Have you ever wondered why certain ads seem to speak directly to you, while others either fade into the background or make you keep scrolling? The answer lies in human behavior. Our actions, habits, and subconscious choices shape the way we interact with and purchase products, and companies can harness this information to direct their marketing strategies to certain groups of people. 

Behavioral segmentation is a marketing tool that delves into the behaviors that drive consumer decisions. This can include factors such as purchasing habits, usage rates, brand loyalty and awareness, and responses to marketing campaigns. By understanding these behaviors, companies can tailor and optimize their marketing efforts to better meet the needs and preferences of different customer segments.

Behavioral segmentation is a distinct type of market segmentation, which is the practice of dividing a target audience into smaller groups based on certain characteristics.¹ There are several main types of market segmentation, including demographic, geographic, psychographic, technographic, and transactional, each focusing on different aspects of the consumer base. While these other segmentations look at who makes up a product or service’s customer base, behavioral segmentation looks at what those customers actually do. But why is behavior so important in marketing? 

When trying to understand what customers want, it’s crucial to go beyond simple demographic information and examine concrete behaviors. To better understand why, let’s look at an example. Consider, on one hand, the legendary British musician “Ozzy” Osborne, former lead singer of Black Sabbath, and on the other hand, King Charles III, the current British monarch. Both men are white, born in 1948, originally from England, and rather wealthy. On paper, they appear to be very similar. 

However, their behaviors couldn’t be more different. Ozzy is known for his outlandish, eccentric, and sometimes shocking on-stage behavior, while King Charles is considered to be a man of few words, usually maintaining a thoughtful and composed demeanor. If a brand marketer wanted to target both men effectively, they would probably need two drastically different approaches. For example, perhaps Ozzy would be drawn to a commercial with bright, flashing colors and loud background music—meanwhile, King Charles may prefer traditional, even simple fonts and graphics, accompanied by soothing sounds. 

There are several different ways to segment customers according to their behaviors, but these are some of the most common:²

• Purchase behavior: This approach uncovers the diverse trends and patterns customers exhibit when deciding to make a purchase. This type of behavioral segmentation offers valuable insights into a customer’s mentality throughout the purchasing process, the challenges they encounter, and the incentives they are most likely to respond to, among other factors.
• Occasion and timing: This segmentation categorizes customers according to when they are most likely to view an advertisement, interact with a brand, or purchase from a website. For example, customers could be everyday shoppers who make purchases throughout the year or holiday shoppers who only make purchases on special occasions. This approach helps brands to know exactly when and how often to target certain audience members. 
• Benefits sought: Different customers want different benefits from a product or a service; some prioritize quality while others look for the best deals and discounts. This segmentation divides the audience based on the unique value proposition various customers seek to gain from a product or service. Understanding what drives customer purchases helps to define which product feature or service aspect to emphasize in marketing. 
• Customer loyalty: Some shoppers stick with brands throughout their lives while others constantly switch based on price, availability, or popularity. This approach looks at the level of loyalty a customer has with a brand and helps to understand the behaviors of existing and repeat buyers. Understanding why these customers keep coming back can significantly enhance marketing campaigns and help increase brand loyalty.

Market Segmentation: The process of dividing a broad consumer or business market into sub-groups of consumers based on shared characteristics such as demographics, behaviors, psychographics, or geography. 

Usage Rate: The frequency with which customers use a product or service. This is a key factor in behavioral segmentation, as it helps identify high-usage customers who may need special attention or low-usage customers who may benefit from re-engagement strategies.

Brand Loyalty: The tendency of customers to repeatedly purchase from a specific brand. In behavioral segmentation, loyal customers are often segmented into their own group for retention-focused marketing strategies.

Customer Relationship Management (CRM): A system or strategy used by businesses to manage interactions with current and potential customers. CRM systems leverage data to help companies improve their relationships with customers through targeted marketing, personalized communications, and better customer service.

Database Marketing: A marketing strategy that uses customer data stored in databases to identify, segment, and target specific groups with tailored marketing messages. It plays a key role in behavioral segmentation by allowing businesses to analyze customer behaviors and patterns, helping to create more personalized and effective marketing campaigns.

To understand the history of behavioral segmentation, we first need to look back at the evolution of marketing segmentation in general. The idea of targeting products and services to specific subgroups of consumers is believed to date back to the 1820s when German and British booksellers directed their efforts to segments in the market based on price, geography, demographics, and psychographics.³ The concept quickly spread across the rest of Europe and eventually to the United States where it was adopted by other big brands such as General Motors and Ford. The latter’s highly successful mass marketing strategy, “A car for every purse and purpose,” marked one of the largest deployments of segmentation strategies of its time. 

