Behavioral Segmentation (And Why It’s So Important)
If you read our blog post “What is Customer Segmentation?” you learned that market segmentation is a technique where existing customers are split into groups based on similar attributes or affinities. It covered a range of methodologies for segmentation including demographic, firmographic, psychographic, needs-based, and more.
But one of these techniques, behavioral segmentation, is so powerful, so interesting and so seemingly difficult to achieve (but it’s not!)—that it merits drilling down a little deeper.
What is Behavioral Segmentation?
Behavioral segmentation or behavioral targeting is a way of segmenting customers based on what they do. Not what they do for a living—but rather the behavioral pattern of actions they take in their daily lives. Especially important are the behaviors that are direct interactions with your brand. Or in the proximity of your brand (e.g. you offer insurance and the consumer is educating themselves on how auto insurance works using Google).
Behavioral market segmentation differs from demographic segmentation because it’s less concerned with someone’s age, how much they earn or in which zip code they reside. It differs from psychographic segmentation because it’s not concerned with their personality, values, opinions, attitudes, or lifestyles.
Rather, behavior segmentation looks at an individual’s actions. What behaviors have they exhibited historically? What are they doing on my website or app recently, or even at this very moment? And what does it say about how we can best serve their needs?
Why Behavioral Segmentation is Important
People’s demographics don’t change very often. For example, people move homes on average about every 5 years. Also, people’s personalities, values, and opinions don’t change often either (for some people we know it’s more like never). But what people want and what they need changes all the time.
Why, as marketers, does it make sense to rely solely on static segmentation techniques like demographics and psychographics in a world where consumers’ preferences and desires are constantly in flux? Answer: it only made sense when those techniques were the only ones available to us.
But with all the data our enterprises have been collecting for years about customer behavior, all the different touchpoints across which they interact with us in real-time—generating rich historical and in-the-moment first-party data—powerful behavioral marketing segmentation is now a possibility. Even a competitive necessity for companies striving to succeed in the modern customer-centric economy.
Using behavioral segmentation techniques, marketers and CX pros can identify what their target audience wants and needs today, giving you an unprecedented ability to personalize customer experiences that are helpful, unique, and drive deep brand loyalty. In the same blog about customer segmentation referenced at the beginning of this post, we talk about how (with the help of AI and machine learning) the lines between segmentation and 1:1 personalization are blurring. And that this is changing the way customer experiences are delivered. Behavioral segmentation is at the heart of that capability.
6 Techniques for Executing Behavioral Segmentation
When marketers build customer segments, they typically use attributes about the customer to create those segments. For instance, with traditional demographic segmentation, you might generate an email marketing list including all customers aged 29-35 who live in high-income neighborhoods in Georgia. The attributes in this case are age, income, and location.
For behavioral segmentation, a whole different set of very powerful attributes is available to us for cutting customer segments:
- Purchasing behavior examines the actions customers take along the way to purchase and identifies behaviors that are drivers of a future purchase. Common signals that inform this type of marketing segmentation include past customer transactions as well as behaviors along the path-to-purchase (do they first search on Google, research on the website, then buy in the store? etc.)
- Occasion-based behavior uses holidays, seasonal events, and scheduled events (like concerts or NFL games), or personal events and routines (like birthdays or eating out every Saturday night) to predict the likelihood of a future purchase.
- Usage rate looks at how often a consumer purchases products, consumes content, logs into online software, and so on, to predict propensity to purchase, increase spend, or churn.
- Purchase reasoning takes into account the fact that different customers seeking the same product may have very different reasons for doing so. I may be looking to buy a car that’s fast. You may be looking to buy a car that’s safe. We’re both in the market for a car but for very different reasons—we should be segmented separately, receiving completely different messages aligned to our interest.
- Customer loyalty examines the customer journey and creates segments based on each customer’s status along that journey. (Don’t miss our blog on how to visualize and map the customer journey.) For instance, if the customer is in the middle of a free trial with your streaming media service (clearly in the consideration stage), you may not want to put them in a segment that receives offers for your most premium subscription packages. But it does make sense to segment them for lots of great content recommendations, and educational content to learn how you use the great features you have to offer.
- Consumer status looks at the state of a consumer’s relationship with your brand to segment them appropriately. For instance, an internet service provider, might classify consumers as non-subscribers, prospects, new subscribers, longtime subscribers, churn risks, and churned customers (who have switched to a different ISP). How you message and present offers will vary based on the segment. I.e. you’ll send “win-back” offers to churned customers, but that same offer wouldn’t make sense for prospects.
Data is at the Foundation of Behavioral Segmentation
As I’ve discussed, behavioral segmentation is very powerful and can give your brand a distinct competitive advantage. But turning its techniques into reality can be challenging because it requires a level of mastery over your customer data that most organizations have not yet achieved.
To overcome that hurdle, many marketers are turning to customer data platforms (CDPs) to
- Unify customer data from every channel and touchpoint, whether online or offline, into a single view
- Analyze customer actions to enable behavioral segmentation executed 100% by marketers or with the help of AI and machine learning
- Activate those segments in the form of personalized, relevant, and timely experiences
Taking the Next Steps with Behavioral Segmentation
If behavioral segmentation techniques could be appropriate to help your business drive deeper customer loyalty, deliver superior customer experiences, and generate incremental revenue, we’d love to talk with you about how to turn it into reality. Reach out to me and my fellow experts at ActionIQ today to get the conversation started.