The Building Blocks for a Better Personalized Experience
Customers that feel valued will return to a product or service. The local butcher shop down the street can achieve this with relative ease, getting to know customers as well as their orders and preferences.
At an enterprise scale, the dynamics are quite different. It’s unreasonable to expect a multinational bank to remember all customers’ faces, habits and preferred greetings when they walk into any branch. However, product personalization is still a goal large companies should strive for — and one they can achieve.
Product personalization boils down to several fundamental areas, all relating back to digital quality. In our recent webinar, The Pyramid of Perfect App Personalization, our expert panel discussed some of those building blocks that lead to well-personalized digital experiences, including:
personalized automated response
The emphasis placed on each step of the pyramid ultimately helps decide how efficiently a company executes a personalization strategy. Too much investment in, say, call center agents can reduce the likelihood of a successful in-market launch if it skimps on localization testing. AI plays a key role in triaging customer issues and complaints, as well as delivering useful recommendations, but it, too, requires the appropriate level of investment and clean data.
In today’s world, an app must not only work, but it must deliver an experience so intuitive that it drives the user back to it. A well-personalized, functional digital experience reduces churn all by itself and helps the customer feel valued. With help from a digital quality partner like Applause, companies can overcome the challenges they face at a global scale to retain customers for years.
View the on-demand webinar here or continue reading this excerpt from the conversation with ourApplause experts:
Adrian Garcia, Solutions Consultant
Mike Plachta, Senior Manager, Solutions Engineering
This transcript has been edited for clarity.
David Carty: We all have positive and negative digital experiences, right? I'm sure we've all been delighted by a digital experience and we've all been frustrated by a digital experience.
So, let's get started with a little bit of an icebreaker. Adrian, as a consumer, what is an example of a great personalized experience or feature that you enjoy?
Adrian Garcia: Well, there's definitely a lot of great apps out there that I enjoy. But I would say that one of my favorites is Spotify. I love waking up and tuning into my favorite music, artists, or songs. Also, a good podcast every now and then.
Spotify does a great job in creating mixes and recommendations based on the lifestyle that I have, activities that I'm doing throughout the day, even the date and time of the year. They'll give me summer recommendations or winter vibes, as well. And the podcasts that I get recommended are also based on the language of the music I listen to. So overall, it's just a great experience.
Carty: Great. Now, let's get into the more fascinating detail here, Mike. Let's talk about the lack of a personalized experience — the kind of thing that makes you want to throw your phone into the nearest body of water. What is something that absolutely frustrates you in terms of a lack of a personalized experience?
Mike Plachta: I actually wish it was fascinating. I think the frustrating experience is how we should all [refer to] it. I still feel like we have too many of these.
I mean, actually, just before this webinar, I spent some time on a call trying to change some of my flights. And I wasn't able to do that. I had to disconnect at some point because I had an upcoming meeting. I was like, ‘Okay, I'll just do it another time.’
But the experience that I wanted to talk about today was just my recent experience with one of my banks. I realized I have a service turned on that I'm paying for every single month, but I'm actually not using that service. So I tried to turn it off via the interface. I couldn't find the option. I tried using the chat icon. I was logged in. I started a chat [and] entered, ‘Hey, I would like to turn off this service.’ And the first message I got from the chatbot was, ‘Hey, we're going to have a human get back to you in 90 minutes.’ I'm like, ‘Okay I have to wait 90 minutes to connect with a human.’ Why [can’t] the chatbot resolve my question? Actually, it was not much of a chatbot. It was just always replying the same thing to everyone.
Anyway, they got back to me. I got a notification on my phone. Great. That works. But I didn't have time to complete that conversation at the time. So the next time I try it again, same thing — wait 90 minutes. And finally, I was like, ‘Okay, I need to do this. I need to spend those 90 minutes logged into the application, which automatically logs you out after some inactivity period, so you have to keep moving your mouse or keep clicking some buttons.’
After 20 or 30 minutes, the human person joined the chat and was able to resolve my issue. But I'm asking myself, ‘Why can’t I do it on my own within five minutes?’ It was so easy. I think the conversation with that person lasted even less than five minutes.
