How to Find Your Best Subscribers and Develop Relationships That Last with Neil Hoyne, Google Chief Measurement Strategist

 

Not all customers are created equal. The best subscription businesses know the power of customer lifetime value (CLV). They optimize around understanding who their best subscribers are, and then deepening the relationship with those best subscribers over time. Neil Hoyne is an expert at this. As the Chief Measurement Strategist at Google, as well as a Senior Fellow at The Wharton School, Neil helps people use data to win their customer’s hearts. He’s written a new book Converted: The Data Driven Way to Win Customers’ Hearts on this topic, which I read on the beach while on vacation. It’s a book about data that’s entertaining and engaging enough to read on holiday, if you can believe it. We recently spoke about how to measure the full value of each relationship, engage in an ongoing conversation with your best subscribers, and perhaps most importantly, how to find and win new subscribers just like the ones you find most valuable.

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Listen to the podcast here

 

How to Find Your Best Subscribers and Develop Relationships That Last with Neil Hoyne, Google Chief Measurement Strategist

Not all customers are created equal. The best subscription businesses understand the power of customer lifetime value. They optimize around understanding who their best subscribers are and deepening the relationship with those best subscribers over time. Neil Hoyne is an expert at this. As the Chief Measurement Strategist at Google as well as a senior fellow at the Wharton School, Neil helps people use data to win their customer’s hearts.

He’s written a new book, Converted, on this very topic, which I read on the beach while on vacation. It’s a book about data that’s entertaining and engaging enough to read on holiday if you can believe it. We spoke about how to measure the full value of each relationship engaged in an ongoing conversation with the best subscribers, and perhaps most importantly, how to find and win new subscribers like the ones you find most valuable.

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Welcome to the show, Neil.

Thank you so much for having me.

I want to talk about your excellent new book, Converted, but first, I wanted to start by asking you what it means to be the Chief Measurement Strategist at Google.

The easiest way to understand it is it’s less looking inside at our own data and more are looking externally to customers that are using data and saying (We work with 16,000 customers who would be considered our large advertisers.) How do they take the same sets of data, sometimes competing for the same customers and make different decisions? Out of that segment, when you look across companies, across verticals, across different countries, what are the patterns that emerge in terms of best in class and worst in class? The ultimate question we try to answer is, “How do we scale and repeat those for any other business?”

These are advertisers advertising on Google. You’re trying to help them, not just to use Google products but to be more thoughtful about how they connect with those customers.

It would be nice if they spend more money with Google but that is a disingenuous goal when it comes to data because people are always wondering if you have your hand on the scale. In the end, we hope that they find growth using data. If our products are built correctly, they should align to help accelerate that growth but they are not necessarily part of the pitch. If we find growth through email and we don’t have an email product, we will still pursue that if it helps the company.

“The biggest challenge when building fluency around data is the reluctance of people to admit that they have no idea what you're saying.” - @neilhoyne Share on X

Very few of the CEOs and CMOs that we talk to say, “We don’t have enough data.” They usually say, “We have a lot of data but we’re not using it. We don’t know if we have the right data. We don’t know how to best harness this data. It’s overwhelming for us.” What do you do with those kinds of comments that you might hear from them?

You hear data is the new oil with the idea that it’s a commodity that you can collect. Eventually, somebody finds the data in it. All engineers and analysts cringe. I had one CMO and I said, “What are you doing with all that data?” She was puzzled when she looked at me. She’s like, “We are going to hire data scientists to unlock the value of the data.” Most companies lack that middle point between the data and the actual money. What’s a strategy that you can use to grow the business? Dashboards and reports help to consolidate all the data but they don’t tell a good story about what you’re supposed to do next with it.

How do you get that story? Where does the story come from, and who’s responsible for finding it?

It’s two groups or functions. One is there needs to be some type of strategy of the business going forward that the data can reinforce or guide. That’s a lot of where our work sits. It is to say, “Here’s a data set about how to look at a customer or how to look at a particular moment in that business. What opportunities come to jump in front of competitors and grow share?”

On the other hand, you also need people inside the business that can translate that idea, that strategy, to something that every function can understand and participate in. You may work with a frontline salesperson where as soon as you mention a confidence interval, they check out and say, “This conversation is not for me,” which means they’re not going to participate in the strategy no matter how great and understand the data no matter how wonderful and brilliant it may be.

They take a step back from the table and say, “I’m going to go back to doing my thing.” That particular group doesn’t transform. You need that first layer, which is to say, “What’s the strategy? What can we do with this data and direct an organization?” That second layer to say, “How do we get everybody onboard to be able to take their knowledge and their understanding of their business and apply that strategy to their day-to-day work?”

