Author Talks: Building consumer trust with Google’s Neil Hoyne

Without effective leadership and a clear strategy, software can only solve so much.

In this edition of Author Talks, McKinsey’s Adam Volk chats with Neil Hoyne, Google’s chief measurement strategist. In his book, Converted: The Data-Driven Way to Win Customers’ Hearts (Penguin Random House, February 2022), Hoyne distills 15 years of analyst experience into marketing and engagement tips for companies looking to boost consumer relationships and grow their brand.

What problem were you trying to solve with this book?

When I was writing this book, [the problem] was really a question: How do companies find growth? I was tired of people saying, “Data will give us growth.” And then when you ask them how, there is a trust that someone else will figure out how to mine all this value from the data that they have.

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When I started looking across large companies, small companies, start-ups, companies in healthcare, companies in retail and in telco, I asked, what were they doing with data that actually helped them grow and achieve the potential we know that data has? That was only the first problem. The second problem is how you get anybody to read a data book? Maybe we have an hour, two hours in our evening, and the question is, do you really want to sit and read a book that talks about spreadsheets and models and technical concepts and math? That keeps data out of the grasp—out of the interest—of most people and most executives.

So the question was: Could I build something, could I write something that was more of a conversational field guide that people enjoy reading, that people are curious or anxious about, and even more importantly, [that they] can make their own? Can [they] almost intuitively learn these ideas without feeling intimidated by data and how technical the concept can be, and then be able to apply their own experience and bring others in their organization onto the same plane?

What surprised you most about writing this book?

The research behind the book, to be clear, is really a distillation of nearly 15 years of working with several thousand companies, of different sizes, across every industry, in multiple countries. And what I was surprised about was really two things.

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First, going back to that original point that a lot of companies felt that more data would solve their problems, you saw mid-cap companies saying, “If we just had as much data as the large companies, imagine what we could do.” [You saw] the large companies actually stumbling over their own feet, saying, “We have a lot of data, but if only we can get a little bit more. If we can only answer this one question, then that will unlock all the value.” But the companies never got there. There was always one more question, something else they needed.

The second part I was surprised about was how often companies fall back, oddly enough, on technology. They were always one software platform, one tool away from unlocking the value of their data, but then they never saw that success.

And I compare it to what a lot of American consumers do when they try to get in shape. The first thing they do is look for a tangible sign of progress. They sign up for that gym membership. They order the expensive home gym for their garage because it looks like progress. They did something that has a tangible impact.

Simply buying something isn’t enough, and companies were falling into the same trap. They were saying, ‘With software, this will unlock all of our data.’

But we also know that consumers who sign up for a gym membership are really only going to go six times in that entire year. Simply buying something isn’t enough, and companies were falling into the same trap. They were saying, “With software, this will unlock all of our data.”

What I actually found in the book is that it’s more around the strategy of data, the processes behind the data, something that can be learned, repeated, and embraced by organizations without having to wait for the six, 12, 18 months that it could take to simply install new software. Software wasn’t the answer. More data wasn’t the answer. It was actually the strategy, the leadership, and the processes that unlock all that value.

You suggest that marketers should focus on conversations instead of clicks. How can this be done at scale?

When we’re talking about the move from clicks to conversations, what we’re really talking about, in its essence, is the movement from short-term to long-term value. To move away from individual sales— individual leads—and look at larger concepts like customer lifetime value, to look at how valuable those customers are going to be over the relationship with your business, instead of saying that they need to spend and do everything right away.

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It just leads to different decisions. It leads to different questions with the data, and surprisingly, the long-term focus [leads to] much better outcomes because you can trust those customers to come back. And, to your question, it works remarkably well. It scales remarkably well because these models that look at things like customer lifetime value work great over large customer data sets.

Larger patterns start to emerge. You have more prospects to target than if you just had a small pocket. So not only is it more intuitive, but it’s also infinitely more scalable than just coming to the office every day and saying, “How can we drive another 10,000 or another 100,000 transactions from our email or CRM list?” Instead, [you should] segment those customers and say, “These are the great ones that we need to pay attention to and lean into. These are the ones that we might want to avoid.”

It also helps when you’re prospecting for customers. If you have two customers equally demanding of your time, being able to say, “These are the customers we want to prioritize and service, and these are the customers that no matter how great we treat them, the models and the data say they’re unlikely to come back.” So, we won’t necessarily turn them around, but we’re going to focus our time and our resources on those customers that are going to bring the most back to us.

What do you think are some of the most important questions brands should be asking?

It starts with the basic premise that companies should be asking their customers more questions. Oftentimes, when we look at checkout processes and we look at lead forms, the questions remain almost unchanged over years at a time: What’s your address? What’s your credit card number? We learn very little past that amount. There’s no curiosity. At most, it’s packed into a god-awful yearlong survey where we’re just going to ask everyone so we can trend something, or a net promoter score which we won’t even hide: “Hey, here’s a net promoter score question: How likely are you to recommend us to a friend?”

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Those aren’t great questions. They may be necessary for dashboards and reports, but what I found is that companies, analysts, marketers, and salespeople have questions to ask, like, “If I could only understand this about our customers, we could do things differently.”

