to answer these questions, they really need to invest in that A.I. layer to be able to handle up to 80 percent of these inquiries if they want to stay relevant. And the other thing we definitely learned, as I said before, is when you’re in a store or when you’re about to be in a store, you still want to be able to get help virtually quickly in a store. While you’re in a store, you don’t necessarily now want to engage with a person in a store as much. You want that engagement to continue. If I’m talking to a bot or a human over text messaging, because I’ve seen something on a website when I go into a store, I want to be able to have that same experience. 

Ned Hayes [00:25:04] Right? Well, one of the key things that we’ve seen over the last 18 months, almost two years now, is the rise in contactless pick up, curbside pickup and being able to interact with a retailer without actually going in the store. So has AI, and specifically LivePerson really assisted with these trends? 

Mariam Reza [00:25:24] Yes, curbside pick up became so big last year. We created a really, I would say, a seamless flow to enable that for consumers. I’ll give you an example of one where I saw it being fairly successful with a lot of great customer feedback as well. I won’t mention the customer, but what the buyer was able to do is just drive up and text a number where they say which bay they’re in and they’re ready for the pickup. That goes to someone who has a device that is enabled to have a conversation back with any of these customers at any of the bays for the curbside, and it doesn’t have to be a person could be a bot, but it was initially a person because they’re going and bringing the items, sending it to the the actual pickup area. But the beauty of it, the difference here with the curbside pickup is generally, you know, we’ve seen where you get it and you’re told which one to park at and you get your items over here. You can have a two way dial, you can actually communicate with a person who is helping you with that pick up, which was really a good experience because not everyone was getting it right with curbside pickup. I’m talking about us as consumers. We might get our bay wrong, or we might get our items incorrect and we need to still communicate with someone. It can be quite a frustrating situation if you don’t think you can get that help because you think that it’s all completely contactless. Well, it is. But the conversation can continue while we’re doing it. So that two way communication actually that we just talked about was happening with curbside. You’re literally able to communicate with someone in the store and that person is communicating with maybe 20 other people who are all pulled up. So that was a very good use case during the pandemic. To enable curbside, simple, scan a code started a conversation, but more than likely you’re actually having a conversation with a human as well as AI and they’re having a conversation with everyone across all those bays. 

Ashley Coates [00:27:23] Yeah, thank you. That’s such a great example. Well, so let’s talk about data, which we always find exciting, hopefully you do too. So can you tell us what kinds of analytics LivePerson captures? How do your clients use this data to improve their customer experience? 

Mariam Reza [00:27:40] It’s such a deep question, I guess, because when it comes to data and how you can analyze it, you can cut this a thousand ways. I’ll put it into a few categories. Category one customer experience Category two would be efficiency, right? Operational efficiency and how you measure that. And the third area would just be adoption and the other areas of return on investment, right? Have I invest in the right channels, the right conversations. Let’s just focus on customer experience for a minute. You know how we started talking about. It’s really important about identifying the intents a customer has with a brand right there in everything we do, like if we measured our businesses based on how well are we satisfying the intents, which is the types of questions customers ask. It really helps us change the way we’re measuring instead of thinking about what’s the first contact resolution across the entire number of conversations versus what is the resolution rate for an order status intent. There is a difference there where you can, with data, actually categorize and hone in to every single intent and really drive customer experience. From that perspective, how well are we resolving what effort is being taken to get that resolution done? What is the NPS and very importantly, something that’s proprietary for us as we call it meaningful connection score, but we’re analyzing the sentiment in every conversation. This is very powerful because when it comes to NPS or CSAT, you need the customer to answer a question and they’re doing it maybe one out of three times best. Right? So you don’t have a full data set to really understand the experience or their sentiment. If we had a way which we do to analyze the sentiment of a conversation and the turns and sentiment change of sentiment, you might come in really frustrated and leave very happy being able to analyze that, or at least measure that is super powerful when it comes to truly driving customer experience. So that’s a big category, right? Just to how well we are servicing our end consumers needs. Again, to summarize, you know, it’s looking at how effective we were in fulfilling. So that’s like resolution rates. What effort was taken and then the measure of their satisfaction or sentiment. Then the other major category of operational efficiency, that’s huge because. At the end of the day, if I have a call center for my retail store. Why would I now invest in online messaging or messaging over the phone? Why would I invest in it? It does deliver a more efficient solution, not only because you can put some very strong A.I. to handle the conversations that you’re not having humans, that automatically is a lower cost, but also the humans are more efficient because they’re no longer having a one to one conversation. That’s akin to chat. But why is it even more efficient than chat? Because in chat, you have that dead air in the conversation, like you have to wait for a response back as opposed to messaging. You can go in and out of a conversation over days if you want. It’s completely asynchronous, so you really take out those inefficiencies even further. So to be able to measure that, that is a big investment on our part. How many conversations are being handled by bots or by humans and a combination of both compared to what it would be if it was on any other channel? That’s where you’re combining the efficiency with the return on investment. Similarly, on the sales side, how many sales were generated, how much revenue was generated per conversation all the way down to, you know, what sells best, which categories of products over messaging? I think there’s a lot of performance data, the operational data. We definitely invest a lot in being able to show the effectiveness of these bots and humans over the messaging conversation. 

Ned Hayes [00:31:27] Well, speaking of investing a lot. One thing that I know a lot of companies have worried about over the past year is privacy and being able to protect user data. And I know machine learning systems, AI driven systems have been accused of exposing data in ways that aren’t very helpful. So how does  LivePerson address that? How should the industry address privacy more forthrightly? 