Bringing this into the world of subscriptions, you have all this data around how you acquire customers, how long they stay, when they leave, and what they do where they’re with you to some extent. How do you make that into a good story? How do you explain to your colleagues across the organization what you’re trying to do with the data or even harness that data to make it useful to your colleagues?

I would say there is a number of different techniques. I don’t think I have figured out a perfect model. I wish I did. I would probably make lots of money. I’d have a better book. I love the book that I have but if you can solve the translation question, that is a monumental opportunity. Let me tell you what I have seen work.

The very first thing that we see companies struggle with is to get buy-in from other teams about how they can transform or use that data for their business. With most transformations, when you see something in data, the most opportunistic ones will have winners and losers. You’re moving resources across functions, which means that some team’s priorities will look better. Other teams’ priorities will look worse.

All of a sudden, those people where they’re looking at losing count or budgets become detractors for whatever you found in that data. It’s not uncommon. I have been on projects where you see great insights and say, “Our subscribers are doing this, which means we shouldn’t be doing that anymore.” The team at the losing side of that argument says, “We’re going to run our own analysis. We’re going to bring our own data.” You end up with a poor decision-maker who says, “I have one team here that says there’s more money here. Another team that says there’s less money here.” The average always comes out to be, “It’s inconclusive. Let’s keep studying.”

The first thing is to find a way to bring everybody onboard. We can talk about the specifics of that. That is the first strategy. The second part of it is to make sure that you avoid common mistakes. One thing that I see oftentimes is that we lose connection to the customers at the end. We talk in a language that is unnatural. Oddly enough, a lot of value was unlocked on our team, where we stopped going to executive coaches for presentations. It’s not that they weren’t talented. They weren’t great at what they did but they spoke our language.

When we mentioned something like, “We should use remarketing. Let’s take a look at churn,” everybody knew exactly what everybody else in the room was talking about. All those people were already onboard with the strategy. It was the people outside we needed. The gentleman I work with, this guy, Mark, out of Chicago, does Shakespeare as a career, which is strange. He can make Hamlet sound interesting. He can also make my presentation sound a lot more interesting.

When we’re talking to him, and we mention that, “The statistical significance of this number or we should build this campaign,” he’s like, “Stop. You’ve lost me. I have no idea what you’re talking about at this point because this isn’t the language I use.” Sometimes it’s simply challenging teams to go beyond the status quo to say, “It’s not what you see in your data but how do other teams see it? How do other teams describe that relationship?”

There are two important points that you’re bringing up. One of them is that whatever story you’re trying to tell, there are going to be winners and losers inside the organization. Culturally, you need to pay attention to that. The other one is you need to make sure they understand and care, which is important for data people to connect with their colleagues across the organization. It’s a challenging thing. There’s the left brain side where you’re trying to get to the right answer or be able to explain what your goals are. The other piece is communicating it in a way that people both understand and don’t feel threatened by.

I’ll add on another piece to it as well. The biggest challenge for some companies, when they try to build this fluency around data, is people are reluctant to raise their hands and admit that they have no idea what you’re saying, especially with basic statistics and math. They’re like, “I should know this as a VP of the organization but I don’t want to tell my team I have no idea what’s going on.”

They sit silently and nod. Occasionally, they jump in. I had a story. I was working with a CMO, and we were presenting an analysis. I brought in a data scientist, a relatively new one who started presenting a whole bunch of things in technical terms. The CMO raises his hand. He’s sitting there quietly. He looks and he’s like, “Did you use Base Z in this analysis?”

I sat there and like, “I don’t necessarily understand what he’s saying and the data science.” That sounds like a statistical term but I don’t know what that means. He cracks a smile. He’s like, “I have no idea what you’re talking about but that’s how I sound smart in meetings.” I looked it up. “Does anyone understand Base Z? It sounds like it’s related to statistics. Everyone thinks I’m smarter than everyone in the room because they don’t know how to answer my question.”

That’s terrible.

That’s his approach. I’m still friends with him. He’s like, “I don’t know what you all do. It’s either you can explain it to me or I need to trust you. I’d prefer to understand what it is you’re doing so that way I can participate.

A key thing that I hope people take from our conversation so far is if you are in a meeting and you don’t understand something, ask. Most of the time, not only don’t you look dumb but everybody else in the room is saying, “Thank goodness somebody asked. That person is pretty smart because they caught me. I was getting off into a realm that wasn’t relevant for the conversation.” Ask questions when you don’t understand. Raise your hand. You’re doing yourself and everybody else a service. You’re keeping the speaker honest.

