How to Become Customer-Obsessed

Kailey Raymond: Being customer-focused or customer-centric isn't going to cut it these days. As Jeff Bezos said, companies need to be obsessed with our customers. If you want loyal unfettered support, you need to know your customers needs before they do, engage with them in a meaningful and personal level, and ensure your policies are so customer-friendly that they do a double take. And with the advancements in predictive and generative AI, this mindset is more attainable than ever. Today's guest, Marbue Brown is a student of the Bezos' School of Customer Obsession. In this episode, Marbue discussed how AI is enabling customer experience, anticipating customer needs, and what it means to be customer-obsessed.

Kailey Raymond: I am so excited to have Marbue Brown on the show today. He's a really accomplished customer experience executive. He's worked with iconic brands across some of the most incredible companies in the planet; JP Morgan Chase, Amazon, Microsoft, Cisco, to name a few. He now owns his own firm, which is actually helping companies achieve better business results through tactics related to customer obsession. Marbue, welcome to the show.

Marbue Brown: Well, thank you so much, and I'm really glad to be able to join you today and looking forward to us having a great discussion.

Kailey Raymond: Awesome. Thank you so much for being here. The way that I like to kick this off is just to learn, in your own words, you've worked at some incredible companies known for their customer experiences. But tell me about your career journey. How did you get to where you are today?

Marbue Brown: Well, interestingly enough, I got into the customer experience space right out of graduate school. I went to work for a company, sometimes people would call it the Bell Labs of the Baby Bells. And our remit was to really take customer experience measurement to the next level, take it to the next stage. And so, early on, I got involved in work that we started pioneering some new techniques relative to how you would measure customer experience. We got to publish that. Some of that work is still being cited today. Some people cite it to take potshots at it, but that's okay.

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Kailey Raymond: All press is good press, Marbue.

Marbue Brown: But that's how I got my start. And then after that, no matter whether my primary role was customer experience or my primary role was something else, I always found my myself in a position where I was working backwards from the customer. I was being an advocate for customers. I was connecting the dots to how we could raise the bar for customers, and it's just something that I've been super passionate about. So it carried to the roles that I had, leadership roles in all of those different companies that you mentioned; Cisco Systems, Microsoft, Amazon, JP Morgan Chase, and I also had the opportunity to work with some of the most incredible leaders along this journey, and so it's just been a really great ride.

Kailey Raymond: That's great. I'm so excited to dig into it. And recently, you released a book, Blueprint for Customer Obsession. I'm curious for you to tell us about what that book is about, and in particular, what the difference is between being customer-obsessed and anything else that's customer-driven.

Marbue Brown: Well, look, Amazon actually popularized the term customer obsession. And especially as they've had this runaway success to become one of the most dominant companies on the planet, that phrase became a lot more used, and people all over the C-suite have been using it to describe their company's commitment to the customer experience. But everybody who says that doesn't necessarily mean the same thing. And so I wrote this book to take the ambiguity out of the phrase 'customer obsession', and what I've been able to do is to lay out the eight hallmarks that separate customer-obsessed companies from their peers. And their peers may be customer-focused or customer-centric, but there is a difference when you get to the level of customer obsession.

Marbue Brown: And there are some things that customer-obsessed companies do differently that are completely different than their peers, but there's a collection of things that they tend to all do, and whereas some of their peers may be customer-centric, they might do some of them here and there, but they don't do this whole collection of things. So that's basically what the book is all about. And as we go through the interview, I'll get a little bit more specific about what some of those hallmarks are and people will be able to have those as takeaways from our discussion as well.

Kailey Raymond: That's great. It sounds like it's like a spectrum that you're describing, of you can be working towards being customer-obsessed, and if you can continue to add these different activities and tactics and strategies, then you actually might be that definition that we're all striving for to be actually customer-obsessed.

