The Data-Driven Way to Win Customers’ Hearts | #230 Neil Hoyne

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Claus Lauter: Hello, welcome to another episode of the e commerce coffee break podcast. Let me ask you a question. What if you can build a business around long term relationship with customers using data to understand who they are, what they need and where to find more of them, that would be great. Wouldn't it be?

So that's what we're talking about today. We want to find out a data driven way to win customers hearts and find out on how to do this. With me on the show today, I have Neil Hoyne. He is the chief strategist at Google and the bestselling author of Converted. The data driven way to win customer hearts.

Neil serves as a senior fellow at artificial intelligence at Wharton school and is on the board of trustees at Purdue university global. He has received multiple patents for his work in marketing attribution and customer analytics been published in notable outlets, such as Harvard business review, and has keynoted hundreds of events in more than a dozen countries.

When it comes. To the world of data marketing strategy, then Neil is the right person to talk to. So that's what I come up to the show. Hey, Neil, how are you today? I'm doing 

Neil Hoyne: great. Thank you again for having me. 

Claus Lauter: Neil, data driven way to win customers hearts, big title, but obviously we can break it down and find out ways on how you can do this.

Maybe to start with, give me an idea, how would you define data? 

Neil Hoyne: Here's how I look at data. I look at data almost as a language. It's a language that helps tell the story of the interactions we have with our customers, with other people, that we can directly observe. So if you and I are having a conversation, we can talk about our likes, our dislikes, how we came to find specific products or companies, our previous experiences with individual brands.

When we're looking at the size and scale of the internet, it's impossible to have those conversations one on one. I guess you could do, it would just take a lot of time. And if you look at your website and you see hundreds of people coming through every hour, then the question is, well, how do you have those conversations?

And really what you see is data is. What's left behind, or I think actually when you look at the the entomology of the term data all the way to its Latin origins, it stands for something that is given something given by your consumers to share those stories with you to say this is who I am.

This is what I'm doing. This is what I'm interested in, and this is how we interact together. And companies just sit there and they collect these stories and this data and then they try to make sense of it to say, well, all right, I have all this information. People have left all these interesting tidbits of knowledge with me.

How do I do something with this? That not only furthers the relationship I have with that person, but also creates some value between us. And that leads to this whole area of data science, which is trying to put rigor and methodology around that practice. 

Claus Lauter: Now, I'm one of these people who I'm happy to leave my data to a merchant in the internet when this data will make my life easier.

So, browsing, experience will be better by shopping experience will be better, but a lot of brands out there just grab whatever they data have. And then they bombard you with things that are not completely related to what you're interested in. Now you're at Google and you're dealing with a ton of data and Google premise is to make.

 The internet experience, with Google better. What's your approach there? How do you think should brands act when it comes to the data usage of their visitors? 

Neil Hoyne: I think there's a few things to unpack. First is let's talk about this value of data. A lot of companies look at data as being exactly that, a valuable asset that they need to collect, which means the absence of collecting that data Has some of them frightened to say, if I don't grab this data right now from this customer, I will be destroying value for my organization.

And so they just go in and vacuum up everything they can, but there's no inherent value simply in capturing it. You need to know how to interpret and how to use that data. And that's where a lot of companies struggle is. They build these huge data warehouses because in their mind, the value of collecting this data should be obvious.

But then when they apply it, they're like, well, wait a minute. What happened? Where is this value I'm supposed to be capturing. And sometimes when they then try to capture some of that value, it's really not in a thoughtful way, which does the opposite. It destroys customer relationships. One of the interesting brands I used to work with actually pointed out to say they had a lot of data on customers, but they actually thought that the value of data was knowing what not to use.

Knowing that if they called the customer the wrong thing, the wrong name, if they gave them the wrong preferences. Then they actually destroy that customer relationship. And so they said, if everyone's trying to throw too much data at the customers, our advantage will be in using less at the end of the day, though, it goes to what you said, which is from the consumer side, if they share all these secrets with you, if they allow you to observe their behaviors, are you, to your point, making that experience better for them?

Do they see something better? So if they share all their shopping habits with you, do they see better recommendations? Do they see better products being developed? Or are you really taking that information and saying, I can charge this customer more because I know they're willing to pay. We always get anxious about that.

I know on travel websites and how some of these travel companies do it is a little bit dubious, but people say if I click too much on those airline flights and I see those prices change, the airline must know I'm interested and they're trying to charge me more. And then we feel we're like, well, I need to open up a new private window.

So that way they don't have that data. And that relationship starts over again to see, do they treat me differently? And really the reason why I'm saying all this is that while we look at data as just being , this capturing of information, there also needs to be trust with the consumer about what you're doing with that information.