You wrote this excellent book, Converted, which I read on vacation. It’s an amazing thing to have a business book that you can enjoy on the beach. It was fun, lighthearted, easy to follow, and full of practical tips and tricks, and almost no data speak. Congratulations on writing a book that was so easy to read and yet so full of valuable insights. What prompted you to write it and to write it in this very approachable style as opposed to writing it for your peers?

The style was front and center. For a lot of the sections in the book, in some cases, the introduction took almost six weeks on its own. If we’re talking printed pages, maybe eight pages. The reason is that you simply accept the reality. People don’t read data books, so the very first thing was to say, “I need to write a data book that’s accessible.” The subtitle of the book, The Data-Driven Way to Win Customers’ Hearts, was a long debate with the publisher to say, “Should we include data even in the title?” Do people see that and say, “Here it is, another data book, not for me,” and write it off?

We also wanted to add to say behind this conversational tone and engaging approach to measurement and analytics, there is a lot of math behind it. There’s also a time and place for it. Everything you’re reading about in the book is backed by research and data. It’s not what we need to talk about now. We need to talk about the strategies that any manager can embrace to say, “This is me. This helps me lead my organization and my team. I don’t need to get bogged down in the weeds.” I emerge on the other side with the confidence to say, “I know how to lead these teams. Now, I know to participate in the conversation and how to demand more than simple dashboards. That should hopefully be better for everyone.”

The first section is about asking questions. I love that you start with that. That’s not even most people wouldn’t even think of that as data. That’s asking good questions. You give the example of getting married. Can you explain what you mean by thinking about the questions you ask a prospect in the same way that you think about getting married?

I look at all of these engagements as customers. I put them in the lens of human relationships. I do that because that’s approachable. Everybody has their own stories and interactions, something that they can provide and ground their relationships with. If you start with data, you’re starting to say, “Let’s talk about unique visitors, time on site, and bounce rates.”

All of a sudden, you’re stuck in this language of data. What we have here going on with our customers is the equivalent of courtship. They want us to trust them. How do we build that trust? When you start looking at things in that lens, other behaviors make sense. For instance, I was always told when I was dating that you shouldn’t call a woman right away. You need to wait a couple of days. Give her space.

 

You say, “Why do digital marketers do that? As soon as I leave your website, you start sending ads my way. Are you that desperate for my attention?” The data says people are less likely to subscribe and be your customer if you approach them in that way.

Instead, if you give them space, you wait to 48 to 72 hours, they are more likely to reengage with you. These stories and these connection points allow us to ground how we understand customers and to realize there’s a very human relationship on the other end. We don’t see those people. We translate them through numbers and spreadsheets.

What I loved in that analogy is we all know that you don’t walk into a bar, find somebody that seems attractive to you and say, “I like you. Why don’t we get married?” You don’t go out with them the first time and say, “Would you like to get married?” They say, “No.” You say, “Let’s go out again,” and then on the second date, you say, “Do you want to get married now?” You get to know them. You ask them other questions. You engage them in other ways. Maybe you go to a movie, meet the parents or talk about your life goals. There are a lot of different ways of asking questions getting to know the other person.

Let’s even unpack that a little bit. What are we talking about? The first thing we’re talking about is beyond anything else, having the confidence that you can make relationships work. Where a lot of companies go astray is they lack that confidence. We don’t use these terms in marketing. We use accountability. It’s to say, “If I spend time meeting somebody, are they going to marry me or not? I need to know that right away, so I’m going to ask.”

I would say, “No, give it a little bit of space.” Organizations have loved that immediate gratification. Now I know somebody clicked on my ad and they bought but that’s only harming you. Have a little confidence that these techniques will work. That’s number one. Number two is to participate in the conversation. Here’s what happens when we talk about asking questions, a lot of companies immediately go towards, “You’re saying I need to collect more data from the customers.” Yes, but in a different way. What’s the traditional model?

The traditional model is you don’t ask the person you’re sitting across from you. You’re not asking the customer for more information. You’re going to third parties. It’s like you’re sitting across, and you’re having a great conversation with the customer. Instead of asking them what direction things are going or what they’re looking for, you say, “I’m going to pay my friend to tell me. They really like me. Do you think they’re going to buy it? Who else are they talking to?”