Carty: Yeah, that's forever in internet time. I mean, you get to a resolution a lot faster than that. For me, I think what I look for in a personalized experience is just being able to log in really easily, no friction there at all. To me, that's the biggest frustration is when it takes me 10, 15 minutes to just be able to log on and use an app. I just want to be able to use it quickly. I want it to remember who I am between different logins. And also if I'm hopping around to a different app on my phone, some apps forget who you are all of a sudden. And that, to me, is what's really frustrating with a lack of a personalized experience — anything that adds to that friction that enables you to use that app in the way that you're supposed to be able to use it quickly.
So let's put together our collective experiences and come to a little bit of a consensus here on what a great personalized experience looks like. First of all, you need a great product. I'm saying the obvious here. But obviously, it helps if you've got a great product that you know is meeting customer needs and is well-developed and just really great out of the gate.
You need to know your customers intimately. You need to understand the customer flows of your app and where users run into issues. Feedback loops are super important here, too, because that use can evolve over time, especially as you add to it or release more features. The less guesswork there, the better.
Integrations with other products and platforms — the web is becoming more immersive. And the expectation is: it's right at your fingertips; everything should be working right away. Friction is really the enemy there.
So any product or experience really needs to be able to integrate seamlessly. I know this is something that you're passionate about, too, Adrian. What else can we talk about with this particular issue here?
Garcia: Definitely. When it comes to integrations, they are basically trying to put different products or services together and just make our lives a little bit easier. I can give you the example of using social networks or accounts like Gmail, for example, to log in to other services — just removing that friction that you explained in the previous slide in which you have to basically let the app know every time who you are and authenticate yourself. It can be cumbersome to do that every time.
So having those integrations is key. And sometimes, it could be other services, like I said before with Spotify. When I go into my vehicle, it has a Spotify integration, and it's actually personalized that it knows who I am when I'm driving, and it's supposed to play my playlist. But sometimes when the car gets updated, that integration breaks. That has happened on one or two occasions in the past, and it's really a frustrating experience. So, making sure those integrations are there and are working properly is key to delivering a personalized experience.
Carty: That's a great point, too. Talk about the last place you want to experience friction. You don't want to be driving down the street and be messing around with your panel or whatever the case may be. It can actually create an unsafe experience, let alone one that is just frustrating for the user.
And then we have a couple of outcomes on [this slide] here, too. Customer loyalty — obviously, this is the name of the game. Price ultimately becomes less important than the experience when you're able to deliver a great personalized product. When the customer feels valued, they will stick around. They'll continue subscribing. They'll spend a little more money. They'll be your brand champions. They'll pull in other people via word of mouth. So really, you want to earn loyalty in order to see those kinds of benefits.
And that's what we're talking about. Every customer wants to feel valued. Now, this is a tough thing to try to strategize for, so I'm going to turn this over to our panel here. Adrian, I know you want to speak to three of the items on this list. Have at it.
Garcia: Thanks, David. So the first one [is] to develop products that address customer needs. The reality is that customers are gravitating toward brands that they feel like they're listening to the customers, to the end users. They understand them. They know their needs before even the end user knows them.
So having a good understanding to be able to increase engagement, provide recommendations that are valuable, enhancing the overall user experience — that's all basic in order to be able to deliver a personalized experience that customers want to come back to.
Loyalty programs — it's one of the ways that a lot of companies and brands achieve this. By having their customers providing some information about their particular needs, their demographics, then they can reward the users by providing them points. It sometimes could be another type of remuneration system, and you can redeem your points. And then that brings that experience of having a little bit back and forth where your users can enjoy additional experiences, and the companies can help to provide a more personalized experience by having a little bit more data to work with.
And, number three, it's discounts and promotional offers. Based on the amount of data that companies have collected, they can give you specific recommendations on products that you might be interested in or services. And they can give you discounts. For example, if you haven't been visiting a restaurant in a few weeks, they might give you a promotion so you come back and deliver that visit to the customer in which they're going to be spending money. And then at the same time, they're going to [be] accumulating points or rewards. So it all connects to each other. And I think that's where Mike can give us a little bit more information about that.
