When most people think of advertising and marketing, an image of the “Mad Men” era agency comes to mind. But with surprising speed, the rise of digital–and the accompanying explosion of customer data–is reshaping marketing. Using big data, marketers today can better understand their customers, deliver personalized one-to-one experiences, and drive significant bottom-line results. They can align their marketing activities with overall goals and KPIs and gain insight into what’s working and what’s not.
However, in the rush to incorporate data science into marketing, new opportunities and approaches to customer intelligence have emerged as well. Many companies are discovering they can do more with big data if they focus on an often underrepresented element in their analysis–humans. Humans are more than a collection of data points; more than a summary of impressions, clicks, pageviews, likes, and transactions. While people generate more data than ever before, the challenge is that insights don’t just pop out of the data–you have to know where to look.
Become customer-obsessed; focus on the humans
The companies that successfully integrate big data into marketing are those that relentlessly focus on their customers. The goals and KPIs they set and measure themselves against, the way they structure and analyze their data, and how they incorporate customer insights into their activities are all driven by this customer obsession. Here are a few examples:
- Promoting savvy, engaging content that connects with certain customer segments in just the right way, fueling their interest in a brand and it’s products and services.
- Strengthening customer relationships by providing content that builds trust and establishes thought leadership—as well as demonstrating a keen interest in the customer’s interests. (What’s the most common attribute of interesting brands? They’re interested in you.)
- Understanding the buying cycle of each customer segment through customer intelligence, lead management, lead scoring and lead nurturing.
Today, customer data, knowledge, and insights are more valuable and of more strategic importance than ever before. That’s largely because power has shifted over time from companies towards their customers. Customers have more options, greater access to pricing information, and, through social media, greater means to share their experiences with others, both good and bad. They have more power, choice and influence than ever before.
In this age of the customer, the only sustainable competitive advantage is knowledge of and engagement with customers.” – Forrester Research
Companies that succeed in this environment are those that become obsessed with understanding their customers, such as Amazon and Salesforce. These companies go to great lengths to exceed customer expectations by leveraging customer information and insights. They are masters at gathering data, turning data into insights, and making decisions and changes in faster and faster feedback cycles. In other words, they find out what’s working and what isn’t and adjust appropriately at lighting speed.
Blend behavioral science with data science
Whatever else it produces, an organization is a factory that produces judgments and decisions.” – Daniel Kahneman
Over the past decade, behavioral economists have changed how we look at consumer buying behavior. Most companies have historically viewed their customers in rational terms—as if purchase decisions were primarily guided by rational choices to maximize personal gain and utility. However, the image of the consumer making unfettered “rational” choices has given way to a greater understanding of economic activity and the many “irrational” factors that influence purchase decisions. We’ve learned that economic life is pervaded by culture, driven by relationships, and influenced by emotion.
At first glance, the worlds of data science and behavioral science may seem to be light years apart. Data science is concerned with analytics, technology, machine learning and big data. Conversely, behavioral science is concerned with human psychology. Upon further inspection, however, data science and behavioral science can be combined into a marketing dream team. Much of big data, after all, is customer behavior data continuously gathered through digital touchpoints and channels. Behavioral science can help guide companies in where to look for insights and how to interpret the data. It can help them develop and deploy marketing and experiences that go with—rather than against—the psychology of human decision making.
What’s Next?
For many companies, now is the right time to re-think how they gather, structure and analyze their customer data. It is time for new metrics and KPIs that are developed from the customer’s point of view. It is time to integrate silos of customer data that are fragmented across multiple internal and external systems. Does your company have a single view of the customer? Or is customer data scattered across multiple systems? When it comes to marketing activity, do you have an integrated view of all marketing interactions with a customer? Or is this data isolated for each separate marketing channel? One of the keys to humanizing big data is making sure that your data foundations are integrated and customer centric.
In their book, Built to Last, Jim Collins and Jerry Porras coined the phrase “the tyranny of OR.” They describe how choosing between seemingly contradictory concepts—focusing on this or that—often leads to missed opportunities. Breakthroughs, they argue, happen at points of integration: art and science; form and function; creativity and technology. When it comes to big data marketing, one of those points of integration is the combination of data science and behavioral science. CMOs can maximize their results by hiring and developing diverse talent across these domains and by building multi-disciplinary teams made up of both skillsets.
We’re in the early stages of tapping into the potential presented by big data marketing. The opportunities to apply data to marketing are growing—but only if we know where and how to look.