That’s also not natural. The alternative is simply where I want to encourage companies to say you have to be more flexible and engaging with customers to ask them where they are in the process, “What you can do to improve, personalize that interaction, and be confident that you’ll get that information back?” I want you to think the next time you’re interacting yourselves on these different websites and when you’re buying from companies, how few questions they ask.

They’ll ask, “Here’s what I need to sign up for your subscription. Here’s what I need to get you through the checkout funnel. I’m scared to ask anything else because you may leave me.” What the data shows is that after somebody subscribes and they purchase from you, that’s the highest their trust is going to be at that moment. They gave you money and a phone number. Things are going great. It’s yours to lose. The Thank You page is what? “Here’s your confirmation. Here you go on your way.” That’s the time you’re supposed to respond.

What should you have on your Thank You page? What would be an example of something that you should have? I signed up. I subscribed. I bought my first product. What happens then?

Generally, I’m a big fan about flexible questions, which is empowering your organization for anybody to ask the questions and try to capture data that can encourage and build new hypotheses for your business, not tying everything up in a single annual survey but to say, “Let’s have a thing.” We’re going to try different questions. Some may work well, and some may not.

The first thing is the Thank You page is going to become our playground to ask. “What do I like to ask? I like to ask about the share of wallet.” Southwest Airlines does a fantastic example of this. Every year or so, I’ll get a survey that says, “How much are you spending with other airlines?” If you’re looking at the value of a subscriber, you want to know how much are they spending in a category. If they’re already giving you all their money, that relationship is in a good place.

If they’re not only giving you a portion of the time and it’s going to someone else, I want to be curious as to why. What can I do better to service your needs? Why are you not having your needs met by another party? What can I do to be better? Another question I like to ask comes as part of surveys, and this is one that’s mentioned in the book, which I love because it becomes so intuitive and powerful.

On surveys, people generally ask, “Where can we improve? What can we do better?” What did some professors think? They said, “Human nature is when you ask somebody, ‘What can I do better?’ they start thinking about all the ways you let them down.” If I go to my wife and be like, “What can I do to be better?” She’s going to be, “You should have picked up the kids. You should have cooked a better dinner.” She doesn’t complain at all. When we ask people negatively, they think about the negative.

They would say, “What if we turn that around? What if we ask people about the positives? What did we do right? What do you like about our offering? What do you like about our company?” As it turns out, when they ask people that question, they were able to measure effects for more than a year and a half later that those customers ended up being happier, having higher lifetime values, and subscribing to more products and services. That’s from a single question that carries almost no risk in something that all businesses do but haven’t asked.

Where do you ask that? Is that once a year question? Is that a Thank You page question?

The effect was measured on surveys. They took standard ten-question surveys, and they put that question on top. You still had the same 10 but now you had 11. That’s how they did their test in control groups. In other cases, I would have no issue putting it on the Thank You page because the psychological effect should be equivalent. There’s nothing special about it being in front of those other ten questions. You need to ask, “What do you like?” It is a nice word to say, “Give me a compliment. Tell me what you love about me,” but in a more balanced way.

Those are three great tips. Use the Thank You page, ask about the share of wallet, and ask what we’re doing well instead of focusing them on what we’re doing wrong.

“Why am I a bad match for you? Tell me.” We’re on the path of self-improvement but it seems an odd question to ask somebody individually.

“After somebody subscribes, after they purchase from you that's the highest their trust is going to be.” - @neilhoyne Share on X

You talked a lot at the beginning of the book about how to ask good questions. You talked about asking good questions as if you’re talking to a real person, thinking of this as a relationship where you want to learn about them over time or it’s not a once-a-year thing. It’s not a one-undone, which very much aligns with how I think about subscriptions. How do you do that at scale? How do you do that when you’re trying to reach a million people and make each one feel like you are carefully and thoughtfully developing a personal relationship with them?

I was talking to a very successful restaurateur in New York City. Until I thought about it, he was challenging the notion of what Silicon Valley calls “scale”. He said, “In Silicon Valley, the idea of “scale” is that you’re going to build a product that can deliver services to millions of people. That’s a scale they look for.”

He challenges that the real definition of scale is being able to deliver the same type of service, experience, and relationship to 1 person and delivering it to 2, then 10, then a million. It challenges us to say if we had one person come to our website, that was our entire day, and we can have that relationship with them. How do we then embrace the two tools and techniques that can offer that same service and level of conversation to future visitors?

The definition grounds us to say we shouldn’t be making compromises based on technology but let’s talk practical tools. What are companies doing? The first thing is the language of the company has to change where they’re talking about people, things that are valuable, and understanding the relationships instead of calling people unique visitors or we’ve received.