Plachta: Yeah, I want to speak to the last three points here in this slide. A couple of things — so, timely and relevant notifications. I feel like this one is becoming more and more important. I mean, [on one hand], there's nothing more frustrating for me personally when I go to websites, look at the product. I want to move quickly, start reading something, and suddenly this pop-up shows up. ‘Hey, why don't you sign up for our newsletter?’ I'm like, ‘Oh, my god, I don't want to do that. I've already done that before. Why don't you know it, even?’
On the other hand, if I'm hungry right now and I want to eat lunch, it would be great to get a notification from — I don't know — DoorDash, Grubhub, or UberEats, for that matter. Just, ‘Why don't you grab a lunch with us? Here's a nice discount or promo code,’ speaking to what Adrian just mentioned before.
So those are really important. Based on the time of the day, based on the place in the customer journey, where you are, are you still looking at the different products and just comparing them, or are you ready to make a purchase, for instance? And the same would apply to services. Did the service already start? Is someone waiting for a product or for the service delivery? All of that can be understood right now, and you can send relevant notifications. Keep your customer updated and posted.
The second one — resolve the customer's issues fast and in a cohesive manner. I believe that throughout the pandemic, we've all been frustrated by different things, maybe even sitting at home. And I do understand that it's sometimes hard to communicate human to human. But at the same time, we, as companies, have to take care of our customers, and we need to make sure that they have a great experience. So, this definitely connects to point number six, here. But every time you resolve a customer issue, you need to do this the same way. You need to make sure that the customer is happy. You need to communicate clearly. And if you cannot resolve the customer issue, explain why. Try to let them know and let them understand what happened that led to a situation that you cannot resolve for any reason. That's extremely important for a good experience and for customers to be coming back to you.
Last, but not least: the end-to-end quality customer experience. It has to be, from the first point of contact that you're making with your customers, whether that's a newsletter or an ad, which should be a great experience already, throughout the traditional brick-and-mortar experience or a digital online experience — when making a purchase or when doing something — and up to the point when the customer contacts you to resolve an issue, that all has to be a quality customer experience. And it will definitely lead to a point where the customer will value your service more than the price difference from the competition.
Carty: Absolutely. So, this isn't easy though, right? I mean, this is definitely a challenge. And it's something that some would argue can be a little bit more challenging at scale. The argument might be that the butcher down the street who has 30 loyal customers can deliver a better personalized experience on a daily basis than a large, multinational company. But I think, Mike, you feel a little bit differently about that, right? Because resources start to come into play that can enable better personalization for larger companies. They're just not using it the right way.
Plachta: Right. We talked about this the other day. When you enter that butcher, they probably know you. They say, ‘Hi, David. How are you doing? Do you want the same thing as usual?’
Technology can enable everyone to do exactly the same thing. You identify your customer. You understand who they are. You understand their purchasing patterns — if we're talking about retail, and you can do exactly the same thing.
Every time I log into Petco to buy cat food and cat litter, they already know what I want. They can suggest to me, ‘Hey, Mike, we've seen that you've made this purchase about three months ago and that you're making similar purchases every three months. Do you want to do the same thing?’ You click Yes. And, one hour later, the product is waiting for you to be picked up from your local store. Amazing experience. And that's very easy to do. And that's really important.
You have to build AI around it. You have to have some resources around it. It will definitely be costly. It is definitely necessary to improve that customer experience. [But] at the end of the day, you will look at some savings, too. Because your support teams will receive less calls about bad experiences.
Carty: Right. Absolutely. I mean, we're talking about architectural and organizational changes here. You've got to revolve your whole operation around personalizing that app for your customers — as you say, resolving issues as early as possible so that you're cutting costs at that call center level. I mean, that's where it really starts to get costly if you can't get to it before that point.
When we're talking about scaling and challenges here, pulling information from different silos — this can be another especially big challenge, right, Mike?