 We find ourselves in a really interesting part of data collection right now, where. Privacy rights, especially amongst consumers, are very important. And what do we see? We see exactly to the point that you said. When there's a lot of research that goes out, consumers are willing to share data with companies.

They're in fact willing to share more data than they have in the past, but they are asking for some very specific things. One is, they want to know what the company is doing with that data. Are you sharing it? Are you selling it? Are you going to raise prices? They want to know what's in it for them. So I'm telling you all about my shopping habits.

Are you going to make life better for me? Are you going to make your products more expensive? And they also want to know that if things don't work out between them and the company, that they have the right to pack up their data and walk away without penalty. Just saying, Hey, things didn't go the way I expected.

Can I have my things, my data, my story, and can I leave? And so really when we take apart, a lot of people look at this within laws and regulations, and that's a fine framework for some, but really where companies are served best is to say, you have a customer across from you that's saying, these are the very reasonable things I want.

I will tell you how I buy and what I need. But I just want to know what's in it for me. And can I walk away? And if you're able to manage this relationship, it's less about the technical nuances of the law. And it's really just saying, can you run a good business? That consumers trust and they feel valued.

And if you have that, they will share more data with you than any other competitors, and you will have more opportunities to service their needs than other companies in the marketplace. 

Claus Lauter: A lot of good things in there, obviously with the flight prices. It makes me smile. I continue to struggle. I'm the oldest digital Nomad that you will ever encounter.

And that's a novel hassle for me. It's like, I don't trust these airlines, a very good example. Now, when it comes to and I think. The idea of what you said with some of your, lines is that they rather use less data to be more personalized than use all the data that they have is a very important point.

Now, if you want to convert a customer, how much data do you actually need to find or to convert them into a superfan? What kind of data points make the difference? 

Neil Hoyne: I look at it in two philosophies. One is a lot less than you think. This is not about saying the perfect thing at the perfect time to customers.

It's just about being slightly better than the competition. I joke around oftentimes. I love my wife. She loves me, but I joke with her and I say, sometimes I'm not sure I'm the best person for you. I'm just the best person you found so far. No, she'll deny it. No, no, no, no, no. Okay. But it's the same thing with a lot of consumers is that we often think we need to have the right message personalized at the right time, delivered in the right way.

We need to have all the data. No, we don't. We need to have a better message than other companies that we're competing with so that that consumer believes that you understand their needs better than other companies. That's where it starts. And so what happens oftentimes is we look internally and say, we have all this data.

I often encourage companies to look the opposite way. What are your competitors doing to engage and to meet the needs of their customers? Where do they fall short? And how do you offset it? A practical exercise that we have here in the state of California is individual consumers under CCPA can request from a businesses, a listing of all the personally identifiable information that that business has on that consumer.

Now we often think about this as a consumer lens. Do I want to know what a large retailer or airline has on me? I know a lot of companies that I actually work with them to say, as consumers request that information from your competitors, what are your competitors capturing on customers? And how does that compare against what you know about those customers?

How are your competitors and using that data versus if you had that same information, how would you apply it? And then the next step in the process is not taking all that data and trying to build the perfect relationship, but saying, how can you use some of that data to meet customers in a fundamentally new way?

Now, we think recommendation engines because those are the most prevalent, but even customizing and something I talk about in the book is customizing the email subject line. If you know the first name of a customer, putting that in the subject line of your email actually increases conversion rates, increases engagement with that email, decreases unsubscribes.

Yet I could open up my inbox right now and look at all the commercial messages I've received in the past month and maybe one or two percent of them actually use that technique despite most of the businesses knowing who I am. And so a lot of it is a thoughtful approach to say you don't have to boil the ocean and do something with AI or ML.

You just need to think carefully to say our customers provided us with this data. How do we use this data, even just one piece of data, in a better way to service them? And if you're not using that data, then this is this backstop you need is to say, maybe you shouldn't be collecting it. If you're asking customers information, how do you spend, if I go over into the other room and I were to go to my wife and say, I need a copy of your credit card statement.

Now she would give it to me. But the next question out of her mouth would be why, what do you need it for? I'm curious about your purchases and how much you spend on shoes, or I'm looking to optimize our tax deductions and seeing if there's anything I can write off different amounts of value for the same data.

And how you communicate that with customers is part of this. And so I, it goes back to very basic things, which is out of the information you're collecting, I want you to think, how are you using it? How are you improving that customer relationship? And if you don't need it, then why are you collecting it in the first place?

Claus Lauter: Very good point there. I used to work in hotel business and whenever we were able to address and we actually were trained for that, a regular guest by their name, we would know that the tip in our hand would be higher than usually. And I think that applies still nowadays in the interwebs. And as I said, it's surprising that so many merchants do not use the name in the email communication.