The language matters?

The language matters because that’s how we condition and treat it. When we talk about things like clicks and conversions, what are we doing wrong? We’re almost commoditizing it. We can get more people anytime we go out into the market, and we increase our budgets. There are only so many people out there, and you’re turning away great people, so use that very human language.

 

The second part is to look for those types of tools that allow this scale to happen in a more natural way. This is where machine learning fits in, artificial intelligence. What’s it supposed to do? It’s supposed to take all the patterns, all the conversations you’ve had in the past, and tell you what to focus on. What are the moments that truly matter in the relationship? When you’re looking at your website behavior, you may see someone bounce in between 30 different pages.

Machine learning is going to have the best avenue to say, “Which of those moments do we think something changes? What should you pay attention to?” When you see a lot of research that comes out, they’re using those techniques. I’ll give you an example. A lot of companies focus on adding something to a shopping cart or starting the checkout process to say, “They’re getting serious.” That’s the next step in the flow. It’s to say, “We had a date. They’re giving me their phone number. We’re having a second date. Things are progressing,” which may be true.

At the same time, they turn away other softer signals they should pay attention to. At least in the retail setting, people that remove things from their shopping carts, that’s a sign of curation. We may think, “They’re saying no. They’re pushing back.” No. They’re being more selective with the products they want to buy. It’s nothing to walk away from a website. It’s another thing to come back.

That is an interesting point. One of the things that I encourage companies to do when they’re thinking about their product offering for a subscription is to start by doing it in a very manual way. When you think about the example you gave, if I’m in a store, walking around, I got my shopping cart full and start to take 1 or 2 things, if I’m done with the store, and I don’t find anything I want, I’ll abandon the shopping cart and walk out.

If I’m saying, “I’m going to take the red blouse out and keep the green one,” that means that I’m taking it more seriously. If you think about that logic of what it’s like to be in a store and say, “I’m shopping online. Does it mean the same thing when I take something out of my shopping cart?” You start to have those a-ha moments.

It totally speaks in terms of treating the user as a person and not thinking about clicks but thinking about actions and trying to understand what’s going on in their mind or journey to accomplish something. What any purchase decision is, “I have a goal. I’m trying to accomplish something. I want to look beautiful, so I’m going to buy some new clothes. I want to get fit, so I’m going to join a fitness program. How are you going to help me get there?”

“When somebody asks what they can do better, they start thinking about how you let them down. What if we ask people about the positives?” - @neilhoyne Share on X

I hope, for all the readers out there, that the takeaway isn’t in our customer funnel. We should have removed things from the shopping cart. Don’t make this a linear process. The larger takeaway is to encourage and establish that curiosity. What you’re doing is you’re setting the stage. This is who you are as a company. This is what you’re offering to consumers. You can guide them. You can have your expectations but consumers are going to do things that surprise you. If your path is to say, “I want to force them to think how I think they should act,” you must go through this page next.

That’s what I want people to get away from. Where the real value comes in is saying, “We’re going to set our stage here and let our customers interact the way they want to interact. We’re going to be curious about why and what we can do better. We’re going to open our minds. People are going to use products in ways we never anticipated. They’re going to use our website in ways that we didn’t plan. We’re not going to try to corral them and say do what we want.” We’re instead going to understand why and how we have better relationships by adapting to what our customers are saying they need.

That goes right back to your original point around asking a lot of questions and being curious. If somebody is taking stuff out of their shopping cart, maybe ask them. I don’t know if this is a good or a bad idea. You can tell me but if you’re at that Thank You page, I had a green blouse and a red blouse. I dumped the red blouse, and I checked out, “Thanks for shopping with us, Robbie. Why did you dump the green blouse?”

What happened?

Was it, A) Because you were getting ready to leave us and somehow we won you back or was it, B) Because you were optimizing which one am I going to wear tonight?

Look at the opportunities and draw a list. We didn’t cover all of them in the book but there are some retail sites that say, “We’re going to mix up our categories for return visitors. Give them a new way of experiencing us, not here is men’s, women’s, kids’ but as you brought up by occasion and what are we going to get? More curiosity from the consumer, which is what they find. They increase engagement with products but also signal to say, “What are you looking for?” “I’m looking for work clothes.” We didn’t get that when you went into women’s and separates. Now we have that understanding.

