By Carter Cast and David Schonthal
“Big Data” is the phrase du jour — it’s no secret that data can serve as a powerful and practical resource for understanding consumer behavior. But it must be used in the proper context, or else it can distance companies from those they wish to understand.
A common problem arises when corporate innovation teams over-rely on data to uncover new insights about customers, or understand user behavior on a deeper level. They become seduced by numbers, convinced that statistics reveal indisputable truths about target-market behavior. While this data can be informative and even comforting (“Forty-eight percent of our new buying cohort claims they’ll repeat within three months!”), it also carries risk; it can miss the nuances of human behavior, paint abstract representations of people and generate information that's void of empathy. Consumer needs, motivations, emotions and behavior can easily get lost in numerical translation and interpretation. As the Talking Heads once sang, “Facts all come with points of view; facts don’t do what I want them to."
Illustration by Michael Morgenstern
At the Kellogg School of Management, we advise corporate innovators to follow the lead of lean startups to gain a clearer and richer understanding of their customers. These startups, constrained by scarce resources, are forced to learn about their prospective customers in the most rudimentary way: by getting out into the market and observing and talking to people on an individual basis — in the right context.
It might seem unsophisticated, but this approach is how startups often discover the key consumer insights that large companies miss. And it’s how they create products, services and experiences with potential to disrupt massive industries.
Here are a few ways that any organization can introduce a bit of scrappiness and human-centered thinking into its research approach:
Manufacture constraints for yourself.
Act as if your corporate infrastructure and resource capabilities don’t exist. Just set them aside for a bit. That means getting out of the office and talking to your customers directly, or finding opportunities to tag along with customers for extended periods of time while they go through the purchasing process. Give yourself short deadlines to force resourcefulness (“We need to interview at least 30 users in the next 2 weeks!”).
Become best friends with your customer service center.
Inside the office, park yourself in the customer call center and answer phones so you can hear customers’ comments and complaints firsthand. By interacting with your customers in a direct, unfettered way, you will quickly learn what’s working for them, what isn’t, and what you can do to make their experience with your product or service better. Are the mice-type assembly instructions for your baby crib exasperating to customers? Is it hard to find the “image upload” button in your expense-management software? It’s not surprising that many successful entrepreneurs start off by handling a bulk of their company’s customer service calls themselves. There is no better way to learn.
Think of your customers as individuals, not data sets.
In the early days of developing a new product or service, seek depth over breadth. Move beyond large surveys and customer data sets, and have long, open-ended conversations with 10 current or potential customers about their experiences with your product and competitors’ products. Explore: What problem are they really trying to solve by using your product? Where do various products delight or disappoint them? What’s the biggest hassle they tolerate when using your products — perhaps without even realizing it? What must they give up to use your offering? If you can answer these types of questions, you can unlock innovation opportunities that data alone will miss.
Put on your anthropologist hat.
Here is a human truth: People say one thing, but do another. Because of this, it’s imperative that you observe your customer in the wild, exploring their behavior in the context of their everyday lives. Put on your Jane Goodall hat and seek to understand them, rather than validate your ideas. Like an anthropologist, collect artifacts that will help you communicate your learning with your team. Take field notes and pictures, record video and audio.
All of this will help you learn (and remember) how consumers live their lives and use your product. It will likely reveal important, sometimes painful, findings. You might realize, for example, that you’ve misjudged customers’ interest in a signature feature that your group developed, or that your product/service doesn’t easily integrate with peripherals that your customers use. Indeed, this process of immersion is how Chuck Templeton, one of our Kellogg School alums, figured out how to design the OpenTable restaurant reservation system; he sat in restaurants for days, observing how restauranteurs managed — and struggled with — their software and point-of-sale systems.
Track emotional peaks and valleys throughout the journey.
Today’s consumers go through a dizzying pre-purchase, purchase and post-purchase process. Gone are the days where the buying public passively receives a product message from Wilford Brimley while watching “The Waltons” and walks into a grocer the next day to buy some Quaker Oats. In this age, corporate innovators must be keenly aware of all the social networking activity that precedes the purchase (e.g., getting inspired on Instagram or comparing deals on Retail-Me-Not) as well as all the discussions following the purchase (e.g., inside a Facebook group or through a nasty Yelp review).
It’s not enough to focus on the moment of purchase. Map the entire customer journey so you can understand the full spectrum of customers’ emotional highs and lows, from the moment they decide to buy in your category to their post-purchase experience with your product. Sometimes, the experiences leading up to, or right after, the purchase of your product is where you will uncover new opportunities. For example, there may be relatively easy and inexpensive ways to alleviate your customers’ pain or frustration while increasing their overall satisfaction in a dramatic way, like when GE modified its MRI experience for pediatric patients or the way that Uber delights its users with extras like Spotify radio and cashless transactions.
Don’t get us wrong — it’s terrific to have big data. It points you in the right direction and helps you hone in on a problem to solve. But to get the texture and nuance that leads to innovation, you need to have direct experiences with the individuals whose problems you’re solving.
Learn more about Corporate Innovation at the Kellogg School of Management.
Carter Cast’s 30-year business career includes a variety of manager, director and executive roles in Fortune 500 corporations and multi-million dollar startups. Part of the launch team at Walmart.com, Carter later became CEO of the online platform. Now a partner at Pritzker Group Venture Capital, Carter invests in high-tech startups and coaches management teams. An award-winning entrepreneurship and marketing professor at Northwestern University's Kellogg School of Management, Carter earned an MBA from the Kellogg School, after receiving a BA from Stanford University. Carter has appeared in the Wall Street Journal and the New York Times and on Bloomberg, CNN, CNBC and FOX.
David Schonthal is a professor of innovation and entrepreneurship at Northwestern University’s Kellogg School of Management. David serves as the director of Kellogg’s Zell Scholars program – a selective venture accelerator program helping student entrepreneurs successfully launch new businesses. David is a leader in the business design practice at IDEO, an award-winning innovation consultancy. Previously, David was a co-founder of Fusion Ventures, an investment and advisory firm focused on growing technology startups in early-stage development. He was also a director of strategy and venture development at Tavistock Life Sciences, a private investment firm. David has also held numerous leadership positions at startups in the technology and life sciences sectors.
