Good, better and best approaches
In a world where consumers are exposed to more than 5K ads a day* and only engage with about 10 of them, its clear why better targeting is so essential. Luckily, over the past 10 years, our ability to learn about and understand consumers has reached new heights.
Through micro-segmentation, we can leverage audience information to better target, understand and connect with our customers. Let’s explore three approaches of audience segmentation and explain when each level of granularity is important (or “good enough”) to meet the goals of your campaign.
Good: Demographics are a solid place to start
Targeting groups of people based on demographics such as age, gender or household income is a popular place to begin a segmentation strategy. Of course, demographic targeting has its critics. In a world of ever improving marketing personalization, demographics can be considered an oversimplified approach to targeting, because it doesn’t address exceptions, complexities and differences among the individuals within a broad bucket. For example, Hitwise (a division of Connexity) found that 32% of people who visit top beauty and cosmetic sites are actually men. This means a beauty brand who markets exclusively to, “women age 18–45,” could be leaving out nearly a third of their potential audience.
That being said, the fact that demographic targeting is quite broad also can be an advantage; demographic segments often provide the greatest volume because they encompass such large groups of people. For that reason, demographics can be especially useful for higher level branding campaigns where you want to achieve greater reach and exposure at a lower cost.
Better: Getting personal with lifestyles
Targeting audiences on the basis of their “persona” can allow marketers to even more accurately understand (and even predict) their behavior. A “persona” is not only defined by demographics, but also can be characterized by a combination of interests, purchases or patterns of behavior, which represent a “lifestyle.”
One way marketers identify “lifestyles” is by matching demographics to relevant online behaviors. For example, a make-up brand advertising their latest lipstick line may want to target not just women 18–45, but specifically “beauty maven” personalities; women who have purchased make-up products or consumed content about beauty. Targeting on the basis of lifestyles can improve the accuracy of your predictions, but they are not foolproof.
Consumers’ daily lives have become so saturated with media that they can usually spot campaigns that have essentialized them into a “bucketed” persona and in some cases, they even resent this reductive approach. Not all female “health buffs” will respond to a banner ad promoting, “flat abs now.” However, people’s attitudes, complexities and purchase intent can come to light when you start moving from tailoring to personalization.
Best: Micro-segmentation is the future
Micro-segmentation involves layering hundreds or even thousands of data points to identify granular clusters of individuals. Rather than looking at target “groups,” marketers can layer rich sets of first and third-party data to identify hyper-relevant segments based on attributes like lifestyle, interests, attitudes, purchase behavior, search behavior, panel data, buyer stage and much more. The result is a rich mosaic of tens, hundreds or thousands of micro-audiences, rather than just 10 or 20 segments.
Moving from broad-based segments (left) to micro-audiences (right) allows for more relevant messaging to smaller “clusters” of people.
Your first-party data, your own customer and visitor information, gives you an excellent jumping-off point for identifying your most valuable segments. For example, in a Big Data report, McKinsey** reveals how Tesco uses its own loyalty program and purchase data to analyze the buyer journey that leads up to a transaction: It uses this information to create micro-segments that inform their product mix, pricing and promotional strategy. The more information a brand has on its customers (as in, the greater number of signals it collects), the more data it has to “pattern match” similar individuals and identify new micro-audiences outside of its own database. In order to identify and target new customers, marketers can leverage third-party data sources to identify consumers with similar attributes to their own best customers.
The trade-offs of granularity
In many instances, micro-segmentation will not be a cost-effective strategy certainly, no brand can launch tailored campaigns for every single micro segment in their potential audience. However, in cases where segmenting audiences by demographics and a couple key behaviors or attributes is not enough, marketers can segment based on additional data points to triangulate an even more “ideal” customer. Let’s say a home technology company released a cutting-edge “smart” baby monitor that reads their baby’s vitals and syncs them to the cloud. Their research shows fathers are more likely to make household technology decisions, so they begin targeting this segment first, with little success. The marketers then realize that perhaps the average dad isn’t ready for such advanced technology. Then, it’s time to get more creative. They decide to double down on promotion to a small, specific micro-segment of “Tech Enthusiast Dads.”
Demographically, they are male, parents and have a high-income, behaviorally, they have purchased baby products and searched, clicked or purchased high-end technology. It costs the company nearly twice as much to target such a narrow micro segment, but the product is so hyper-relevant to this audience that they convert at 5x the rate of normal dad segments.
Audience segmentation is a careful balancing act. It’s easy to assume relevance and granularity are always important, but micro-segmentation may not always be necessary to achieve the ends you desire. If your goal is to generate brand awareness among a wider audience, it’s possible that larger demographic or lifestyle segments will serve the needs of your particular campaign (at a lower cost). If you do plan to delve into micro segmentation, strategize based on your main objectives; for example, if your goal is to increase return on ad spend, spend your resources identifying and targeting the micro segments with higher margins and lower CPAs.
This article was published in Oracle’s “Data Source” magazine. You can download a free copy of the publication here