Look at companies that optimize menus. Starbucks does a great job dropping the currency sign from their menus to make people less anchored by price. That’s something we can try on our website. Let’s not remind people of price. Even the way people interact with products by zooming in and looking at the texture, size, and color of products generally is an indicator to say, “Are they going to be happy with their purchase? Are they going to call customer support right away and incur more costs for your business?”

When you talk about, “Are they going to be happy with their purchase?” If they’re not happy with their purchase, the chance of them coming back goes way down. The lifetime value declines. You’re a big believer in optimizing for lifetime value. Can you talk a little bit about why that is, what that means, and why it’s important? In the world of subscriptions, it’s something we talk about but it’s true in almost any business.

I look at it from a very simple human lens. I meet a lot of people in my life. Some people are very close to me, my wife, my family, and close business associates that provide so much value to my life that I simply couldn’t do without them. They change my life and how I respond. I certainly want to find and build relationships with people like them.

On the other hand, there are people that you’ll meet only once or twice in your life. It may be a flight attendant or the Uber driver that took you to the airport. You’ll never see them again. They’re great people, and they had that moment. First of all, imagine how different your life is if you don’t understand and identify those relationships and you don’t spend a little bit more time, if you haven’t seen a close friend or family member in a while, if you don’t reach out to them or even worse, if you think about the other side. What if you treat everybody equally?

What if you go out and you’re like, “I have to make an important career decision. Do I ask my family or do I ask the Uber driver?” I then average the two answers together. The reason why I say this is because practically speaking, when we look at how companies build out their subscription sites, what do they do? They’re going to run an AB test. They’re going to say, “Do people like the red button or the blue button? This creative or that creative?” They then treat everybody equally.

They say, “The family member is worth as much as the Uber driver.” Even though the family member is going to come back and be with us forever, we’re never going to see the Uber driver again, and we’ll average their results together. When people start looking at their business from a lifetime value lens, it allows them to prioritize opinions, data, and questions a little bit more. We want to listen to these people and build for them. We don’t want to turn these people away but we’re not going to put as much emphasis on their opinions even if we ask.

Listening to the customer doesn’t necessarily mean listening to every customer equally. It means understanding who your best customers are and optimizing for more of them for them to be happier. This is very much, in the role of a past guest that we had on the show, Peter Fader, a friend of yours and mine, who talks a lot about this concept of customer-centricity.

You talk about this in your book. You have a whole section dedicated to a very practical way of incorporating customer lifetime value into your work by segmenting your audience. Can you talk a little bit about how to do that and where to get started if it’s something that you’ve never thought about before as an organization?

 

The first practical step is certainly to calculate it. One of the things we talk about in the book is best-in-class practices. If you search how to calculate lifetime value on Google, you’ll end up with 3 to 4 pages of poor results. The first thing was to clear the air to say, “Not only here’s how you calculate it but to give everyone confidence that they can calculate it without it being a month-long effort, that it is relatively straightforward and proven in these models.”

The second thing is, once you understand who your great and customers are, understand why. “What makes them different?” Was it where they came from, the time of day, a promotion, a coupon code that you had, the products or services they were interested in early on, “Who introduced you, or maybe the agent they spoke to over the phone that won them over?” That’s the next question. That helps you to build that profile.

Behaviorally, what makes people different? Afterwards, you have three choices. You certainly can go out and acquire more customers. You can develop the customers that you have a little bit further or you can retain the high-value customers that you have now. That’s everything past that point. It’s walking people through to say, “Here’s what options are available to you to acquire more of these people. Here’s what we can do to develop them. Here’s what we could do to retain them,” all with a little bit of segments to say, “Here’s how far you can push these rules before things start to break.”

For instance, you want to acquire better customers. You don’t necessarily want to say, “We’re going to go after the very best customers, no matter how attractive,” instead, you simply want to meet better people now than you did yesterday. Those rules are put forward, so people know, “Can I save a little bit of time by making sure I learn from the best and worst practices in the industry?”

When I think about the companies that I work with, I felt like this was one of the most important sections of the book, this idea that it’s not that hard to segment your customers by value. You break it into four quadrants. You can use a few data points as a starting point and use some hypotheses to start to figure out what’s different in quadrant 1 than quadrant 4.

Start to tinker on the margins so that you’re spending a little more in the channels that attracted more of the quadrant 1 people using those messages a little more and a little bit less in quadrant 4. One of the things that I hear companies talk about is they say, “It seems very risky to segment and go after quadrant one.” That’s not what you’re saying. You’re very explicit about that.

