Editor’s Note: This post is part of our Big Ideas series, a column highlighting the innovative thinking and thought leadership at IIeX events around the world. Alim Barnes-Gaskins will be speaking at IIeX North America 2020 in Austin, April 14-16. If you liked this article, you’ll LOVE IIeX North America. Click here to learn more.
As both a consumer and a researcher, I’ve seen a lot of change in the past decade. From the ability to have nearly anything delivered straight to your door to the spread of smartphones we carry every day, emerging technologies have created new challenges for brands trying to succeed in retail. Thankfully, there are more tools and data available today to help inform brands’ omnichannel strategies.
The shopper journey used to be linear with clear segments consisting of the sequential actions: “Discover, Consider, and Purchase”. Brick-and-mortar and e-commerce shopping were usually “either/or” propositions… sometimes “both”, but almost always separate. Now, consumers – not just millennials – seamlessly move back and forth, integrating digital and physical shopping experiences. The touchpoints along today’s path-to-purchase are complicated, but ripe for intervention and influence if they are well understood.
Over the last 10 years, access to “big data” has revealed previously unattainable behavioral characteristics in shoppers. Naturally, brands began mining these streams of “big data” to uncover new ways to sway consumer choice. Many brands rationalized backing away from tried and true consumer research methodologies, hypothesizing: “Why do we need insights, when we have data?”
And boy do we have a lot of data:
- Passive tracking of web activity
- Analytics of pre- and post-purchase activity on e-commerce sites
- The application of AI to “big data” POS sources
- Use of Natural Language Processing to reveal insights from consumers’ online searches and other aspects of their online lives
Still, “big data” analytics alone suffers from the same shortcomings as an overreliance on traditional quantitative survey research, which was once the gold standard for uncovering consumer insights. Both give us “2-D” versions of the shopper journey!
Several themes have emerged in the quest for a more holistic understanding of the omnichannel path-to-purchase, and the secret to influencing consumer choice. In order to obtain a 360-view of the shopper journey, omnichannel research requires the aggregation of the following, complementary components including a:
- Commitment to blending “big data” with “thick data”
- A behavioral framework that can identify and decode the innate drivers of influence in consumer choice
- Relentless focus on driving better business outcomes
So, What Exactly is “Thick Data”?
It’s not really a new concept. “Thick data” is the data captured using qualitative interventions to deliver insights into the emotional drivers of consumers: their motives, values, beliefs, and preferences. This information uncovers the “whys” behind how consumers behave and what drivers/barriers impact consideration. “Thick data” is often unstructured and resistant to the analytical approaches available in quantitative research but yields a much richer picture.
For example, in studies where we’ve utilized passive web activity tracking, interesting patterns were identified concerning how consumers discover a brand within their complex path-to-purchase. Passive tracking provides a linear sequence of websites accessed throughout that elaborate journey. What it does not provide – and where qualitative discussion and expertise prove vital – is consumers’ thought processes during consideration touchpoints. In that research, “thick data” showed shoppers were not jumping from product page to product page, rather many were opening multiple browser windows and directly comparing specific offerings. That insight added nuance, which allowed for a better understanding of shoppers’ consideration stages and ultimately a more accurate illustration of consumers’ “jobs to be done” than “big data” could have provided alone.
“Thick data” informs our understanding of the total consumer experience of the product, as well as the shopping event. Ultimately, marketers need to uncover a truly 3-D and actionable picture of the optimal drivers of influence in consumers’ lives. Combining “big data” and “thick data” does just that.
It may not be the perfect analogy, but I like to think of it like this:
When we go to the dentist for a check-up, regular 2-D x-rays are enough to identify basic oral health concerns. If you have a more complicated condition, a specialist takes a full 3-D scan to digitally reconstruct your teeth/skull. Your dentist may also conduct qualitative assessments of your lifestyle (“do you grind your teeth, where do you feel pain, how long have you been in pain, etc.”) to develop a well-rounded perspective. Then and only then, can they formulate a treatment to address your health concerns.
Is it bad to say getting omnichannel insights is like pulling teeth?
But honestly, this formula works! I’ve used this approach with clients to tackle their biggest business problems, discover the “here’s what… so what…” in consumer insights, and form recommendations for the all-important “NOW what!”
Many things have changed in the last decade: the proliferation of apps, our increasing use of mobile devices, and the explosion of connected devices and digital assistants. The tactical aspects of “how” we shop may be evolving, but the basic principles of behavioral science are more relevant than ever, particularly when investigating how shopper choice impacts brands.
When we marry “thick data” with “big data”, and analyze both through a behavioral framework, what emerges is more actionable, relevant, and effective guidance for brands. Once the holistic “3-D” view of the omnichannel path-to-purchase can be seen and understood brands can identify the opportunities for when and how to engage consumers optimally, to drive better business outcomes.