Marbue Brown: That's absolutely correct. By the way, one of the things that we have in the book is something called the customer obsession continuum. And it goes all the way from companies that are customer-indifferent, to companies that are customer-aware, to customer-focused, to customer-centric, to customer-obsessed. And we have very clear markers that people can use to understand what's the difference between each of those different levels on the continuum and even some quick reference tools that they can use to assess themselves and say, "Well, I'm kind of between here and there." And so yes, it is a journey, absolutely.

Kailey Raymond: I love that. That's really interesting. We actually just released a book ourselves, and it's kind of like the ability... Ours is called the Customer Data Maturity Curve, and so it's the ability for folks to take the digital actions and be able to drive personalization and make sure that you are doing best by your customer and across every single channel that you can, and that's the ability to do it technically. And yours is the desire. And so it's this really interesting little graph that we can create together talking about those two things.

Marbue Brown: I just love that. I just love how you described that, that whole issue of maturity, right? Because there's a place that you can get to that's the top of the mountain, if you will. But like anything else, one time somebody asked me, "What comes after customer obsession?" And I said, "More obsession." Because you can't say, "Oh, I got to the top of the mountain and now I'm just gonna hang out there." You got to keep striving to actually maintain that position 'cause it's not just gonna happen like that.

Kailey Raymond: The bar keeps changing.

Marbue Brown: The bar keeps changing.

Kailey Raymond: The bar keeps getting higher. And one of the things that I think makes the bar higher are our customers. Of course, they're driving a lot of the reasons why we're leaning into some of these larger macro trends that we're seeing. So I'm curious, from your perspective, you've been in this industry for a very long time. What are some of the top trends that you're seeing related to customer experience today?

Marbue Brown: Well look, for example, more automation is one of the things that I see, that people are tapping into, how can I use automation to deliver the customer experience? But, as our technologies get better, the ability to use automation also gets better. And so that's one of the areas that I see people tapping into, using automation a bit more, but I also see that they can get better and better at automation so that it's not annoying to customers, right? 'Cause when automation doesn't work properly, it annoys customers. We don't want that. That's not customer obsession. I see people embracing the notion of omnichannel more.

Marbue Brown: Some companies were firmly planted in the brick and mortar space. Some companies were firmly planted in the digital space. But now, people understand you need to have a healthy crossover between the two of them. One is not the stepchild and the other one is the real business, if you will. It's all the real business and you got to be great at it in the different channels. So I see people embracing that more. I see more recognition that employee experience is a huge contributor to customer experience.

Kailey Raymond: I love this.

Marbue Brown: And so, if you don't have that employee experience right, it's not likely you're gonna get the customer experience right. And so that's another thing that I see is a bigger trend, that people are embracing this notion of the symbiotic relationship between employee experience and customer experience, and I think that's another big thing. And then, another one that I see is a big trend is embracing a wider net of customer data sources to understand customer expectations and requirements. For a lot of years, people have really anchored on surveys and capturing their data about the customer through there.

Marbue Brown: Yet, there's a huge gold mine of information that companies have all day long, every day, that they're getting through other sources. They're getting data through their interactions with their contact centers, they're getting interaction with their representatives dealing with customers directly, they're getting interactions through email, chat, social, and so there's much more embracing of how do I tap into these data sources, this complete set of data sources to really understand the customer expectations, the customer requirements of being to work backwards from the customers? So these are four trends that I see a lot of right now with respect to customer experience.

Kailey Raymond: I love this. I was actually just speaking this week to somebody on my team about how and when and if we'll ever get rid of things like NPS surveys, because we have so much rich customer data that's telling us a lot of what the customer is actually doing and how much they're actually using your products. You can do social listening across social media platforms. But my argument was, this new trend towards zero-party data, so first party data being what you actually are collecting about people and their actions, zero party data being form fill. Tell me about yourself and how reliable is that narrator? I think you're gonna need to continuously marry the two, right? I don't think that there's a way that you can get away from NPS.