I’m clear about it because was that dramatic? Imagine you’ve built your business on whatever strategy you’ve had for years, and then all of a sudden, the CMO comes and says, “Everybody stop. We’re going to go after these people.” You’re like, “We’ve never reached out to these people. We don’t know how to message him. We haven’t learned this conversation with them. We happen to gather them. How hard could this be?”

Instead, you say, “Let’s take everything you have. Let’s not try to reinvent your business. Let’s try to nudge you in a better direction so that you make more money. If that will work, we can do it again.” We find teams generally are more accepting of that change and something overly dramatic to say, “No more doing this, only doing that.” That’s far too binary. It doesn’t lead to a lot of success.

At the same time, not all customers are created equally. If one customer is worth $40 and one is worth $200, don’t say the average customer is worth in between. Understand the difference between the $200 our customer and the $40 customer but be gentle, curious, and experimental as you continue to optimize around those higher-value customers.

You don’t need to abandon the lower value customers and say, “Get away from my business.” Maybe you don’t want to spend as much marketing investment on them. During that time, you want to prove to yourself to say, “If we believe these customers aren’t going to come back, let’s take a couple of hundreds of them. Let’s stop marketing to one group. Let’s continue marketing to the other and look at the results.”

The reason we do it is not because I lack confidence these techniques will work. Sometimes you need to prove it to your organization that they do. That way, you can make iterative changes. You can learn from it. How do these people respond? You can move forward with the next test. That way, you’re keeping yourself lightweight and nimble in your learning as you go.

The systems you need to do this aren’t that sophisticated. You can use a pretty straightforward spreadsheet. You don’t need to have tons of data on your customers.

A lot of people think, “I need big data systems. I need cloud.” I’m like, “Most of the work I do is in Excel. It’s easy to work with but that’s also why these techniques rise to the top. Do you want to go out and buy a new enterprise system takes eighteen months to install? That would be disappointing. Thank you for reading the book. For the next eighteen months, you’re going to be doing the exact same thing we started talking about not to do, collecting and organizing more data. Let’s use Excel and get into work.

This is also an important takeaway. Start getting curious about your customers. Ask them more questions. Try to understand who the best customers are using the data you have available now. Use your Excel spreadsheet. Don’t worry about saying, “We’re not going to do this for two years while we evaluate, vet, build our new big systems, and hire as the data scientist to give us the answer.”

“Data scientist, go do your thing.” You’ll never hire any good data scientists if they find out that’s the job.

The last thing I wanted to talk about with regard to the book is culture. I love that you dedicated a chunk of the book to talk about how to build relationships. What I see with a lot of companies that move, let’s say, from transactional models to subscription models, which almost by default are more focused on customer lifetime value, long-term relationships, all the things that you talk about.

People within the company don’t understand what the subscription people are talking about. When they understand it, they’re threatened by it. Those are the two parts. There are winners and losers in terms of who gets the budget, who gets the headcount, who gets to be the hero at the exec team meeting. What have you learned in your work at Google and in your work more broadly working with hundreds, if not, thousands of companies about the cultural piece of moving to this model?

“Two great tips: use the thank you page, and ask about share-of-wallet. - @neilhoyne Share on X

I’ve learned candidly that even if you have the guaranteed right answer, there is a 50/50 chance that companies will accept it. That’s what it is. I’ve run experiments that show, “Here’s a company that can make 5 or 10 times more revenue, proven in a best in class methodology and still come like, “Our data is a little bit different,” and they ignore it.

This is the reality. We tend to trust ourselves and our intuition more than we trust data. We don’t admit it. We don’t think how data wins. Data rarely wins. It’s oftentimes the people in the room that will make that decision. What that last chapter is about is to say, “If you want these ideas to take hold, it’s more than learning the principles. You need to learn who’s on the other side of the table.”

We touch on the best practices. What are the core areas? One is this idea, this theme we spoke about around incremental improvement for your business as opposed to chasing a perfect answer. We talk about the need for experimentation to collect data, build confidence in what you are doing and the changes you’re making. The models that you’ve constructed are, in fact, leading to better profitability.

We talk about how you get other people in the organization on your side. How do you get that agreement to make sure that when you’re running these tests and implementing these models, people aren’t going to be threatened in that transformation, and they have the opportunity to grow? The fourth and perhaps most important area is, how do you bring other people in your organization along with you?

How do you make them evangelists of your work and what you know as opposed to simply coming along and saying, “What does Neil say is the right answer,” and they do that? If you don’t do that, you undo that entire storytelling aspect we started with. They’re not able to participate. They’re not able to use their experience to help you ask better questions, formulate better insights, run better tests, and being able to educate them on what you see in the direction you should go so that they can participate and add value themselves.

