It’s one of the biggest and oldest problems in business: how to continuously understand what customers want. What are the needs, motivations, and emotions that drive consumer behavior? For companies, that question is as essential – and challenging – as “What is life?”
Every company, of course, strives for happy, loyal customers so they can win in today’s hyper-competitive, digitally driven markets. Many fall short, however. An Accenture survey found that “76 percent of executives agree that organizations need to dramatically reengineer the experiences that bring technology and people together in a more human-centric manner.”
Good news: Businesses have the power to do this. But to get there, they must do a better job creating a shared understanding within their companies of who their customers are as human beings. Without that understanding, businesses are hard-pressed to build a true and meaningful connection to the people they serve.
Truly knowing customers is hard to do at scale. As a result, businesses have come to rely on data to try to understand who customers are, what they do, and what they want and need. But while data was once thought to be a panacea, in reality, it’s a mixed bag.
On the plus side, businesses in the digital age have access to a nearly inexhaustible supply of data charting purchases, clicks, page views, survey results, etc., and it would be foolish not to leverage it. This information can be valuable in gleaning trends and offering baseline insights into the experience people have when interacting with brands and products.
On the other hand, while this information can be helpful, it’s incomplete. Data can’t provide a holistic picture of multidimensional, decidedly human customers. After all, people have complex psychologies that may influence choices in ways that data cannot capture. They’re just too sophisticated to be boiled down into numbers.
It may sound like heresy in a world where many companies spend billions collecting, sorting, and interpreting data in an effort to assemble a clearer picture of customers, but businesses need to recognize that data alone simply will not help them deliver unforgettable experiences, secure loyalty, build buzz, and improve their offerings over time.
With that in mind, here are four common practices companies should reconsider.
1. Looking to analytics for all the answers.
“What is my customer doing with my product?” Analytics can help there. This involves observable customer activity, such as how long individuals are staying on the website and what they’re buying. Analytics is behavior seen at scale, which can help identify patterns and areas to focus on.
But extrapolating meaning from data can be tricky. It runs the risk of superimposing the company’s ideas, logic, or even hopes and preferences on the data. Businesses often are left making educated guesses about motivations and they might guess wrong.
When developing new products or features, companies tend to use behavioral analytics to nail down what real customer problem they’ll solve. But by relying exclusively on this data, businesses get only a partial view of how effectively they’ll address the need – more insights are needed about how the problem arose or why it’s a problem worth solving.
2. Relying too heavily on demographic segmentation.
Demographic segmentation, which focuses on certain traits such as age, gender, socioeconomic background, occupation, and location, is a cornerstone of companies’ efforts to understand customers. And it sometimes can be useful, such as in targeted marketing campaigns. But it’s also an archaic and limited way of sussing out the audience.
Where demographic segmentation hits a wall is in determining what customers want, need, and hope for. The method only aims to delineate who customers are. And it doesn’t even do that well because it assumes that every person in a certain group thinks and acts the same. Remember what I said earlier about humans being complex?
3. Falling in love with surveys.
Surveys, questionnaires, and other customer feedback techniques are a good start in obtaining feedback from customers by providing a direct line to their recollections and impressions. But surveys have a long list of shortcomings. For example, it is hard to design a survey that’s objective, accurate and truly representative of customers, which means the data may be skewed. And surveys rarely drill down enough to reveal a customer’s deeper perspective.
Take the question of ease of use of a product or service. “Is this easy to use?” is a straightforward question in a survey, so businesses assume they’ll get straight answers. But do they? What about a person who enjoys using an app but sometimes gets confused about one feature? They might say the app is “easy to use,” but a valuable perspective that could help make the experience even better is lost. Survey results don’t give a full picture of ease.
4. Not listening to actual customers.
“If you don’t listen to your customers, someone else will,” Walmart founder Sam Walton once said. Walton backed this up by visiting several stores every week to see and hear first-hand how they were delivering a customer experience that he demanded be “legendary.”
As these four points show, leaders in many companies have been conditioned to believe that numbers are all they need to make sound business decisions. But many don’t realize what they’re missing.
Using data alone prevents companies from maximizing existing customer relationships, reaching new markets or niches, or making improvements that customers truly want. More detail, more nuance, and more truth from customers is needed than data can reasonably provide.
The move to digital doesn’t absolve companies of the responsibility to seek out authentic customer perspectives and capture the narratives that let businesses envision and create experiences that delight and support the people they serve.