Plachta: Yeah, definitely. Working between the support teams and the product teams and connecting them together, making sure that they resolve issues. The support team can be a great source of information for a product team to identify the most common customer pain points to be able to resolve them with the technology. We have all the pieces in place. We just need to put them together, enable that communication, make sure that those two departments — not only those two, but many departments — collaborate, and then we can make that customer experience better.
Carty: Right. And management of customer data at scale, obviously, a challenge, too, when you're talking about different regulations all around the world, but a necessary endeavor to properly inform the algorithms to receive predictions and things along those lines.
So we've been talking about a pyramid. Let's look at our pyramid here. So let's look at our building blocks as we move up here. The customer journey, the foundational layer, at the bottom there. Localization is going to go right on top of that. As we go a little further up, you have the personalized automated response. So here's where we have some AI influence here. And then the human being right at the top, [where] we're talking about call centers and issue resolution, things like that. Really costly resource, but one that you can't altogether ignore.
So let's take this step by step here. We'll start with the customer journey. And here's Adrian to talk about this with us. Now, as a company, we refer to the customer journey a lot. And we're kind of referring to it in a little bit of a different way in this particular pyramid. It's a little bit of a blend of functional testing, payment testing, UX — basically, what we're talking about here at the foundational level of the personalization pyramid is understanding how users are going to interact with your product and catering to that kind of use, right, Adrian?
Garcia: That is correct, David. Like you said, the customer journey is the base layer of any app or digital experience. The goal with that is that we can guarantee that a user, from beginning to end, will have the experience that you're designing.
So, for example, before, we talked about logging into an app, having the right integrations, whether that's through a Google single sign-on. Or, if it's going to be two-factor authentication, you have to pull up your authenticator app or maybe receive an SMS. It's all part of the experience. And if you're not personalizing to the specific needs of a user, then people can get frustrated easily enough. And that will lead to abandonment.
After that, you have to guarantee that the user is able to understand the different screens in a mobile experience or the pages on the web. You have to make it easy enough to navigate. So that all relates to UX. It's extremely important that you are designing for all users. And that, also, is part of the inclusive design process. You have to make sure that it's available for everyone and accessible for everyone.
So, you have to take into consideration, as well, payment methods. There's so many variety of payment methods nowadays that not only includes credit cards anymore, but other methods, like PayPal, for example, peer-to-peer subscriptions, you have BNPL as well — Buy Now, Pay Later. So there's so many different factors on the different flows.
And that's without putting into consideration so many devices and types of operating systems. So the screen size is going to matter a lot, where you are at the time of the day, whether you're using a specific browser — these are all different variables that can be complex for a lot of engineering, testing, and product teams to make sure you can deliver that experience taking all of these considerations into the flow.
So [it’s about] understanding how to cater to specific needs based on this customer journey and tailored to specific personas — so making sure that you're tailoring this specific journey to a user, for example, in their 60s, that may be, for example, a female that is located in the US could be a very different experience than a young male that is going to be located in Japan. So we'll talk a little bit more about [localization] on the next slide, but that's building up into how to build that second layer of the pyramid.
Carty: Absolutely. We've been talking about users a little bit like they're all the same or interchangeable. But really, the personas can be quite different. And you mentioned accessibility. It's such an important point — something we're really passionate about here at Applause — promoting inclusive design. So some really interesting points there, Adrian.
So localization — next step up on the pyramid here. And if you happened to catch our localization webinar back a couple of months ago, you might recognize this image here. I think it's just super helpful to explain what we're talking about when we say ‘localization.’ It goes well beyond translation. And translation is challenging enough. You're talking about verbal and written language. You're talking about different dialects. You're talking about different ways of speaking all around the world, and slang — things like that.
But it goes beyond that — cultural sensitivities, local customs and norms. And so there's really a lot in this area, right, Adrian?
Garcia: Correct. When it comes to localization, there's also a lot of variables to take into consideration. Let's say, for example, that I'm going to be buying a pair of sneakers online, and I want to go ahead and pick them up at a store. I want to go running today. The best experience is if I go ahead and download my app for any type of shopping experience that I want, I'll be able to select a location that's near my current geographic location. So that already [counts] as localization.
Then the language [counts too]. It could also be temperature or measurements. It could be currency if I'm traveling abroad, as well. So, all of those little things are taken into consideration.