Marbue Brown: Absolutely, it's gonna be important to marry these data sources. The challenge that companies have had is that a lot of the data that's freeform is very difficult to parse, and they've not been able to do that well. Look, this is one of the things that I think that AI is gonna help us with tremendously. Large language models have made it possible for us to parse data in ways that we were not able to parse data before. Now, these sources of freeform data will become more accessible. They'll become accessible in ways that people are able to see what the themes are and be able to summarize those themes in a semi-quantitative type of way.

Marbue Brown: They're gonna be able to understand sentiment. People are talking about these things, but are they talking about them mostly in a negative way? Are they talking about them mostly in a positive way? In some sort of a mixed to neutral kind of a way? So that's something that's gonna happen as we get a little bit further down the path with AI. But hey, we're already beginning to see some great examples of how people are gonna be able to parse this data and that's a game changer.

Kailey Raymond: I love that you just said that. The last company that I worked at was called AlphaSense and it did that. So it had NLP technology and it would be able to assess the sentiment of documents. It also took unstructured data in the form of long form writing, earnings reports, 10-Ks, all that kind of stuff, and it highlighted the top trends. It does now Gen AI summaries to be able to pull the top bullet points from a lot of those documents, and that is huge. Imagine call listening and being able to take the most succinct points from a call center and deliver that back out to your agent and immediately be able to solve their problems. Incredible.

Marbue Brown: Yeah, and voice-to-text technology is getting better. There's all this type of stuff that's going on, and now, AI is gonna make it possible for these agents to have co-pilots that actually help them in the middle of conversations with customers and is able to suggest to them ways that they can solve the customer's problem faster. So it can be parsing this information practically in real time, helping them to just come up with better solutions for customers when customers are calling in with inquiries or they have some difficult problems to solve. All those things are actually going to be game changers in the way that we deliver customer experience.

Kailey Raymond: Is AI a critical piece of the next bullet point of being customer-obsessed in this new era?

Marbue Brown: Oh, absolutely. I absolutely see AI as being a critical piece. Look, we've heard a lot of concerns about AI, and to be quite frank, I'm not going to downplay the concerns or dismiss them, let me put it that way. I'm not gonna dismiss these concerns. But I think some of them have been maybe a little bit overblown. Some of the applications that people talk about where AI could be problematic, it takes very specialized knowledge, it takes a super determined effort, if you will, to be able to execute some of the things that they're talking about. So it's not a large swath of the population that are ever gonna be able to do some of the things that they're talking about with AI.

Marbue Brown: But that said, despite some of those concerns that we do need to pay attention to, I see, in the customer experience space, some really important ways that AI is gonna help us. I mentioned being able to parse customer data a lot better, it's gonna help us there. I mentioned about co-pilots that will assist agents in being able to deliver a better experience for customers. But, I mean, if we go into some of the spaces like automation, think about mobile apps and virtual assistance in mobile apps that may help people to navigate mobile apps. Especially, you may have mobile apps that are a little bit more complex to navigate, an insurance company mobile app, and you need to find certain things in there; how to file a claim, how to post information for that claim and all those kinds of things.

Marbue Brown: But if you have a great AI-powered virtual assistant, it can help you get to those places without having to do a whole lot of work. Think of banking apps, and I could go through a variety of different types of scenarios. Even you can take a shopping app, where a virtual assistant can help you get to the place, the things that you're looking for without expending a whole lot of energy trying to do that search, because it's smart enough to understand regular voice commands in natural language and take you to the place in the app where you need to do the thing that you need to do, if you need to do a return, whatever the case might be.

Marbue Brown: So you have that sort of thing. Think of IVRs, right? You have an AI-powered IVR and you don't have to spend a whole lot of time punching a bunch of different buttons to get to where you need to go to. Now, I know sometimes folks are actually doing that to give time for agents to do some other work, if you will, but the flip side of the story though is these IVRs may be smart enough to enable you to solve some of the issues that you're trying to solve without frustrating you. This is the key, right? Right now, some of those IVRs, they can help you do stuff like that. But they may wind up frustrating you because when they don't know how to do what you need to do, you just get stuck in a loop, and you can't get out.

