Why Community is the Last Great Marketing Strategy
January 19, 2023
Neil Hoyne: Hi! I wrote it because my experiences in marketing—all the advertisers I helped get the most out of their digital marketing, all the stories I heard—pointed to a problem. Customers are the most important thing to any business, but especially during the pandemic, most companies have lost touch with them.
For airlines and hotels, with customers on lockdown: Will they ever come back and fly or stay with us again?
For car companies that found themselves short of inventory: Are the people who are showing interest in our vehicles truly interested—or are they just signing up for everything that’s available in hopes that someone somewhere actually has a car to sell?
For retailers: Are people still willing to pay full price or do we have to develop products to meet them where their income is right now?
Companies everywhere are trying to answer these questions or questions like them. And unfortunately they can’t. They don’t know how to, because their historical data isn’t much help.
That’s where this book comes in. It’s a field guide to finding your way in the post-pandemic wilderness. Basically what it says is let’s take a step back and refocus on, re-engage with our customers, and understand those who are going to drive the most sustainable value. My book, Converted, shows you how to do that. It provides a digital marketing strategy any business can follow in an unprecedented time where companies are grasping for different ways to grow.
Neil Hoyne: Well, the Introduction is the place to start! I’ll often send it out to people because I think it captures the spirit of the book: entirely candid, brutally honest, hopefully a little bit witty and perhaps even self-deprecating—and accessible. It’s not trying to sell you on a concept or a framework as much as it is to engage you in a conversation about an opportunity that is out there, just as if you and I sat down in a café for a cup of coffee and spent four hours together. That’s the length of the audiobook. Four hours together, talking about connecting with your best customers with someone who has studied thousands of companies, countless business models, billions of rows of data, and has made a lot of money doing it. Let’s sit down and have that conversation.
Here is a passage from the Introduction that shows what I mean:
A Digital Marketer Walks into a Bar …
… and asks the first person they see to marry them. Crazy, right? But that’s what companies do. That’s digital marketing. And if the marketing team asks enough strangers the question—maybe it’s a hundred, maybe a thousand—eventually someone will say yes. The marketers give themselves one moment, one opportunity to drive a result, and they treat every interaction the same. They can only change so much—what they wear, which bar they walk into, maybe a word or two in what they say. And then the CEO asks: Why aren’t more people saying yes?
Because others are playing a different game. They say hello, they start a conversation. They ask questions, actually listen to the answers, and let things develop. They begin to build a relationship, one step at a time, and then they ask themselves, “Is this going anywhere?” Their data tells them the answer—and they act on it.
Neil Hoyne: AI and machine learning have been with us for quite some time. The foundations are reasonably established. What’s emerging are new ways of broadening the conversation by making AI more accessible. It’s no longer limited to somebody who says, “We’re using machine learning to predict the stock market!” The science and the application are very difficult to wrap your head around—although you have a lot of respect for the people who are doing it. ChatGPT is a more recent example. It’s a stunning example of AI that everyone can interact with.
The other day, my wife was struggling to write a letter to a company whose product was giving her trouble. She sat there on her email, trying one draft after another. None felt right. So she went into this tool and asked, “Could you write me a letter to a customer service team explaining these three issues?” Within seconds, it wrote five paragraphs of clear, concise thinking. Brilliant!
It wasn’t just that ChatGPT saved her time, or that its letter was probably more effective than her own writing. Suddenly she connected the dots to say, This is where AI fits into my life. This is how I can participate in those conversations.
In technical areas, we don’t spend enough time simplifying the story to show people how it’s going to change their life. Tools that people are excited to interact with, excited by the possibilities, suddenly make this very cutting-edge tech accessible. That’s really the gap that these technologies have to cross in order to be successful.
With this emerging spirit, I think AI and ML have taken a large stride towards businesses, towards marketers, towards consumers in understanding how it can influence their world.
Neil Hoyne: I’d say it’s simply to understand the differences between your customers. Customers and the relationships we have with them are very similar to the relationships we have with people in our own lives. Some people give us a lot of value; others give us very little. Unfortunately, most businesses treat all customers the same. It’s a noble goal, but it’s not the reality. Even if these businesses don’t have the power to act differently with different customers, they should at least have the curiosity to ask, Who are going to be the customers that I need to keep, that I need to understand, that are going to sustain my business? And what can I do to serve them better?
Those are questions everybody reading this article should ask.
Neil Hoyne: I’m certainly excited about the topics discussed in the book, and I think there’s plenty more to explore. But to take a step back and use a wider lens, I am very passionate about making data itself accessible to wider audiences.
We touched on this in the previous question on AI. I think too many people look at data and say, I’m not a data person so I’m not going to understand what’s going on here. And I don’t think we should tolerate that anymore as a discipline.
It’s not about data analysts teaching all these people how to use data as it is meeting them where they are. We need to make data more accessible to more audiences instead of demanding that they own and understand all the technical language and nuances that data analysts use.
How do we make data easier for more people? How do we help them speak this language, and how do we do it so that they can speak it too, and understand the relevance to their work? Otherwise, we’re only understanding what data people want to study.
I want to know what the opportunities for data are from a finance lens, from an operations lens, from a creative lens—just so we can understand when we use those AI tools where they plug into the world everyone else inhabits. It requires a different type of storytelling, a different language. And that begins with a desire to do it.
Thank You Neil Hoyne
Many Thanks Bertrand Jouvenot