74 percent of marketing leaders told us that market and customer insight are one of the top capabilities critical for success (Gartner subscription required).
Yet, when I ask marketing leaders what kind of data they have on their customers or prospects, the most common answer is quantitative data. Most organizations are comfortable with gathering and have knowledge of the “what” – what it is their customers do. But, while necessary, knowing what your users do is not enough data for you to make sound decisions. We, as marketers, need to understand and dig deeper into user motivations and needs. Emotion and values play pivotal roles in how human beings make decisions; facts justify and validate those choices. If we only understand the “what”, we only understand a part of the picture. This forces assumptions that lead to flawed decisions.
False Assumptions Lead to Ineffective Marketing and Experiences
I live at the beach and, during our first summer there, our neighbors kept commenting on what fitness buffs my fiancee and I were. We would head to the boardwalk in our workout clothes every day, and they saw us running or walking very quickly once we got there.
But, we don’t run from one end of the boardwalk to the other for fitness, we do it for fried Oreos. (They may not look tasty, but if you like Oreos these are like little bites of tasty heaven. Just don’t eat them in the wind because the powdered sugar gets all over you). Anyway – there are fried Oreo stands at each end of the boardwalk and we run to the one we think has shortest line. If that line is too long (in the summer, lines at the food stands can be VERY long), one of us races down to the other stand to see if that line is shorter.
If my neighbors were a company, and only assessed my behavior, “what” I was doing, they would build experiences and marketing programs around exercise. While I do exercise, it isn’t relevant to what I was trying to accomplish. Fried Oreos are basically the antithesis of exercise. By understanding why I was doing what I was doing, they can offer me a more targeted, relevant experience. Showing me how long the lines are or enabling me to order ahead for fast pickup would earn my loyalty and advocacy.
I used this example with a client the other day and she said, “Or they could have arranged delivery service!” While a great idea, it would not work if I was a company’s main persona or client base. Because fried Oreos are so bad for you, and so addictive, I try not to eat a lot of them. Putting physical effort into getting them is part of the mental trade-off I make to rationalize eating them. Understanding how and why I make that decision would prevent a company from offering products or services I don’t want or won’t use. It would also drive more focused innovation, such as lower-fat fried Oreos that help assuage the guilt I feel as I consume their powdery, chocolaty goodness. It might even make me indulge in more.
Relevance Requires Qualitative and Quantitative Insights
You may be thinking, “OK, we get it. You are overly-obsessed with fried Oreos and we need to understand our customers better. How do we do that, exactly?”
The way you accomplish this is, no surprise, by looking at your data. Qualitative and quantitative: analytics, user research methodologies (Gartner subscription required) and Voice of the Customer (VoC ) data. At a high level, you should strive to understand:
What: your users do/don’t do, and what they are thinking and feeling as they do it
Where/When: they do it
Why: why they do/don’t do it
How: they do it or how they prefer to do it
The amount and specific types of data you need depends upon some key factors:
- the goals of your users and your company,
- what existing data you have,
- the quality of that data and
- where your knowledge gaps exist.
Filling those gaps with qualitative and quantitative data creates insights essential to your ability to offer products, experiences and marketing programs that your customers/prospects want and respond to.
What kinds of insights does your company use to understand your customers? Do you think you have the right mix of qualitative and quantitative data? Most importantly, do you have any lower-fat fried Oreos recipes you can share?