Putting ‘whole person’ thinking at the
heart of insights will grow brands.
A Hub white paper by Fern Grant of The Mars Agency
I have spent 25 years working in consumer insights. I’ve heard motorcycle owners in China complain about their wives not wanting them to race, shaved armpits in the shower with women in London (yes, with bathing suits on), and stood in line with moms at midnight before Black Friday.
I love research. I’ve loved it from my early days as a research psychologist; then as a brand planner; when I was the head of insights for a toy manufacturer; and now as the leader of a team of integrated planners. I love it because the work gives me the opportunity to connect with ‘real’ people, and to understand the richness and complexity of what makes us human. As a planner, research is my window into solving problems, to formulating insights, and developing strategies.
I do think research is facing some significant challenges as a discipline, and as a function within marketing. There has always been healthy dialogue around research techniques and approaches. But, lately, I’m hearing broader conversations relating to the efficacy and value of research.
Everyone is talking about data overload — we simply have too much of it, and more arrives with every new technology. Another topic cropping up is data relevance — we have data we didn’t ask for and aren’t quite sure how to use. Data affinity is a more recent discussion — finding relationships between data from different sources, with different purposes. Finally, and of greatest concern to me, is data merit — we have lots and lots of data, but seemingly fewer and fewer insights.
Simply put, we have more tools than ever that allow us to talk to and connect with consumers and shoppers. Yet, we are struggling to produce insights. This comes at a time when, in my opinion, we need insights more than ever before.
Manufacturers are under significant pressure to provide value to their consumers, their commerce partners, and their shareholders. Competition is tough. Getting placement is tough. Rising above the noise and clutter — physical and virtual — to reach people is also tough. Omnichannel behavior and the growth of e-commerce raises a whole new set of challenges as we spread budgets across channels. Then there are consumers themselves: savvy, engaged, empowered, demanding, content creators.
Growth has never been more important, yet it is getting harder to realize. The challenge is clear — we need to make better use of data to form insights to help marketers do their job and succeed. Let’s pause and ask some questions. What is that job? What does success look like? What kind of insights do we really need?
Marketing is all about influencing people — attitudes, beliefs, perceptions, and behavior. The ultimate goal is purchase (of course). At the end of the day, marketing efforts are pointless if people don’t buy our brands. That is one of the reasons I moved from brand to shopper marketing. Understanding how to persuade people to buy intrigued me. Over time, though, I’ve come to realize that the goal is much more than getting people to buy.
I recently reviewed three briefs — all from the same company — to find each retail team had provided an objective that involved growing their share by stealing it from the other team. This will deliver a great volume play, but where is the growth for the brand? The goal of marketing has to be more than influencing purchase; it is about influencing purchase in favor of growth. Growth can only come from change.
We want to get people to do something new and different — not just buy our brand on Saturday versus Sunday, at Kroger versus Publix, or on deal so they’ll stock up. We want current buyers to purchase more because they will use more. We want lapsed users to come back; we want to convince new users to sample. We want current buyers to trade up or buy across our portfolio. We want our current buyers to introduce us to their friends who don’t buy us — yet.
Influencing this kind of change isn’t easy. It requires more than looking at basket data and figuring out where and how to place a deal. To influence change, we need a strategy based on insights. It’s about understanding why people behave the way they do, and why they are not behaving the way we want.
Why do people buy what they buy? Choose to shop when and where they do? What is the relationship between their different mindsets, trips and channel choice? Why do people say one thing in a focus group (I avoid processed foods for my kids), but basket data tells us they are doing something very different in practice (oops, how did that box of chocolate coated cereal get in there?). There is usually a pretty good answer if you dig deep enough and connect all the dots.
So, what is getting in our way? Silos.
Think about the physical silos. Although the marketing funnel has collapsed, we are still organizationally structured against the linear marketing funnel of the past. This includes research, which is briefed and collected from different groups including consumer insights, shopper insights, sales, category, strategic planning, customer relationship management, digital, and information technology. Connecting dots is tough when the dots are all produced in silos.