That’s the secret sauce. There are lots of smart people out there who can tell you the right answer. The hard part is bringing together a team to support implementing that knowledge.

We’re only human after all.

I want to close out with a speed round. Are you up for that?

 

Let’s go.

What is the first subscription you ever had?

It would have to have been a newspaper at that point. I’d probably say the New York Times. If not that, I’d say maybe Nintendo Power when I was a kid. They had that magazine. It was a big thing when I was five. I’ve got the inauguration but that wasn’t my subscription. That was my parents’s.

What is the subscription you get the most enjoyment out of now?

I’d have to say Netflix. It’s not any good movies. It’s just because of my kids. I have a 2 and a 5-year-old. They love Netflix. Nothing makes them happier than watching cartoons with me.

What is your best advice for a reader spending a significant budget with Google on advertising?

Trust anything your account team says. The best advice I have with anybody spending time with Google if you are working directly with Google, you should be. Let the people on the other side know what success looks like for you. Oftentimes, especially with advertising platforms, they send over too much data. “Here’s more data and case studies.” They don’t necessarily know the burden of proof in the organization to say, “How do we build that trust? What do you need to see?” That way, the information and guidance they’re providing are speaking the language of your business.

That’s helpful. What’s your favorite question to ask a new customer in general?

My favorite question to ask is probably the one that I already brought up, which is, “What do you like about us?” I gain a lot of insight from that question. The worst question I ask people is, “How did you hear about us?” As you put in dummy answers, people will select channels that you’re not even marketing on. Sometimes, it can be difficult to get honest answers in those categories.

My final question is, what is your favorite underused metric?

We’ve spoken so much about lifetime value. I have to throw it in the mix because people don’t look at it often enough. They’ll spend more time on new customer rates, which is our garbage bounce rate. I don’t know what you learned time on site. It’s like, “Why aren’t you looking at lifetime value customers?” “We’re too busy looking at CPA or ROI.”

It says, “Look at what your customer’s worth even if you don’t use it or you’re not going to bid on it. Know it’s there.” If you have a conversation where everyone is saying, “Look at the CPA of our campaigns. Look how much it costs for each new subscriber.” Somebody puts up a column next, and you’d say, “I know we’re not bidding on it but how come these subscribers are going to stay longer than those subscribers?” I love those debates within organizations. There’s no pressure because you didn’t tell anybody to use it but I want people to start asking why.

That is fantastic advice. It’s been a pleasure to talk to you, Neil, as always. Thanks so much for spending time with me, and congratulations on a terrific new book.

It’s my pleasure. Thank you so much for having me and for the wonderful questions as well.

—

That was Neil Hoyne, Chief Measurement Strategist at Google, as well as a senior fellow at the Wharton School. Neil’s new book is Converted: The Data Driven Way to Win Customers Heart. For more about Neil and his book, go to ConvertedBook.com. For more about Subscription Stories, go to RobbieKellmanBaxter.com/podcast. If you like what you heard, please go over to Apple Podcasts or Apple iTunes and leave a review. Mention Neil and this episode if you especially enjoyed it. We read all the reviews because we want your feedback. Thanks for your support and for reading

 

Important Links

• Neil Hoyne, Chief Measurement Strategist at Google, Senior Fellow at Wharton, Author of Converted: The Data-Driven Way to Win Customers’ Hearts
• Converted Book
• Uber
• Subscription Stories Episode with Peter Fader
• New York Times
• Nintendo Power
• Netflix
• Machine Learning
• Customer Lifetime Value
• Data Science
• CPA
• ROI
• RobbieKellmanBaxter.com/podcast
• Subscription Stories: True Tales from the Trenches on Apple Podcast

 

About Neil Hoyne

Neil has served as an analyst, researcher, inventor, lecturer and, in his words, the father of many forgettable slides of glossy funnels and Venn diagrams. A witness to and participant in billion-dollar successes, and instructive failures, all in the pursuit of building indestructible customer relationships through digital media. A key player in the executive rallying cry to be more “data driven.”

As Google’s Chief Measurement Strategist, Neil has had the privilege to lead more than 2,500 engagements with the world’s biggest advertisers. His efforts have helped these companies acquire millions of customers, improve conversion rates by more than 400 percent and generate billions in incremental revenue. Immensely proud of the degrees he’s earned from Purdue University and UCLA, Neil returned to academia in 2018 as a Senior Fellow at the Wharton School of the University of Pennsylvania.

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