That's basically a very simple thing to do. 

Neil Hoyne: I'm surprised by it as well. And you bring it up. Hospitality is one of the best industries because it's built around servicing the customer. Retailers, as much as they talk about it, it's either relegated to a customer service function or it's all about shipping more product.

How do we optimize the number of products we go after? I'll tell you a fascinating story. I was talking to , That's some of the people at one hotel. And I asked them, I said, how do you engage your customers? How do you filter out information when you're talking about one to one interactions?

And something they said still sticks out in my head today was that they said they're very careful about the questions they ask their customers. They want them to do be organic, but for them, the people standing behind the desk, that's data collection for them. And just, they have that moment. And what they said is oftentimes when you leave a hotel, what will they ask you?

They'll say, well, how was everything? And you as a guest have to then think, okay, do I want to start complaining? And you give them the answer that everyone gives, which is everything was fine. unpack that. That is a wasted interaction. I ask you a question and you provide nothing of value to me.

And so they actually ask people, they say on the way out there, say, was there anything we could have done better for your stay? That's inviting criticism. It's inviting information. And if you criticize that property, if there was some way that you were let down, that becomes part of your CRM file that for every other stay, not only at that hotel, but other properties they own, they will make sure that never happens again.

A manager will be alerted before you come in to say. Don't do this if we haven't systematically removed it from our company. And I love that just because it highlights this end to end process, which hospitality is remarkable for, which is, let's ask a question. Let's collect data with intention. Let's understand how we optimize that question to get the information that is most valuable.

And then let's make sure we take that information to improve ourselves, our processes, and that our customer experiences the value of sharing that information back with us. 

Claus Lauter: On that, I want to touch on AI because that probably can help with that. Obviously, as a merchants, you're not able to ask every customer that's coming in new to your online shop these questions, but AI might be one way to do so.

Do you have already some experience, real life experience on AI is facilitated on asking the right 

Neil Hoyne: questions? I've seen it and I often tell people that AI is a very promising and exciting area, but we have to be very careful, , as practitioners to make sure that AI is not leading the strategy. And here's the way that I would break it apart.

If you're in a business where your bottleneck is to say, I wish I had a way to more thoughtfully engage our customers. Instead of email, I wish I could get them more immediate responses. I wish we could give dynamic messages. We don't have enough people that we can pay in the call center. We need to service these people at volume.

Those are problems that AI can solve. If, however, your organization is on the other side to say AI is really popular, where do we put it in our business model? Then I become a little bit more concerned because AI and technology is driving your business strategy. as opposed to supporting it. And so I always take that step back to say what are the business challenges you're trying to solve and are you trying to solve something that's meaningful or are you just trying to say we need AI because AI is popular.

And it's not to say again that AI and these large language models won't be productive but really to take a step back to say yesterday NFT.

Now, NFTs, at least according to Google search trends data, is at almost one of the lowest points of interest since they first burst onto the market. Coca Cola's lagging a little bit. Disney disbanded their metaverse division. There's still companies that are saying, well, we're going to start taking cryptocurrencies.

There is a challenge around following these trends so aggressively out of the fear of missing out. And so really I say, understand the technologies, but don't lose focus of your business questions. And if your business questions are saying, we can't properly serve our customers, and this is a better way to do it.

Parallel, I draw with this, just something we're all very familiar with, are phone menus. So I called up FedEx the other day because I had a question about a package that was misdelivered. It was delivered to my house instead of the neighbor. It should have gone. Eighty pound package, I couldn't have carried it.

I could not get through FedEx's phone menu to reach somebody. Their phone menu is built. Oh, do I need to ship a package? Do I have a billing question? No, none of these. None of these would let me. Do I have a tracking number? I do, but I'm not the shipper or receiver, so it doesn't let me go any further. And then I call DHL and somebody actually picks up.

This is for a different issue. They pick up right away over the phone. No phone menu. And what a remarkable experience this was for me to talk to a person. And so I always worry about that, to say, when technology displaces people, you may become more efficient on one metric, but are you destroying relationships on the other?

Could you actually measure that? And so I guess it's just a caution to everybody in terms of the path about how we integrate technologies such as AI. Just to say, a lot of promise, a lot of potential. Just don't let it drive your strategy, let it support it. 

Claus Lauter: I love that example with people and specifically marketeers are a victim of that following the shiny object syndrome, the latest trend and squeeze all out of it and not really facilitated in a business, in the best, perfect way.

And then move on to the next one. As you said, NFT is crypto all to the next thing. 

It's not about the customer. The customer lost in the process and, does not get anything out of it. Now in your book, obviously you're touching on all of these topics.

