5 Behavioral segmentation examples that drive results
Segmenting has been around forever. In fact, there’s a very good chance that even dinosaurs used segmenting on some level, dividing themselves between carnivores, herbivores, and omnivores (and probably using those models to aggressively cross-sell omnivores on the benefits of a vegetarian diet). Behavioral segmentation, however, is a fairly new phenomenon that has gained traction with the introduction of customer data platforms (CDPs), which are designed in large part to extract behavioral data.
The difference between segmentation and behavioral segmentation is significant. Traditional segmentation, for example, typically creates segments around demographic data: age, income, and location. This data may be harvested (e.g., through customer registration) or purchased through a third party. But demographic-based segmentation is only useful up to a point. Treating all women between the ages of 35-54 with an annual income greater than $100,00 can help refine your marketing strategy a little. It’s not going to lead to the kinds of personalized experiences that Sephora, Spotify, or Netflix deliver.
Behavioral segmentation is how Amazon and Netflix do what they do. They look at behaviors, rather than relying only on demographics, and tag their content with thousands of keywords to help them understand customer behavior and boost customer loyalty. For example, someone who clicks on Mars Attacks may not like science fiction movies, but may like Tim Burton movies, and recommending another science fiction movie might be a turn off for them. (Then again, so might recommending another Tim Burton film, since Mars Attacks was pretty awful. But I digress.)
Behavioral segmentation can help connect the dots between action and intent. As you surface more relevant content you continue to learn more about a customer’s interest further refining the segment based on that behavior. This allows you to get closer to the intent, or why customers behave the way they do, rather than just tracking what they do. And it can encompass a lot more than just product affinities. For example, marketers can take advantage of a variety of types of behavioral segmentation:
This one is obvious and where many marketers start with behavioral segmentation. It provides insights into purchasing behavior based on a wide range of behavior patterns. The connection between buying a toaster and a toaster oven may not be an indication that someone loves toast, but could be a sign of a new homeowner or someone who’s renting their first apartment.
Knowing the what is important, but so is knowing the when. Is a new customer a weekend shopper or more likely to be online shopping in their bed at night? Do they tend to buy certain items around specific days (e.g., family birthdays?) and does their buying behavior change over the seasons (e.g., they buy more indoor products in the winter)?
Measuring and understanding a consumer’s level of engagement with your brand can be very important. This isn’t just a matter of counting clicks and visits, but weighing how much time a visitor spends on a specific page or piece of content, how likely they are to provide product feedback, etc. Targeting marketing campaigns to different segments of engagement can be highly effective at increasing the number of loyal customers you have and boosting their lifetime value.
Content affinity behavior
This is our Tim Burton example from before. Understanding what kind of content and what kind of content attributes resonate with a user is a powerful tool in building personalized customer experiences and creating a meaningful customer journey. It allows you to take the next step and recommend content that pertains to their behavior, interests, and even create content based on the patterns you’re seeing.
Consumers tend to engage with different channels, well, differently. They may buy shirts online but shop for shoes in a store. They may be more likely to click on an ad in Facebook than during a Google search. I know that personally I tend to buy certain items directly from an app on my phone while simultaneously watching the latest on Netflix and Hulu. And knowing all of this about me helps companies meet my needs by providing me with the content when I want it and how I want it. AND, it allows marketers to optimize their ad spend, by only serving the appropriate ads to the appropriate person in the right channel or suppressing ads that aren’t appropriate for the viewer. It ensures you are sending the right message, ad, or any content for that matter, at the time when someone is most likely to be engaged with your brand.
A company’s goal is to provide the best experience possible and that means learning about what your customer wants and giving it to them. Ultimately, behavior is the best metric for personalized marketing. Traditional market segmentation simply tells you what large groups of people have in common. Behavioral segmentation, however, tells you what makes people unique. And if you can’t deliver the personalization that today’s consumers expect, you’re going to end up like the dinosaurs: extinct.