The 6 Sides of Every Customer

Are we all hexagons under the skin? No, I am not talking about some sort of new geometric philosophy. Nor am I making a mock profound assessment of the human condition. Rather, I want to spark a discussion about the consumer data that matters to developing rich, genuine customer understanding — powerful insights to drive the best possible program results.
The 6 sides of every customer
A person is a lot more than a gaping maw relentlessly focused on consume, consume, consume and/or making a rational and detailed assessment of the options in your category. Yes, Virginia, people are complex, and their motivations, needs, and actions emanate from a complex set of mindspaces. Analysis of a variety of successful digital and integrated campaigns shows us that comprehensive customer insight comes from six different types of data — a range of information types that, in aggregate, reveals the six sides of the customer that drive persuasion.
Let’s consider each of these data types and what they reveal about your customer.

Demographics and lifestyle

Most products and services companies have a demographic skew in their audience base. In addition, many brands have recognized that there’s value in getting far more granular in their demographically based segmentation. Consider a popular target like moms 18-49. Take a look at the two photos below, and then imagine how different the perspectives and lifestyles of these two mothers might be.
Yes, looks can deceive, but they can also be revealing. This is why more and more brands are pursuing granular demographic segmentation and personalized media to better deliver relevant messages to prospects.
Traditionally, digital media has used a great deal of inference to identify demographics and lifestyle. Many audience definition models use browsing — and other habits — as a proxy for known facts about a person. The quality of those inferences is based upon the amount of data analyzed, the quality of that data, and the standards with which we make inferences.
Inference isn’t inherently bad, but more and more brands are seeking more verified forms of demographic and lifestyle information to drive better audiences for their programs. Those focusing on personalized media are also looking to data sources that use known facts versus inferences. Working with Nielsen and comScore, my company has compared inferred audiences against verified offline-derived demographics. The results found big gaps in the accuracy of inference. Inference, after all, is simply educated guesswork.
But the crucial value of demographic and lifestyle data is well established. And a combination of verified demographics and rich digital behavior provide an excellent — and often essential –foundation.

Passions and interests

Digital has long leveraged browsing and interaction data to unlock insights about a person’s passions and interests. From browsing reviews of crossover SUVs to spending hours on recipe sites, what people choose to do online helps us identify the right people for targeting. Passions also help us determine more compelling messaging for individuals and segments. For example: Does a person’s behavior indicate that they respond better to the perceived prestige of a brand, or evidence of its quality? Or, family-centered messaging or ads that are all about me?

One example would be in the use of content to determine passions. Knowing that someone looked at 10 pages of sports content in a month is less valuable than knowing that they’ve watched three hours of UFC video in the same period. The latter shows a greater time commitment and a clear, deliberate choice to consume large amounts of such content.
Interest data can help us segment or personalize messaging to individual interests. For a pickup truck manufacturer, reaching people who have a passion for monster truck sporting content might be preferable to avid consumption of equestrian dressage videos. Better still might be an approach that speaks one way to the first group, and highlights the horse trailer towing power to the second. In short, uncovering a person’s passions helps us deliver far more compelling communications.

Device usage

ComScore says that 51 percent of total digital time is now spent on devices other than a PC. Given this, we need to understand user behavior across all device types in order to truly understand their needs and passions. After all, if we see only PC-based data, then we understand less than half of what someone does online.
Real-time cross-device browsing, interaction, shopping, and purchase data help us create a holistic view of how our target is spending their time right now. That informs message timing. From there, understanding the particular cross-device behaviors of an individual (for personalized media) or a group (in segmented marketing) helps us to deliver the right mix of messages at the right places on the right screens for maximum impact.
As we all know, connecting devices for either data analytics or media delivery is tough stuff. Methodology matters a great deal. But behavioral and device usage data from PCs, smartphones, and tablets is becoming essential to driving maximum results for marketing investments.

Social media interactions

People spend a lot of time in social environments — this is true across demos and devices. According to GlobalWebIndex, people spend two hours per day — about 27 percent of internet time — on social platforms. Other data sources show similar percentages.
 That’s too big a block of time to ignore, which is why many solutions providers now offer social advertising solutions that leverage first-, third-party, and/or social network audience data to extend digital programs.

Now, not all social time is relevant to your category or product. In fact, much of it probably isn’t. But some may well be, and given that it represents more than a quarter of the average person’s digital time — and even more for younger, more urban folks — you shouldn’t ignore social.

Brand relationships

I’ll bet dollars to doughnuts that the big change in digital advertising, over the next two to three years, is going to be the nearly ubiquitous use of first-party brand relationship data to inform targeting and messaging. Brands will embrace the idea of putting their big customer data to work in all of their digital programs and campaigns.
Traditionally, it has been tough for agencies to convince clients to share their first-party data for targeting — it can seem like a hassle and requires the heavy participation of client IT teams. But that is changing fast. Tag management has made it easier, and the value of first-party brand data for targeting has proven massive.
Integrating site interaction data — available when a brand tags all of its pages — is a great start because it helps reveal the preferences, interests, browsing, and even purchases that customers conduct online. Further, by using third-party data and cookies you can actually identify more of your customers and hand raisers as they browse the web. When you rely on third-party cookies, a high percentage of your users are hiding in plain sight because it’s unknown that they have a pre-existing relationship with your brand.
Data from other digital interactions can also enrich your insights, and through them your overall program effectiveness. In addition, in most categories 80 percent or more of products are purchased offline. Offline brand interaction data is very powerful in order to understand and measure the offline impact of your online programs.

Actual purchase data

We’ve saved the biggie for last. There is no better way to predict future purchases than with a comprehensive understanding of past purchases — both historical and recent transactions. Real-time or recent data helps predict both need and stage in the decision process. Historical data reveals seasonality, purchase cadence, and other insights that pinpoint people who are most likely to buy in the immediate future.
First-party purchase data is an unparalleled resource for targeting and messaging. In addition, companies with access to broad sets of purchase data — in the same and related product categories — have a great advantage. Again, the keys are the quantity, quality, and recency of purchase data.


You don’t need to understand all six sides of your consumer to get good results. Companies prove this every day with campaigns and ongoing programs that drive good results. But while good results might have been good enough in the past, these results are insufficient to achieve today’s KPIs. Marketers need every potential tool in their arsenals to drive the best possible results.
As you think about the programs you are planning now, ask yourself whether you are leveraging all six types of data — and in the best ways possible. If you are on the agency side, one of the big opportunities might be in convincing your clients that putting all of their first-party data to work will yield great benefits.
Although this kind of client persuasion might not be easy, the results will be worth it. In fact, putting that first-party data to work might be the key to demonstrating the agency’s value today and in the future. After all, our industry is only getting more competitive.
Thanks to iMediaConnection for publishing this first.