And not only that, but also the cultural sensitivity. You might be sending a promotion to someone that is on the east coast using idioms that are normally used there. But on the west coast, that could have a totally different meaning. So you want to make sure that when you're personalizing those promotions or notifications then that actually is tailored to the specific location of the user that you're working with.
Carty: Absolutely. As a content marketer, I know all about avoiding idioms when we're talking about content. You don't know what's going to translate well to another language.
And I think when a lot of people hear localization, they think, ‘Where are you? Where is our customer?’ And that's true. But I think, really, at the core of it, what you're talking about is, ‘Who is your customer? Who are they on a foundational, cultural level?’ And it's about understanding that person in the context of who they are when you're targeting them for your service or for your product. So it's a really fascinating area to try to get right. And unfortunately, a lot of companies don't get it right.
All right, thank you, Adrian. And we're going to go back to Mike, now.
Let's talk about the personalized automated response. Now, here, we're talking about delivering effective recommendations based on past purchases and behavior. But we're also talking about chatbots for customer service and issue resolution. So what can we recommend in this area?
Plachta: Yeah. I really like what you said earlier. You cannot treat every customer the same. Everyone is different. Everyone has different backgrounds. We all have got different age groups, genders, et cetera. So you have to take all that into account.
Luckily, AI really helps. I feel like almost every website has a recommendation engine right now. The tons of ads that you see every single day, they are all personalized unless you opt out of it. And some people like it. Other people don't. I actually do [like it]. I don't really have time to find great products, so I like to have them suggested on some of the ads. Other people will be like, ‘No, I really want to protect my privacy. I don't want any personalized ads.’ I really respect that. That's completely fine.
AI really helps. AI needs to be properly trained. So you need to have high-quality data to build AI. If you don't, your product will fail. I've seen too many like that. We've had a ton of customers who tried building AI algorithms just using some random data on their own. They quickly learned, ‘No, we cannot do that.’ They turn to us for quality data — for data from hundreds or thousands of people — and we were able to provide that to help them build those algorithms.
Furthermore, your AI needs to be retrained all the time. So situations change, economy changes, that will have an impact on things that customers are even asking. If we talk about chatbots, even, everyone is getting used to chatbots or voice bots. So you hop on a call to resolve a customer issue. The first thing you're going to hear is a computer voice asking, ‘Hey, Mike, can you identify yourself? Can you provide your booking number? Can you provide your receipt number or maybe an order number?’ Anything that helps them identify you as a person and help you better resolve your question.
The thing that you can do with chatbots, and voice bots, and all these automated services is you can resolve customer issues faster. You can skip the wait time. Traditionally, you would have to wait 5, 10, 15 minutes on line waiting for a human to resolve your issue. Right now, you connect over a chatbot or a voice bot, you describe your issue, and based on some of the keywords that the person will be using, the chatbot can recognize, ‘Oh, this is the issue. And so let me recommend this, and this article, or this tip, and then let's see if that helps before we connect with a human, before we incur that additional cost.’
This has to be localized, like we discussed using those idioms and things that are localized. And that also needs to focus on the most common customer issues. Talk to your support team. Identify 20% of the most common issues that are occurring. They'll probably cover 80% of the situations — so we're talking about a priority rule— that your customers find themselves in.
And, then, just one example that I want to provide. I recently changed a mobile operator. And for some reason, my wife's phone was losing the data connection from time to time. I didn't know why. I'm an IT person, well-immersed in technologies. I figured, ‘Maybe I'll try to resolve myself.’ But I couldn't. I eventually couldn't resolve it myself. ‘I'll turn to the chatbot.’
The chatbot was asking relevant questions, [trying] to identify me. It asked, ‘Which line does the problem occur on? What kind of an issue is it?’ And then suggested an article. The article wasn't that helpful because I already checked those steps. But, at the same time, this article probably provided the right information for most people. I'm going to talk about the rest of that journey in a moment on the next slide.