Mariam Reza [00:31:49] Let me answer the first part of that. We have to align with a lot of the privacy requirements. Full stop. The customers we service today, some of the largest brands in the world, and when it comes to data privacy, it’s not just about taking a box on have we met the requirements of any regions like, you know, in Europe and me, it’s it’s very stringent when it comes to data privacy as well as consent and exposing what we will do with the data where it is hosted and so forth. But for us, it’s a matter of building that adoption and trust within using not only the LivePerson technology, but all of the conversational AI in the conversations. So yes, there’s a whole focus on that goes without saying we wouldn’t be scaling at the rate we are if we did not have that focus. But what should other businesses be doing? I think it’s very important for anyone when they’re having a conversation to know exactly what will happen with that information. We’re getting these upfront more and more when it comes to starting a conversation. It can be very natural. It can be very short, it can be very natural short. Everyone’s used to it, but we also need to be able to without me sounding facetious, stick to that. What we’re putting out there in any of our conversations with end consumers, we need to be able to show that we are doing that and that goes down to anybody wants to know about like, expose, expose your data privacy, how you do it, expose your security, expose what you do for consumers. It is so important today. It’s more important than ever, right? Because a lot more conversations are happening. We’re getting the permission from consumers and that permission can very easily be taken away. 

Ashley Coates [00:33:37] So looking into the future, are there any new AI powered technologies that you see coming down the road, new types of the AI technology that can enhance the customer experience? 

Mariam Reza [00:33:48] There will be a lot. Yes, I’m going to try and answer 10 things just popped into my head as you asked that, maybe I’ll try and answer it with what are we doing as well? Well, we’ve made some really good investments and new acquisitions recently that will give you an idea into how we’re thinking about expanding in this space. Firstly, we acquired this voice analytics platform called Voice Space, where we want to understand further all the conversations consumers are having with their brands. Despite having this major shift as us, as human beings did messaging with friends and family, we still can see a lot of businesses out there still maintaining call centers, right? So we want to be able to help them analyze all these conversations to better service them. That automatically will lead to investments in new technology in the customer experience space. I would say specifically, the immediate opportunity there would be like just in voice AI making that a lot more available in a meaningful way. I’m not going to knock what we have today in our homes and but it is quite limited in its ability when we think about voice, A.I. and what you can get when it’s very much one directional today, we want to be able to have conversations, whether it’s voice solutions or when we call in, we want to be able to do what we can on messaging today in a voice conversation so that you can enable consumers to go between whatever platform they want. They want to talk to somebody or they want to actually message with somebody, just make that experience very consistent. The other area of investment will, I think, be in personal AI is like your own little personal bot and personal assistant that you can design around you. That would be an area that I think I, myself, for example, wouldn’t mind a very complete personal assistant that could go all the way from booking my appointments to scheduling outings to booking a restaurant like that whole personal concierge. We’ve talked about it over the years, but now it’s more and more possible for us to enable that. We at LivePerson, we’re enabling that through several different initiatives. One example is what we started doing during COVID. Brands came to us to help them with their testing. They needed to get these COVID tests done before employees could come back to work. So our vision there was right we can enable that with combining this conversational AI that can help you through taking a test, track it accurately. But the goal is not to just give them a testing app. Eventually, that app can be your health concierge. It can really help you improve your lifestyle. Today, it’s for one test. Tomorrow, it can monitor multiple things and become that AI for you. We have these in pockets all over our phones. I think if you look at your phone, you’ll see it’s an app for everything. But to be able to bring that into one would be quite the customer experience I would want. But I think that’s not far away, but it’s still a little way out. 

Ashley Coates [00:36:50] Yeah, that would be pretty handy. Well, Mariam, thank you so much for joining us today. We have one last question for you, which is what is your legacy as an industry leader? What do you hope to further accomplish and be remembered for? 

Mariam Reza [00:37:04] This is a hard one, of course. I feel like I have not yet written my legacy. However, when you look down what you’ve done and where you’ve always stuck to and I’ll say it’ll continue in the path of leveraging the importance of human connection with whatever vehicle, whether it’s through AI or another human. But leveraging that connection, listening and understanding and being able to demonstrate empathy, being able to put that into technology or any business function or any initiative, I think that will be one that I’d love to continue down the path of. What would I be remembered for in that case? More and more as we, I guess, evolve where we get further away from human connection. I’d love to utilize all of these technologies and advancements in our arsenal to actually make that human connection even stronger and more possible, as opposed to creating a distance which we’re going through that curve, right? It has created distance between humans themselves. But yeah, if technology can be used in an effort to make it an even better human connection, that would be one of the legacies, right? And that’s why I stay in this space where, you know, every conversation you have on our platform with LivePerson, it’s going to be something that’s empathetic, trustworthy, we’ve understood if we haven’t, a human steps in and you have this full tangle, everyone’s here to resolve or help you stick to that industry. I guess for now till I figure out if there is another legacy out there. 

Ned Hayes [00:38:39] Great to hear your thoughts on this industry and all the growth that’s possible here. Really appreciate your time today. Thank you. 

Mariam Reza [00:38:45] Thank you, Ned. Thank you Ashley

Ned Hayes [00:38:47] The Spark Plug is a wholly owned property of SnowShoe all content and copyright 2021 SparkPlug Media.