However, it wasn’t until the following century in 1956 that the term “market segmentation” entered the business lexicon when Wendell R. Smith, an American professor of marketing, wrote about the process in his article, “Product Differentiation and Market Segmentation as Alternative Marketing Strategies”.⁴ In this paper, Wendell argued that targeting specific market segments could be more effective than a one-size-fits-all approach, encouraging brands to look for more ways to target their audiences.

Almost a decade later, American market research pioneer Daniel Yankelovich noted that segmenting customers by demographic factors, such as age, income, or location, was not enough and that they needed to be differentiated by their behaviors and the drivers behind them.⁵  Later known as “psycho-behavioral segmentation,” Yankelovich’s approach looked at why people behave the way they do and tried to divide them into groups based on this information. Since then, studies have shown that behavioral segmentation is superior to demographic segmentation because it can capture clear, discrete, relevant, and actionable differences within populations.⁶

As marketing segmentation developed over the twentieth century, various systems were invented to help businesses streamline their customer relations and marketing strategies. In the 1980s, what we now know as Customer Relationship Management (CRM) began to emerge, largely due to the efforts of database marketing pioneers Robert and Kate Kestnbaum.⁷ The Kestnbaums were among the first to recognize the potential of systematically analyzing customer data to improve marketing efforts. They developed methods for using customer databases to predict buying behaviors, identify high-value customers, and tailor marketing messages to specific segments. Database marketing—analyzing and leveraging data to identify which customers are most likely to engage with a marketing campaign—allowed companies to customize their communications, leading to higher engagement and retention rates.

As database marketing evolved, it laid the groundwork for modern CRM systems, which integrate customer interactions across various channels. Today’s CRM systems allow companies to segment their customer databases quickly based on multiple parameters, including behavioral patterns, enabling marketers to identify trends, target specific groups more effectively, and drive the evolution of behavioral segmentation as a core strategy in personalized marketing.

In recent years, artificial intelligence (AI) and big data have had a profound impact on the scope and potential of behavioral segmentation in marketing. Advanced analytics and machine learning algorithms enable marketers to analyze vast and complex datasets and uncover deeper insights into consumer behavior. Thanks to the availability of more consumer data, behavioral segmentation now includes more nuanced factors such as customer journey stages, engagement levels, and predictive behaviors. In particular, marketers can use real-time data to quickly determine what content to target customers and which channel to employ at what moment, thanks to the data that is collected and generated by AI algorithms.⁸ These technologies enable marketers to provide more personalized experiences for their customers and design hyper-tailored marketing strategies that resonate with the behaviors and needs of their diverse audiences.

Wendell Smith

American professor of business administration and marketing, as well as former President of the Marketing Science Institute in Philadelphia, Smith originally coined the term “market segmentation.”

Daniel Yankelovich

Prominent American public opinion analyst, social scientist, and market researcher known for his pioneering work in the field of public opinion, social trends, and interpreting public attitudes and behaviors. 

Robert and Kate Kestnbaum

American database marketers who laid the groundwork for modern customer relationship management (CRM) systems and targeted marketing practices.

Behavioral segmentation can revolutionize the way brands and companies connect with their audiences which, in turn, can save companies lots of time and, of course, make them more money. 

Research shows that consumers, particularly digital natives such as Gen Z, increasingly want personalized interactions with brands including tailored ads, product recommendations, and post-purchase follow-ups.⁹ By using data about the behaviors of specific audience segments, marketers can achieve the highly targeted and personalized marketing campaigns expected by today’s consumers, leading to higher engagement and conversion rates and overall increased customer satisfaction.

Behavioral segmentation can also help brands and companies be more efficient and cost-effective in their marketing endeavors. By filtering customers or potential clients that display the highest level of engagement with a product, service, or brand, marketers can make more informed decisions about how best to allocate time, budget, and resources. This ensures that efforts are directed toward customers who are more likely to convert, reducing wasted spend on less responsive audiences.

Overall, by aligning marketing efforts more closely with customer behavior, brands and companies are more likely to achieve better performance outcomes, leading to a higher return on investment (ROI) for marketing activities.

As with any type of segmentation, behavioral segmentation doesn’t always give you the full picture. One limitation is that it doesn't provide a complete understanding of consumers, as it focuses solely on current or past behaviors without accounting for the underlying motivations, emotions, or broader contextual factors that drive these actions. This can lead to oversimplified strategies that fail to resonate with deeper, evolving needs. To mitigate this challenge, behavioral segmentation can be combined with other segmentations to provide a more nuanced understanding of different consumer segments.   

Another drawback of behavioral segmentation is that consumer behavior is changeable and cannot always be predicted correctly. Segments based on past behaviors may quickly become outdated, leading to less effective interventions and missed opportunities to engage with consumers as their behaviors and preferences shift. 