Now, because I promised you in this book something that’s actionable, something that’s exciting—we don’t simply want to talk about the theory and say, “Well, what would some of those questions be?” Let me give you a few examples. One is in a retail setting: “Is this a gift for somebody?” It just so happens that the research shows that for people who are buying a gift for someone else, that’s their first purchase when they’re acquired as a customer. If that purchase is a gift for someone else, they tend to have a higher lifetime value going forward than customers who are buying for their own needs.

It turns out gift giving is a reflection of [one’s] self: “I want to have good taste. I want to be connected with those brands.” As it turns out, those customers will behave differently. What about asking about share of wallet? If you have two customers with equal lifetime value: one where you’re getting 99 percent of their revenue in the category and the other one where you only have 50 percent, you now have a signal to ask, how much more can I get out of that customer?

Or even the lowly survey. A majority of companies will send out surveys to ask people, “How was your experience with our brand? What could we do better?” Well, some professors had a hypothesis: What if asking people that question makes them think about it a little bit more? Where did we fall short? What could we do better? Well, where did you disappoint me as a consumer?

And they thought about the opposite. What if we started a survey by asking customers what they love most about our products and our experience? And they actually found that in a retail setting, customers who were asked that question ended up having a higher lifetime value. Those positive ideas about what they loved about the retailer and their products became salient in their mind. And it changed their behavior over the next year.

How can brands tap into the irrationality of humans to sell their products and services?

The very first step is simply recognizing that this irrationality exists. A lot of companies will sit there and say, “This is how we want to map a customer journey, how we see the consumers behaving. ‘Oh, they’re going to start here, they’re going to look at our products, they’re going to learn more. And after this period of time, they’re going to convert.’”

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And that limits them because what they’re effectively doing is forcing consumers to fit that mold without being curious about all the different reasons why customers leave. They make broad assumptions: “Well, those customers didn’t convert because they weren’t interested in our products” or “They didn’t convert because our ad targeting was wrong. We brought in the wrong people,” instead of saying, “Did they want something that your journey and your process didn’t allow them to have?”

One of the things that I discuss in the book was actually an automaker. And in their mind, the customizing-a-car feature was their shopping cart. This was a way to get people through the final [steps], to see who’s interested, and [based on] how much they were customizing their car, what the end value of that car would be.

That’s how [the automaker] prioritized: if you’re looking for an entry-level car versus a high-end car with all the trimmings. That’s how they would prioritize their efforts: more money versus less. But they didn’t necessarily think, would people actually use [customization] in the way we anticipated? And what they found, far too late and after many dollars spent—or wasted—was that the people who were customizing the highest end cars were actually adolescent boys who were building their dream cars and thinking, “Well, I can’t afford this particular car, but if I could, I would add on everything. Look how great this is.”

Those were the people that they were targeting the most aggressively with their advertising and marketing campaigns. When we take a step back and look just at human behavior overall and how that fits into how we optimize and service customers—there was a great study published that looked at nearly 700 experiments that were run online, testing everything from a new search function to changing the color of a button on a landing page.

The study consistently showed that those behavioral interventions that play to the irrationality of consumers—a product almost being out of stock, for instance—those consistently led to the best performance out of any test, out of any optimization we could run. So this is what that chapter and that concept is about: here is the most powerful tool kit you have for guiding and influencing your customer behavior, and it’s time to fully embrace it.

How can brands offer more personalized experiences?

There was some great data that came out that actually highlighted that consumers were willing to share more data with the companies and brands that they interact with. They were just asking for a different deal. What I generally see is that consumers are okay sharing data, but the first issue is that they want to have trust in the brand that they’re sharing that data with.

Consumers are okay sharing data, but the first issue is that they want to have trust in the brand that they’re sharing that data with.

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They want transparency: How is that data going to be used? They want control—to revoke the permission to use that data. Perhaps most importantly, they want to understand what’s in it for them. I got an email last week from a company that said, “We’re changing our privacy settings so that we can better service you, and because of that, we’re going to start capturing at least 40 different data points on your behavior.”

But they didn’t tell me how it would be used, or what I get as part of that deal. What that’s really forcing companies to do is to reevaluate their relationship with consumers. It’s no longer just a land grab of connecting to as many data sources as possible and sucking all that information in and selling it off. Companies are now saying, “Let’s go to the consumers and see what type of value we have to provide, so that way they’re comfortable sharing that information with us.”

Something important to think about when it comes to privacy is that it affects all companies equally. There’s no way around it. That legislation, those privacy changes we see happening in technology, affect every business. The goal shouldn’t necessarily be to compare your business against the data you had last year or five years ago but rather, how do you capture more data so that you can make better decisions than your competitors? That’s how you’re successful.

The key to that is: How do you build more trust with your consumers? There’s a lot of work to be done in this space. What exactly is the right value exchange for consumers? What do they want? For how much information, and for how long? That’s where companies are starting to invest.

They’re starting to say, “Let's get this right.” Instead of waiting for legislation to come out or technology to change, they’re saying, “Let’s get ahead and realize that that trust will go a long way.” That trust is future- proof. They’re going out right now and saying, “What incentives do we give customers for their data? We don’t know, but let’s start testing.”

And what type of value is most important to customers? Well, let’s start testing those messages as well. And what questions do we need to ask? What’s going to be most powerful? We have the mailing address. That’s great. We have their payment information. That’s great. What other questions can we ask that will change our relationship with those consumers so they see the value in exchanging with us, that we can also then use to transform the way we build relationships with them?

Watch the full interview

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Neil Hoyne on building consumer trust

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