Kailey Raymond: We've all been there.

Marbue Brown: And you have to make three, four, five calls to be able to get to where you need to go to. But with AI, this would be smart enough to say, I can't handle this. I need to transfer it to a live agent. It'll be smart enough to be able to detect when somebody is getting frustrated or angry or any of those kinds of things and make the right call. So these are some of the kinds of things that AI is going to be able to do that's really going to help create better experiences for customers. And I think that going forward, the companies that don't embrace this sort of stuff will be behind the curve when it comes to delivering the top of the line experiences for customers, right?

Kailey Raymond: I absolutely agree with you. And what's really interesting is you're talking about friction reduction for the customer, making it as simple as humanly possible to get to the answer that they need to get to. And what I think another benefit of that is, is kind of going back to one of the trends that you mentioned, which is employee experience. The employee experience of having some of these tasks that might have been really manual or you're clicking around in different systems and making it seamless for you and saving you a ton of time can also enhance the customer experience. So it's this really interesting flywheel that we're putting together in theory, if everything goes well, that could not only aid customer experience but go back into that feedback loop.

Marbue Brown: Yeah, but let me tell you, this is not theory. I mean, let me give you an example of something. If you go to Amazon and you start your customer service experience through chat, you very likely will be dealing with a chatbot, right? Now, that chatbot is a pretty smart chatbot. It's gonna come up knowing the last thing you ordered, the last few things you ordered. It will come up suggesting to you that maybe one of these things is what you're contacting about, and it knows how to interact with you in a very smart way. But it also knows that at certain points, it may need to transfer you to a live agent, and it can do that seamlessly. And that live agent can complete certain aspects of that and actually transfer you back to that chatbot seamlessly, and the chatbot can actually complete the experience. What I'm saying, though, is that where we're gonna get to is a point where dealing with a chatbot may be almost indistinguishable from dealing with a live agent. We're not quite there yet, but we're not too many steps away from that. And so those are some of the kinds of things that we're actually going to see.

Kailey Raymond: So, so interesting. And I think a lot of what we're talking about requires a lot of data. AI has this feeling of this huge paradigm shift happening in the market right now. It almost feels like pre-internet and internet. That is how vast and how large this feeling is right now. I think in particular in tech, it feels like every single day, every single moment, people are asking, how are you using AI? I was just at a conference and there was something a little bit different in the air at that conference. All of the companies, if they weren't already using AI, were interested in using AI, but many of them were a little bit nervous about it. Not necessarily because of the P doom scenarios of AI taking over everybody's job, but rather about the quality and the cleanliness of their data and the ability for them to have good outcomes leveraging AI from the data that they've been collecting. And so it's a really interesting time because AI requires high quality data to get the best results.

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Kailey Raymond: So, the namesake of the show, Good Data, Better Marketing, I'm wondering, Marbue, if you would be able to define good data.

Marbue Brown: When we start talking about good data, you want data that's not filled with noise. You may have heard the expression garbage in, garbage out. I remember back in my Microsoft days attending a talk that was called Garbage In, Gospel Out, where if you have the wrong kind of data, you can actually have models come out that tell you things that aren't actually true. And so it's important to make sure that you don't have noise in your data, but also that you have ways that you can audit your data so that you can determine whether the information that you're getting out of it is good or is bad.

Marbue Brown: Now, look, it's always good for people when using data to apply the reasonableness test. Because if you see something that looks super odd, too good to be true, these are some of the kinds of things that you have to take a step back and you have to double check. But sometimes your data doesn't always tell you the whole story. I'm reminded of a statement that Jeff Bezos made, essentially that if your anecdotes and your data don't match, maybe something is wrong with the way you're measuring.