Give me a little bit of an insight. What's the story behind the book? How did that 

Neil Hoyne: come together? easiest way to look at the book was that. It was a series of missteps that companies made. I spent more than a decade of my life talking to companies, talking to boards, talking to private equity firms about the decisions that they make, how they want to sell more products, how they want to become more profitable.

And you start to see good companies versus, I don't want to say bad companies, but let's say underperforming companies. Companies that had a lot of potential that was never realized. And what really happened with this is that somebody asked me, they said, could you just tell me some of the stories of the companies?

I want to learn not from case studies that said, here's a company that did everything right. Could you give me a case study of companies that did something wrong? I want to learn from a group of really smart people who thought that they were looking at the data, that they were making all the right moves, and then went bankrupt.

I want to learn how those mistakes happen because those are the things that are not spoken about publicly. Those are the things that are most valuable. And so I wrote one of these stories, and then another, and another, and it became 20, 30, 40 of these stories. And they all went on a theme of companies that started embracing technology, embracing strategies for strategy's sake, trying to push products.

And all of these companies lost sight in one way or another of their customers. customers are most valuable assets. They were losing touch of these people because they were so focused internally on their own metrics and their own KPIs. And so really what this book does is it breaks down all these stories and you don't have to read every story.

They all certainly come together in a theme, but really each story carries a lesson to say, these are things you should look out for. These are things you should be mindful of your business. And the kind of the greatest testament I had to this was that I wrote these and all these stories are anonymized.

So you're not going to read it. And even though I know the companies, I'm not going to call out who these people are executives were, but I was surprised at the number of people that have called me. After reading the book, and I had one gentleman in particular that came up and he's like, Neil, it's like, I'm reading into the book, chapter 14, chapter 15.

We're talking about this happening with metrics. It's like, was this my company? And I was like, sorry, can't tell you. And he starts mumbling under his breath. It's like, damn it. And then he starts this stream of profanity. He's like, I told the board they were doing this and this and this. And he's like, ah, we could have been better.

Meanwhile, I'm sitting here thinking, I'm like, this story was not about your company. This story was about someone else, but I'm glad you can relate to it and see those challenges. And so, it's really, the book came from a collection of mistakes around companies that lost their connection through technology, through data, with the customers they were trying to serve, and practical lessons we can gain from it.

It's not doing it from a perspective of judging any company, it's just a perspective of, I want you to be better. By learning about the mistakes that are common so that when you see them in your own organizations, you realize where some of the best intentions and best data can lead you astray. 

Claus Lauter: I love that approach.

, I've been in business for more than 20 years and not all the businesses that I started worked out and I learned from the ones that failed. I think that's what you have in your book now. When it comes to e commerce, is there a certain trend that you see right now, or any final thought before we come to the end of the coffee break that you would give our listeners?

Neil Hoyne: I would say is with online commerce, a lot of companies I'm working with right now are struggling to find their footing. In the past, it was, we're going to do exactly what we did last year, but a little bit better, a little bit faster, a little bit less expensive. COVID changed a lot of assumptions as to who these customers are and how they're behaving.

Now for some companies, that's a cause for concern. They're not sure what direction they're going, so they're going to be more conservative than ever. But for other companies, this is actually an opportunity to say, let's try something new. Let's look at our customers in a different way. And maybe this is a time where we actually want to make this change to our business.

And so really the underlying theme here is that a lot of companies are moving from this product and volume centric world to let's build lasting relationships with the customers that not only stuck with us through the pandemic, but are going to contribute the most value for us going forward.

Let's understand who we are and let's finally make that change. And so disruptive circumstances do a lot. They keep us up at night. They make us unsettled in terms of our estimations and our strategies, but you can also see this as a moment to say, well, now it's time to change to what we can do better and all these things we're talking about, the data.

The AI, these ideas of who customers and their relationships are finally coming together where it's possible for businesses, even the smallest businesses, to have a leg up on these larger companies that aren't so adaptive to the changes that we see in front of us. 

Claus Lauter: It's a perfect ending to today's episode.

I 100 percent agree with what you just said. And I think sometimes merchants. Entrepreneurs need to take a step back and look at what they actually do and what they want to achieve and focus more on the customer than on the technology. Neil, thanks so much for your time today. Where can people find out more about you and your book?

Neil Hoyne: My book Converted, is available on Amazon and at booksellers everywhere. It also is available as an ebook. Audible. If you want to listen to me speak for four and a half hours, I don't know if anybody wants to do that. LinkedIn is also the best way. If you have any questions on the book, you can search my name, Neil Hoyne.

Find me. It's where I tend to answer a lot of messages and questions from the customer centric, curious business people and entrepreneurs in the world. 

Claus Lauter: Cool. I will put the links in the show notes and you just want to click away. Thanks so much for your time today and talk soon. 

Neil Hoyne: My pleasure.