Converted: The Data-Driven Way to Win Customers’ Hearts (Book Review)
Companies nowadays are always looking for data-driven ways to engage with their customers. In Neil Hoyne’s book, the Google’s Chief Measurement Strategist shows practical ways businesses can adopt in their digital marketing strategies to build a deeper relationship with their customers by using data to understand them.
In our digital world, everyone is crazy about Big Data, and every company is striving to be more data-driven. But what does it mean to be data-driven? How can businesses use data better? My digital marketing professor suggested us check out Neil Hoyne, a Chief Measurement Strategist from Google who has led more than 2,500 engagements with the world’s biggest advertisers, in the pursuit of building deep customer relationships through digital media. His first book Converted: The Data-Driven Way to Win Customers’ Hearts contains valuable lessons to winning customers’ hearts and being a better leader.
According to Hoyne, the best companies are now changing from delivering quick messages that demand an immediate response from customers to starting deeper and more long-lasting conversations with them. As these conversations are what separate marketers from the competition, in his book, Hoyne explores his ideas around 3 themes: conversations, relationships, and self-improvement.
Ultimately, businesses can find success in digital marketing by acquiring the most valuable customers, understanding them through data, testing, and modeling, while continuing to build a winning team and develop a culture of brainstorming ideas and putting them to test and into action.
The 3 Themes
Engage in conversation with your best customers.
In this part of the book, Hoyne shows us ways a business can start understanding their customers better by starting a conversation with them.
Hoyne suggests businesses identify as many customers as possible, collect data on website interaction, ask different questions, engage people beyond the website, and guide the conversation by customizing messages on websites based on the customer’s journey.
Although it is intuitive to be ambitious with data collecting, Hoyne argues that businesses should start simple (perhaps with an excel spreadsheet), and try existing models instead of building a model from scratch.
The idea is to always explore, ask questions, measure, and never stop investing in finding answers.
Acquire great customers and build relationships with those that matter.
In this part of the book, Hoyne suggests businesses build relationships with people that matter by identifying the best customers. Acquiring customers takes a lot of effort but identifying customers is easier than changing customer behaviors.
One of the ways he teaches businesses to identify the best customers is by calculating Customer Lifetime Value. By using data to predict customer’s CLV, looking for churn signals, businesses can identify their best customers and increase retention.
Develop a culture of raising ideas and build a winning team.
Throughout the book, Hoyne stresses the importance of starting simple and exploring. In the last part of the book, Hoyne continues with his ideas of “thinking small” by seeking progress not perfection. Because the market changes and the process of being better never ends, Hoyne suggests leaders build a culture of “consistently raising ideas and putting them to test”, by getting every person in the marketing department to contribute ideas, noting the hypothesis, what data supports it, how you would test it, and what the company would do differently based on the result.
Hoyne also invites leaders to build a winning team of people with diverse skills that will help push their team forward.
My 3 Key Takeaways
I. Start simple, think small, seek progress not perfection
Throughout the book, Hoyne encourages businesses to start simple. For a business that is just starting to use data more deliberately, it is better to start with a small team, a small dataset, and continue building from there. Progress is much more important than perfection. Instead of focusing on making the data perfect, “use what you can for today but invest in finding answers for tomorrow”. Instead of being scared of machine learning concepts, use machine learning to automate tedious tasks to free up time for creativity. Most importantly, never stop learning or try to be better.
II. Ask questions but collect answers with intention
Hoyne shows us how asking questions can anticipate customer needs and learn a lot about them. For example, Hoyne shows us that one of the best questions you could ask during a purchase interaction is “Are you buying this as a gift?” Studies show that when people buy gifts they actually engage with the brand more and gift buyers could be worth more than a single purchase suggests.
From personal experience, it is true to say that when I look for gifts I do a lot of brand comparisons and shopping around before I make a very deliberate purchase on a gift that I think the receiver would enjoy. Throughout this journey, I engage much more with the brand than when I normally buy things for myself because the gift says a lot about me and is what helps me bond with the receiver.
Thus, by asking questions like this, brands can learn more about their customers, predict their value, and customize experiences for them. However, it is important not to bombard customers with too many questions. For every question you ask, Hoyne says to also consider how the business is going to respond based on the answer. Collect with intention. Less is more.
III. Spend more on your best customers and let go of low value customers
In the second part of the book, Hoyne shows valuable ways to identify the top 20% customers using his CLV model. Although it is hard to let go of low value customers, we should accept people for who they are. Sometimes it is impossible to save a relationship with a customer. The best thing to do is to focus more on the better customers. It is more efficient to try to earn more value from the top customers than to fixate on changing the behaviors of low-value customers. Ask questions to understand your best customers, and in the meantime identify more of them. Let go of low value customers that cost more for the business but learn from them to do better.
Although some of Hoyne’s ideas across the three themes are repetitive, he explores the three themes deeply with proven studies and practical advice, while also using analogies for better understanding. Overall, the book provides a helpful guide for businesses that want to build deeper customer relationships by using data more deliberately. Hoyne’s ideas are not only valuable for small businesses that are hoping to be more data-driven but also for big corporations that want to change for the better. Hoyne invites businesses to self-improve by showing how companies stagnate because they focus so much on spending every dollar correctly instead of exploring and experimenting with new ideas. The book can indeed be an inspiration and action guide for companies to explore and join the conversation on data-driven marketing, while developing ways to use data better, understand customers, increase conversion, and leave the competition behind.
Get the book here