Kailey Raymond: Oh, I love that.

Marbue Brown: So, that's one of those things that I think that we really need to think about when we're dealing with our data. But really, the scenario with missing fields, those kinds of things, or just the same thing can be represented in the data five different ways, all of those things make it very difficult to parse data. And so, sometimes it's not so much that the data is good or bad, but it's whether you can clean that data to the extent that some of these problems that I'm talking about, you can dispense with those problems. You just need to know what the likely challenges are and then you need to be able to account for those challenges. And as you account for those challenges, then you're able to do something better with your data.

Kailey Raymond: That's perfect. The fact that you also mentioned anecdotes as a way to really gut check yourself and make sure you're on the right track, right? Like your customers aren't gonna lie to you. They're gonna tell you what's going on with your service. And you and I both know that we can make a data set tell us almost anything that we wanna hear, but being able to measure that up against the actual feedback coming direct from the mouth of your customers is incredibly important. I'm wondering, how does data influence customer obsession? Any tactics you wanna share or anything? Any insights there?

Marbue Brown: I would say, and it kind of goes back to what we've just been discussing, that data is one of the primary enablers for customer obsession. One of the hallmarks of customer-obsessed companies is that they engage personally. And part of what that means is that they personalize touch points with their customers. They also give customers what they want before they know they need it. That's a really important piece there. Okay, give customers what they want before they know they need it. How are they able to do that? How are they able to personalize touch points? How are they able to give customers things before they know they need it? They're able to do that with data, because data enables them to do that. So what it comes down to is making sure that you're capturing pertinent information about your customers and then you're reusing that information whenever they engage with them. I mean, you've heard over and over about how people contact the company, they have to tell the same story over and over and over.

Kailey Raymond: Oh, yeah.

Marbue Brown: Or let me give you another one. How many times have you gone to the doctor and filled out the same old forms over and over and over and over? And this is kind of things that that really frustrates customers. But if you can capture this information and you can reuse it when you're dealing with customers so that the customer feels like, you know what, I love it because this company gets me. That's what makes the experience that much more special. I'm reminded of a scenario from Ritz-Carlton, where a customer went to one of the hotels and she really liked Christmas tree displays and stuff like that, and she mentioned that to somebody she was dealing with.

Marbue Brown: Well, a year later, around Christmas time, during the season, she checked into a Ritz-Carlton and when she got to her room, she had on, the wall of her room, the Christmas tree displays from all of the Ritz-Carlton's around the world so that she could see what they all look like. Now she said that in passing to somebody, and that person took that information and utilized it to create a basically wow experience for her. That's the way that data can be taken, put back into the process and really used to make it a memorable experience for customers when they deal with you and to make them feel like, you know what, this company gets me.

Kailey Raymond: That's so great. And I think the ability that you're talking about as well is that's something so tangible in-person. We talked about omni-channel earlier. They're gathering information and insights about that customer all year long via their website, via their apps, or however, and one of the most impactful ways that they're gathering data as well is with the actual human beings that they're interacting with in-person on site. And so being able to marry that information that you're getting in real life with that data that you're capturing online into one unified customer profile to deliver an incredible experience that is memorable, that's personalization. That is what drives loyalty.

Marbue Brown: Absolutely. And the companies that are great at this have actually created practices and mechanisms that their employees can use. So when somebody is on the phone, an employee could be typing that information in. And so it goes into a database somewhere. The scenario is a little bit different if you're interacting with somebody in a live scenario. But, again, the companies that are great at this have created mechanisms that their employees can use to capture this information, store this information, reuse that information so that it can be really brought back into the experience the next time the customer comes in. Now, there's a balance between being great at this and being creepy. Okay?

Kailey Raymond: What's the balance? Tell me.

Marbue Brown: There is a balance, and so people need to understand that balance and they need to architect to ensure that the information that they're collecting about customers will be information that the customer feels like, hey, these people ought to have about me. But I mean, like if you're having a conversation, for example, and your phone starts talking to you and you think, "Hey, I wasn't talking to you," Well, that feels creepy. You understand what...