Carty: Right. And just real quick, Mike, I mean, this is an area where a lot of companies could get really sophisticated and have really well-groomed data collection operations here. And [yet] so few are missing the mark. And I think that's part of what ends up being a frustrating experience: you're on the phone, or you're waiting for 45 minutes, or you're waiting for the live agent for 20 minutes. You could be collecting some useful data during that time, and a lot of people are missing the mark with that.
Plachta: Yes, exactly. So very often when you hop on the phone with a person, they start asking you questions. ‘Okay, give me your account number, or give me that order ID.’
I remember that a couple of years ago, we were working with NHS, National Health Service in the UK. They were building a voice service that would collect your name, your address, your date of birth, primary complaint — anything that would help save 2 minutes from the real human support person time. Just 2 minutes. But imagine 2 minutes times 100,000 calls every single month or maybe even every single day. That's a tremendous amount of time that a healthcare provider — maybe a nurse, maybe a doctor — can spend on actually helping you instead of just collecting very basic information.
Carty: That's exactly right. It adds up so quickly.
And that's why we have the human influence right at the top of the pyramid. It's a necessary component, but it is a costly component.
Now, we talked about how AI can step in here and be helpful with things like sentiment analysis and giving other rich details that can help a human operator resolve issues. So, Mike, when you talk about this part of the pyramid here, what comes to mind for you in terms of having an efficient human influence right at the very top?
Plachta: Yeah, that's right. I think it's very important to stress that part. This is the last step that you should focus on. You should figure out all the three basic steps first, and then add that human influence. And for me, personally, this is probably the hardest one to build, as well, but if you think about it, very important.
So continuing that journey that I had with my mobile operator, so once I said, ‘Hey, this article doesn't help me,’ the chatbot realized, ‘Okay, so let me connect you with a human.’ And there is a wait time. There's always a wait time — a couple of minutes. But the chatbot was really helpful in that matter and said, ‘Hey, so before the human hops on the conversation, let me collect some additional information.’ It asked me to take a screenshot of my network settings. It asked me to say, ‘How often does it occur — does the problem occur? Is it frequent? Is it infrequent? Is it something that happens every single day at 5 p.m., or is it something that occurs randomly, et cetera?’ Just get more information about the issue.
Then the human hopped on the conversation maybe two minutes after I provided all this information. They quickly reviewed it, and they told me, ‘You know what, Mike? Try checking if your iOS is up to date.’ And I was like, ‘Oh, wow. Okay, I haven't thought about that. Let me check that. No, it isn't.’ And they said, ‘Yeah, try that and let's see.’ I was like, ‘Okay, that's going to take about 15, 20 minutes. It doesn't make sense that we stay online. Let's just disconnect, and if the issue occurs again, I'll just connect with you.’
That was a great human influence. So, first of all, a knowledgeable support person who was able to help me. Second of all, they were able to quickly resolve my issue. But if you think further about it, could the chatbot resolve that issue? It probably could.
One more thing that I want to talk about here is understanding the customer sentiment. So is your customer frustrated about the experience? Are they screaming bad words, or are they maybe saying, ‘Stupid chatbot.’ Or are they saying, ‘I want to talk to a human. Human, human!’ Those things happen. The chatbot should recognize that, as well as immediately say, ‘Hey, let me connect you to a human. I am sorry that I was not able to resolve that issue for you.’ And that will already help. That will already soften the blow.
So communication — very important. Recognizing the customer sentiment. And then thinking about what else can the chatbot do — or voice bot, for that matter. It doesn't really matter. And then plugging in that human experience. But also very important [to be] knowledgeable.
Carty: Absolutely. And this is the part of the pyramid where you're really trying to go to a last-ditch effort, in some cases, to preserve your brand reputation. I mean, the last thing that you want is somebody leaving because you can't resolve an issue that maybe a chatbot might have been able to handle in 10 minutes.
I did want to ask you, Mike, before we go on, is there a standard across industries — and forgive me if that's too broad a question — on how many issues that a chatbot should be able to resolve versus a human at the top of the pyramid?
Plachta: Yeah. I don't think there is a particular standard yet. But I would always lead with the priority role that I mentioned before: 80/20. It will definitely help a lot.
