Henry Ford said: “If I’d asked customers what they wanted, they would have said, ‘a faster horse’.” Steve Jobs famously echoed that sentiment when he said: “It isn’t the consumers’ job to know what they want.”
Sam Walton took a related view with his 10th Rule: “Swim upstream. Ignore the conventional. Think differently. If everybody’s doing it one way, there is a good chance you can find your niche by going in exactly the opposite direction.”
Others, meanwhile, offer a more “quantitative” perspective. Dr. Oz says, “The major part of good heart health is in the metrics,” and W. Edwards Deming advised: “In God We Trust; all others must bring data.” Peter Brand, of Moneyball fame, said: “It’s about getting things down to one number. Using the stats the way we read them, we’ll find value in players that no one else can see.”
It seems good instincts and hard data are the yin and yang of business insights.
JC Penney chief executive Ron Johnson told Harvard Business Review, “you’ve got to trust your intuition much more than you trust the data.” In his book, Blink, Malcolm Gladwell also came down on the side of running with our first impressions.
On the other hand, Michael Mauboussin, author of Think Twice, offered a rebuttal to Gladwell’s thesis, arguing that better decisions depended on the “wisdom of the crowds,” along with data and mathematics. And IBM chief marketing officer Jon Iwata advised his fellow CMOs to embrace “advanced analytics and compelling metrics” in their decision making.
This debate may be as old as the business of marketing itself, but it probably will never die — and certainly not at a time when brand loyalty is eroding, private labels are growing, and more than 90 percent of new products are failing. Growth requires innovation, and innovation will not happen without insights.
So, is getting at those insights an art or a science? The answer, clearly, is “yes.” It is both. But the more important thing is to evaluate the quality of the insights based on the results that they ultimately deliver in terms of innovation and growth. That’s the reason we invest in insights, whether gut or quantitative.
Look at the top-level companies in the Hub Top 20 over the last five years. We know how they got there. They understand that a brand is a promise made and kept, and that making and delivering the brand’s promise drives equity that drives enduring, profitable growth. They know that it’s innovation in the product, promise and channel that drive equity.
Most companies use a similar process for developing the insights. Every company has some level of insights that translate to some level of innovation that translates to some level of strategic planning and activation. Maybe it’s because they all use a similar process that most are experiencing less growth than they could?
But what makes some companies more innovative than others? What is their strategy? Some offer a value breakthrough like Walmart. Some are first-movers, like Microsoft. Some have a new vision, like JC Penney (results are yet to be determined, of course). There’s also a whole lot of talk today about the relationship between company culture and innovation, with Zappos often mentioned. Each of these companies has different strategies, but they all use insights as the currency, and translate those benefits to some form of consumer end-benefit.
A Whole-Brain Approach
Given that consumers take a “whole brain” approach to making decisions, marketers need to take a “whole brain” approach to insights, with full consideration to both the “left brain” (logical, sequential, rational, analytical, objective) and “right brain” (random, intuitive, holistic, subjective).
We need to recognize that shoppers are motivated first by emotion; shopping is an experience and that experience is an emotional one. One of the most important things to understand about translating insights into innovation is where the decision is made. That means we have to understand the consumer, the shopper, and whether their decisions are made before they get to the store or while they are in the store.
There’s no way that we could do all of that purely through intuition — or purely through data. What’s required is a “think, feel, do” approach.
To understand the shopper mindset, we need to have a deep, fact-based understanding of their behavior and the motivations that drive it, which can be acted upon to further brand innovations. These motivations can include attitudes, beliefs, values and feelings. Tapping into those motivations to influence shopper behavior requires understanding that behavior in the retail environment.
So, we need an understanding of that, as well: How does the consumer decide where to shop, and then how do their surroundings influence whether they stick to their shopping lists or make their purchase decisions on the fly? The relationship between insights and innovation is built on the connections between the consumer, the brand and the retailer. It’s these connections that take us to a more strategic approach to developing insights, and it mixes quantitative and qualitative intelligence. They can help push the idea further because we are taking a more complete view of the consumer into account. After all, it’s the idea that changes the world, not the insight, so let’s put the focus there.
Crayola, the number-one brand in children’s art supplies, has done a great job in this regard. More than half of Crayola’s category volume is sold during the back-to-school period and the brand has limited relevance the rest of the year. Their challenge is to innovate within their category and expand their relevance from “children’s art supplies” to something more.
Their strategy is to broaden the definition of their category by creating new opportunities for self-expression. This is based on the insight that parents want a broader range of products to satisfy the aspirations they have for their kids. Crayola developed a range of “concept lanes” at retail, including kids’ art galleries in stores and Crayola Towers, a striking display of Crayola products that highlight the product’s many creative possibilities.
I was not involved in the development of these concepts, but clearly they took into account the mindset, behavior and surroundings that were influencing the shopper’s decision-making.
Connecting the Dots
In today’s fragile economy, companies are under such pressure on the earnings side of the equation that a lot of decisions are made to reduce risk. At many companies, it’s believed that quantitative research reduces risk.
Not everyone buys into this, however. In fact, Christine Day, chief executive of Lululemon Athletica, the rapidly-growing fitness-apparel retailer, says it’s just the opposite. “Big data gives you a false sense of security,” she told the Wall Street Journal. Lululemon uses no customer-relationship management software at all, and instead relies on listening to what shoppers say when they are in the store (see page six). Lululemon’s results speak for themselves: “Over the past three years, the company has posted nine quarters in which sales rose 30 percent or more from the year before,” according to the Journal.
Regardless of whether the approach tilts to the quantitative or qualitative side, Lululemon and other innovative enterprises are connecting the dots between the insights and the results achieved. And in a world where insights are judged only by the results they help deliver, the most sensible approach is to combine the human elements of judgment and creativity with the prediction and analysis of statistics or agent-based modeling. In this way, smart data collection provides the facts; models supply the rigor; and we supply the judgment and creativity for insight-inspired ideas that get better results.
We can do scenario planning and understand how the consumer decision is made and which levers to pull. Therefore, we can identify the relationship between the consumer’s decision process, brand equity and the return-on-investment. We can do that by channel, by retailer and by consumer (see chart). It’s not about analyzing each of these areas independently, but rather looking at their interdependence.
As a result, we can now understand the success drivers in terms of awareness and demand creation. We know what to do at retail, and how much money to spend. We are building insights based on scenario planning with predictive results. It is the best of all worlds, where not only are we using insights to create great ideas, but we are also testing them in different scenarios, at different levels of spending.
The three questions about accountability are always: How can we improve over the results we’re getting now; how can we say that with a straight face; and how can we be sure we’ll get the results we’re predicting? Using the data, the model, our judgment, and testing the different scenarios allows us to go back to the data, push the ideas, make those ideas bigger and optimize the business.
This is art and science, gut and analysis, and it provides a framework for insights, innovation and growth.