Kailey Raymond: Oh, yes. We've all been served those ads before.

Marbue Brown: But I'm just saying there's certain types of things that you can do that feel creepy. You got to stay out of that space. But you really do need to bring into the scenario of dealing with customers, this whole notion of how do you take the information from your interactions with them and reuse it in subsequent interactions to really make the experiences that much more special?

Kailey Raymond: What's really cool about what you're sharing right now, too, is it seems really obvious, like, oh, listen to people and then relay that back and make sure that they know that you've been listening, and it feels like it's authentic, right? But what I think that a lot of the trap of capitalism and a lot of businesses, perhaps, is that it costs money to invest in these customer experiences. And you hope that you're going to get something in return for the bottom line, shareholder value, but at the end of the day, won't that experience, that good experience, in theory, give you tenfold the outcome in terms of dollars? I think that the upfront investment of that might seem scary if you might not know the outcome, but ultimately, you're probably gonna get a more loyal customer and retain them a lot longer.

Marbue Brown: Well, I tell people that customer obsessed-companies, they take actions, they adopt policies and they make investments in the customer's favor, even when they cannot immediately connect the dots to their own financial benefit, because they know that in the end, it always pans out. And if you think of companies that fit the bill of customer obsession and you think of some of the things that they do, their competitors, they cringe. They don't want to go there. They don't think that those things are sustainable. But the truth is that these customers have sustained these behaviors for a long time, and their financials are phenomenal. Costco's return policy, most companies just won't go there. But Costco's financials are not hurting. More people go there and shop there because of the return policy.

Marbue Brown: You look at what Chewy does. Chewy sends out handwritten notes to pet parents. That takes time and money. But I can tell you, many of those folks who get those handwritten notes, they're never going to shop anywhere else for their pet's needs. Or you take Zappos, where their agents don't have any time limit on how long they can spend with a customer. Other companies would say, that's absolutely insane. They don't use any scripts. But Zappos is one of those companies that keeps demonstrating that, hey, these kinds of behaviors work. And can I tell you something about these companies? Their customers are not casual consumers. They're rabid fans. They do the customer's marketing and their advertising for them. So if nothing else, recognize that when you invest in that, you can save some money on the other end, because you're going to have people who are out there evangelizing your message for you.

Kailey Raymond: That is the dream. User-generated content, fan mail coming in your way from these actions that you're taking. I love those examples.

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Kailey Raymond: I'm wondering if you have a favorite in terms of a campaign or a program related to a customer obsession that you wanted to share. You just gave a few great examples, but is there any one that just comes to mind as your top one?

Marbue Brown: It's not so much a campaign, but it's actually something that I used to do when I was at Amazon. I ran something called the Customer Experience Andon Cord. And what the Customer Experience Andon Cord does at its most basic level is give customer service associates the ability to take an item off the site because it was causing a bad experience for customers. Now, look, we automated that. We used machine learning and all kinds of advanced statistical models to be able to pull those items even faster than customer service associates can detect the problem. But customer service associates still have that ability to do that. Now, let me tell you, that inspires trust.

Marbue Brown: I mean, literally, a customer service associate could be talking to a customer about an item, pull the Andon Cord, and the customer could actually see in real time, that item is no longer available for sale. That is something that I believe that has inspired confidence and has enabled customers to keep shopping at Amazon and keep coming back with confidence. So having spent some significant time working on that, that's definitely one of my favorites.

Kailey Raymond: I love that example because you're right. I think the word trust here is really powerful. It's really what we're all trying to strive towards. It's, you're driving personalization, but what does personalization do? It makes it feel like you have an authentic relationship with a person or a company. And what is that based on? Trust. You know that they're collecting certain information about you, you're okay with it, and then it's like a happy little cycle. And it goes back to your point about employee experience, customer experience. These are all beautiful little mechanisms that are creating feedback loops for people. I know we've spent a bit of time talking about AI today, which I imagine is probably on the minds of everybody for the next year or so. But I'm wondering if you were looking at any changes on the horizon, any trends that you're watching out for over the next six to 12 months related to customer obsession?