Now think about the virtual silos. Everyone agrees that the path-to-purchase is not linear, but a dynamic, complex process. We also seem to concur that, although their mindsets are different, the lines are blurring between shoppers and consumers. Our experiences as shoppers can influence how we think as consumers, and our experiences as consumers can impact when and how we shop. A television ad can prompt an immediate purchase while I surf the net, just as in-store activations can drive awareness of a new product.
We know this, yet we often think of (and research) the people we are trying to influence in buckets. I have seen great integration between shopper and consumer segmentations, but it is the exception versus the norm. For the record, I have never been asked if I am experienced in understanding how messages influence people, but I am regularly asked if I know how to ‘do’ packaging research. Connecting dots is tough when the data we produce doesn’t have much in common.
Working out what we need to say, when and where and how to deliver it — and adapting messaging across various communication touchpoints — is complex. Factor in the inputs from the marketing silos, the distinct groups of data holders and all the competing agencies, and it is no wonder we’re left overwhelmed and uninspired.
So, where can we look for the solution? Integrated Marketing Communications is one attempt, although success has been limited. Some organizational restructuring is needed. I see attempts being made at integrating teams, but this is costly and disruptive, so it will take a long time to implement. In relation to what we can all do today, I want to offer a different way to think about and collect data.
From data as information to whole person insights
We need to get more focused on why we are collecting data versus what we are collecting (see chart). This captures the idea of an ecosystem. Here is an individual, moving in and out of different mindsets and stages of decision-making, engaging with a wide range of touchpoints and people and places, all of which offer marketers the opportunity for engagement.
Our job as researchers and planners is to understand this broad ecosystem, connect the dots between all the information, and find what I call ‘whole person insights’ that provides marketers with a strategy for influencing behavior — a strategy that will inform more than a message or a tactic, but rather an experience to influence people to buy.
The idea of an ecosystem model is compelling because it offers a framework for different teams to place and map the data they collect in a meaningful way, connect it back to the actual consumer experience, and connect the data together. It almost acts as a living, breathing knowledge map, uniting silos around a common point-of-view, and helping to unite data around a common meaning or objective.
From producing data to narrating data
The human experience isn’t linear, so why research and represent it that way? One of the first things I did when leading a research team was to assign each researcher to a business unit. I asked them to document everything they knew about our consumers and the category, what they bought and why, what they didn’t and why not. They reviewed our research and they interacted with the other ‘silos’ to collect information.
Next, they brought the business unit and data holders together to share the narrative they produced. The group connected the dots ‘intuitively’ and identified gaps in knowledge. Together, we spent the next year trying to fill those gaps, adding ‘chapters’ and details to complete the story, and validating some of our intuitive connections.
We were a small team with a small budget, which worked to our advantage. We couldn’t afford to do consumer and shopper segmentation separately, so we did both at the same time. This gave us an understanding of the relationship between the two. Similarly, we combined some television ad testing with packaging, which elicited really interesting learning. In the end, this approach enabled us to choose a national campaign that we knew in advance would translate well to other media.
Imagine using our data to create stories around the human beings we wish to influence, such as a narrative about new moms or Millennial men. Or, perhaps illustrate a behavior we want to influence — the grocery stock-up trip or back-to-school shopping. Better yet, consider a narrative around a growth objective — for instance, how to get private-label users to switch to our brand.
Finally, what if we engaged with ‘real’ people to build that narrative? Instead of demanding uniquely different people every time we conduct research, we do the opposite and find people we could talk to over time and iterate our learning. Think of it as a form of extended ethnography, including a range of methodologies that would span a year, or a life-stage, and include the broader ecosystem of family, friends, home, work, and shopping. I’ve seen some interesting examples of this type of work and it yields some rich ‘whole person’ insights.
This type of work will become increasingly important. Fifty percent of US households make $51,000 or less per year. The average salary of a marketing director is $106,000. I always say to my planners, don’t tell me you understand the Walmart shopper until you have lived for a month with $90 a week for household expenses. We need to interact with the people we are trying to influence with our marketing.
Certain software tools can house data. However, I am unaware of anything that satisfactorily connects data. Until such a platform is developed, we need to attempt to do this work ourselves — connecting our silos, connecting our objectives, and connecting with the people and ecosystems we are trying to influence. This is the future of delivering growth for brands!