Take, for instance, the COVID-19 pandemic. Imagine a company segments its customers based on their historical purchasing behavior, identifying a group of frequent in-store shoppers. They develop marketing strategies targeting this segment with enticing in-store promotions and discounts. However, as the pandemic hits, many of these customers shift to online shopping out of necessity and convenience. Despite their previous in-store behavior, these customers now prefer online shopping, making the original segmentation outdated. The need to continually review and revise behavioral segmentations to account for new trends, life changes, or external events can make this approach quite time-consuming and costly. 

A final challenge regarding behavioral segmentation involves ethical concerns around privacy and transparency. As companies gather more data on consumer behaviors, there is a risk of overstepping boundaries and using personal information in ways that customers may not be aware of or comfortable with. Issues like data collection without explicit consent or using insights to manipulate customer behavior raise questions about the limits of ethical marketing practices. 

For example, targeting vulnerable groups with specific offers or exploiting psychological triggers could lead to accusations of manipulation rather than providing value. To mitigate these concerns, companies are encouraged to adopt transparent data practices, ensure that customers understand how their data is being used, and implement measures that respect user privacy, such as offering clear opt-in and opt-out options. By addressing these ethical considerations, businesses can build trust with their customers while still benefiting from the insights gained through behavioral segmentation.

Personalizing product experiences

If you’re a subscriber to Netflix or any other digital streaming service, you’ll be familiar with their personalized promotional emails and “hand-picked” in-app recommendations. Netflix uses a type of behavioral segmentation called “product usage” to understand their customers’ usage patterns, including time spent on the app, types of movies or TV shows viewed, and devices most commonly used.¹⁰

What does Netflix do with this information? They analyze it and use it to offer customers tailored viewing experiences, helping them to identify new shows and navigate the app according to their behaviors. For instance, if a person consistently watches horror movies and true crime series, Netflix hooks onto this pattern and starts recommending similar content. This monitoring is all done through methods like cluster analysis or predictive algorithms to try and truly understand what the user might want to watch next. Although, as our staff writer Preeti Kotamarthi explains in her article on personalization in tech, there are simple ways to hide your true self from the brands that are trying to grasp who you are (or at least who they think you are). 

Nike, one of the most recognized sports brands in the world, also uses data from its app and other connected devices to deepen its relationship with customers and better understand their purchasing behaviors.¹¹ In 2018, Nike acquired Zodiac, a leading data analytics company to help bring together data points from customers that use the Nike app and other connected devices such as Fitbits and Garmins. The insights from this data are used to understand customer habits and behaviors and predict their purchasing behavior. 

According to Nike’s own website, the average running shoe generally lasts between 300 and 500 miles, depending on the user. By looking at the number of miles run by a user on the Nike running app, Nike can send the runner a reminder or new shoe recommendations when they start to reach the upper limit. Equally, if a loyal Nike customer usually buys a new pair of gym shorts every six months through the app and it’s been nine months since their last purchase, Nike can reach out to that customer and prompt them back into their buying routine. 

By deeply understanding their customer’s habits and behaviors, both Netflix and Nike are able to optimize their marketing strategies and offer customers better products and services.

Behavioral Change

While a definite mainstay of marketing, behavioral segmentation is also used in other fields including behavioral change. Behavior change, the process of altering or modifying an individual's or group's behaviors, attitudes, and habits, is often applied in international development, healthcare, education, and workplace and organizational management to bring about positive changes in people’s lives. 

Behavioral segmentation is crucial in behavioral change because it allows for the customization and targeting of interventions, strategies, and communications to specific groups of people. Not everyone responds to change or new ideas in the same way. That is, their potential “margin” for change varies; some people might be early adopters of a new idea while others may be more resistant to change. 

Project managers can use behavioral segmentation to help understand the unique barriers and motivators that influence people’s decision-making processes and then segment the population into groups according to these factors. From there, a behavior change campaign can target different groups depending on their potential for change. 

In a recent project based in the UK, London-based consultancy The Behaviouralist used behavioral segmentation to identify the segments of the population with the highest margin for becoming the first users of the new “Mobility-as-a-Service” (MaaS) platform.¹² The service allows users to plan, book, and pay for a wide range of travel including public transport, e-scooters, bikes, and car sharing. By segmenting the population by their margin for behavioral change, the project was then able to set realistic target behaviors for each group—from simply downloading the MaaS app to using it for their daily travel needs—and integrate these into their campaign. 

Behavior Change

There are many reasons why a change in behavior might be desirable. Better health outcomes, improved attendance at school or more positive attitudes towards the environment. This article looks specifically at the art of “nudging” and how we can understand people’s goals and help them achieve them more effectively. We look at different behavior change frameworks and how they can be applied to different challenges. 

Three Thought Patterns That Let Advertisers Influence You on Social Media

Besides behavioral segmentation, marketers have many other tricks up their sleeves when it comes to pushing you into making a purchase. The rise of social media has had a profound effect on the advertising industry, forcing marketers to look more closely at human behavior and the way we think in order to influence our decision-making. This article looks at the new dimension of advertising: viewer’s exposure to other viewers. 

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