But talking about what you mentioned, that last ditch effort, sometimes we just need to compensate the customer. And very often, that decision of how much do you need to compensate the customer is made by software, as well. So the human consultant who's going to speak to you, they will consult software and application asking, ‘Hey, how much can I do? Why not shift that experience to a chatbot?’
Why not say [via] the chatbot, ‘Hey, I'm sorry your package is late. We promised that it's going to arrive on Friday, but unfortunately we couldn't predict this or that, and it's going to arrive tomorrow or even Monday, for that matter. Let me give you a $10 voucher for your trouble.’ You would feel amazing. And if the chatbot resolved that issue, that would be just one minute, let's say. It's resolved fast. It's probably resolved in a way that you are happy about. And you already know, it's not going to happen today or Friday. It's going to happen next week. But you have all the relevant information.
Carty: Right. Actually an opportunity to improve your reputation instead of mitigating the blow of how much it is hurt by a particular issue or challenge with a customer.
Plachta: That's right.
Carty: So really, really interesting. Let's bring it all together. Let's look at the pyramid one more time here with a little bit more detail.
So customer journey at the bottom — again, we're talking about all of these foundational elements of digital quality that we talk about all the time: functional, UX — making sure that it works and it is usable. Different device/OS combinations. Making sure you're understanding the user flow.
We go one step up to localization — relevant translations, understanding cultural sensitivities and customs, and obviously operating on the correct side of the law is very, very important, whether you're talking state boundaries or country boundaries. The personalized automated response — here's where we're talking about our predictions, our recommendations, chatbot help, which can be super, super helpful in issue resolution. And at the very top, we're talking about that human influence as it applies to customer service and, again, issue resolution and preserving your brand's reputation.
So I'll bring back in the panel here. We're kind of just summing things up over here. This is not necessarily an easy task. It involves a little bit of investment. We're talking investment in AI, investment in digital quality from the ground up. It requires a pretty efficient and sophisticated data collection operation if you want to deliver helpful recommendations and things along those lines.
So, Adrian, if there's a particular takeaway here, what would you say that is for our viewers today?
Garcia: The reality is that companies are being challenged on a daily basis on how to elevate the customer's expectations to receive relevant, contextual, and convenient experiences across the board. So that could include all types of verticals; in retail, quick-service restaurants, travel, hospitality, media and entertainment, financial services, and health care and lifestyle companies.
So, it's just a really broad spectrum where you actually have to deliver a personalized experience. And, like you said, it's not easy. But it's something that, if you want to be able to thrive in the current digital age, you have to be able to deliver it.
Carty: Absolutely. And Mike, you said earlier, it's going to take some investment. Where should those investments go? When you're thinking about doubling-down, putting extra money toward this kind of issue, really trying to understand your customer end-to-end, provide a better experience, how should you think about those investments on a holistic level?
Plachta: Yeah. I'll just probably say, invest in AI, whether that's personalization, or chatbots, or voice bots. It depends, obviously, on the business that you're running. But you're definitely going to hit a couple of these pain points in the future, whether that's improving sales by personalization, or whether that's problem resolution through chatbots, you're going to have to do that.
I mean, think about the recent experience with airlines canceling thousands of flights because of various reasons. If a chatbot can resolve 80% of the issues that are happening, then your call center will not be in crisis mode. And I believe that the call centers of those airlines are in crisis mode, right now.
So AI can resolve issues. It is an investment. In my opinion, it's a necessary investment. But it provides a quick return on investment, as well.
Carty: Absolutely. And here at Applause, we offer a wide range of digital quality solutions and services that really hit each step of the pyramid all the way along the way, whether you need manual functional testers in the market in which you want to launch — real people, real devices, real locations — to test your customer journeys and localization, whether you need to grow your test automation operation, or whether you're looking to simply improve the user experience [or] you need voice testing, AI, data collection — like Mike talked about earlier — accessibility, [or] inclusive design — another area that we are super passionate about.
We want to be your digital quality partner. We want to know what your goals are, and we want to help you get to the point where you can launch the best possible product for your customers. And we work with a variety of companies and do that in a really, really interesting way.