Marbue Brown: Well, first of all, let me tell you one of the things I would love to see happen with customer obsession, is for more people to really embrace customer obsession as a business strategy. So I did talk about the fact that customer-obsessed companies engage personally, but also they bet the farm on extreme customer-centric policies. And so that's one of the things that I'm looking out for. And to be quite frank, that's one of the things that my company is dedicated to doing, helping companies go in that direction and really jump in with both feet and go after that. I'm looking to see how much adoption in the space of AI there's going to be. I think some people are skittish because they're hearing all of these kinds of things, but I think folks need to recognize, we have been incrementally going towards AI already.

Marbue Brown: There's a number of things that we're using that are already AI. I'm looking to see people ratchet up their adoption of some of these kinds of things that I was talking about, and we're seeing some of it already. I believe it's Wendy's who now is ready to enable an AI bot to take your order in their drive-through. I'm watching those kinds of things. And then really in this employee obsession space, I'm looking to see what companies are going to do to really elevate the employee experience. This has been a tough area over the last couple of years. We've heard all kinds of things. Absolute minimum Mondays, quiet quitting, all of those kinds of things.

Marbue Brown: Let me tell you something, though. In the companies that embrace customer obsession and they embrace employee obsession, they usually, I'm saying usually, not always, tend to do a much better job on these items. We've been a very difficult period since this pandemic, so everybody is navigating challenges. But that ability to mobilize your employees around a North Star, but also for them to feel like you're treating them the way you want them to treat customers, I'm looking to see how that trend develops. Because, to be customer-obsessed, you got to be employee-obsessed.

Kailey Raymond: It's the golden rule. That's great. Marbue, I have one last question to leave everybody on, and that would be, what steps or recommendations might you have for somebody that's looking to join the maturity curve of customer obsession?

Marbue Brown: Well, let me tell you, one of the great places for companies to look is to take a look at their policies. It's great for them to look at their policies and to determine whether in fact they have any policies that would make their employees and customers do a double take because it's so customer friendly. Some of those policies, like I mentioned, people do a double take because they're so customer friendly. Well, if you haven't got any policies like that, maybe it's a pretty good bet you're not customer-obsessed. So you want to join the maturity curve? Maybe that's a place to start. I have a flip side of that. Maybe you should check your policies and if you have any policies that are objectionable, because sometimes there are policies where your employees can't even identify with those policies because they know that those policies don't work for customers. And so, even when they have to deal with customers on those policies, they try to distance themselves from the policy, right?

Marbue Brown: Now, if you have policies like that, you really need to rethink whether those policies are working for you or they're working against you. Often people adopt those policies because they think it will protect their bottom line, they think it will protect the franchise, but they're doing the exact opposite. As soon as customers find a better alternative, they are going to leave and go to that better alternative. So great place to start, check your policies, do a policy review, and see if that's a place where you need to make some adjustments to move the needle.

Kailey Raymond: I love that. Encode it into the policies themselves. Make sure it is embedded within your culture from the very top to the very bottom. Marbue Brown, thank you so much for being here. Pick up the Blueprint for Customer Obsession. I really appreciate it.

Marbue Brown: Yep, and you know what? I'd appreciate it if people want to continue to engage with me, they should feel free to come to customerobsession.net, which is my website, or they can check me out on LinkedIn. There aren't too many Marbue Browns on LinkedIn, I'll tell you that. So folks can check me out on LinkedIn and I'll be happy to engage with them.

Kailey Raymond: That's great. Connect with the one, the only. Thanks so much, Marbue. Really appreciate it.

Marbue Brown: Thank you much.

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