What is segmentation?

Whether the goal is selling extremely complex industrial equipment to multinational enterprises or the latest smartphone to teens, the engine that drives modern marketing is personalization.

Just how critical is personalization for today’s savvy and demanding customers? Consider the following:

• 90 percent of customers think personalization is “appealing”
• 80 percent of customers say they’re more likely to purchase from a brand that offers personalized experiences
• 77 percent of customers are willing to pay more to a brand that provides them with a personalized experience
• 72 percent of customers say they will only consider brands that offer them personalized experiences and will reject or avoid brands that don’t
• 44 percent of customers say personalization is a major influence on their brand loyalty

And on the other side of the spectrum, we can see at the costs and consequences of failing to deliver optimized personalized experiences:

• 66 percent of customers say generic marketing and content stops them from moving forward and making a purchase
• 63 percent of customers say they will boycott a brand that delivers unimpressive (read: annoying, superficial, or just plain bad) personalization

Of course, there is a very practical and obvious problem that brands face in their attempt to deliver personalized experiences: it’s incredibly difficult, if not impossible to build a robust dossier on every prospective customer. It would be like a restaurant requiring diners to participate in an in-depth interview about their likes, dislikes, goals, concerns, and other details prior to ushering them to a table and taking their order.

Yet, as noted above, today’s customers don’t just prefer personalized experiences: they demand them. So what can brands do? Enter segmentation.

Segmentation is the process of dividing a large and diverse target market into smaller categories, whose members share certain characteristics and details (we look closer at these common elements later in this article). This enables marketers to engage customers with a meaningful and agreeable degree of personalization, but without having to intimately know each one — which is simply not possible.

While segmentation at the enterprise level is complex and sophisticated, we can illustrate the essence of this vital concept with a simple scenario.

Consider a restaurant owner who is creating a new menu. Obviously, she wants to optimize customer enjoyment and satisfaction, and consequently maximize profits and brand loyalty. Rather than randomly choosing menu items that may or may not be appealing and desirable, she leverages market research (gleaned in a variety of ways from different sources) and identifies three main groups of customers:

• The health-conscious who place a high priority on nutritious foods
• The affluent who want (and will pay for) premium international cuisine
• The professionals who want a “go-to” spot for off-site informal meetings with colleagues, customers, suppliers, etc.

Our wise restaurant owner builds her menu accordingly. And she crafts messaging on her website, across social media, and through other online and marketing offline channels so that each of these segments (i.e., customer groups) knows that her restaurant is the perfect destination for them.

In this sense, segmentation significantly increases the chance that your messages will resonate while reducing the chance of sending the wrong messages.

Segmentation enables marketers to engage customers with a meaningful and agreeable degree of personalization, but without having to intimately know each individual — which is simply not possible.

The most important benefit of segmentation is also the most appealing — when done right, it’s highly profitable. A study by Bain & Company found that over a 5-year period, brands with effective segmentation strategies generated 10 percent higher profits than brands with ineffective segmentation strategies.

Below, we highlight other benefits of segmentation that contribute, in some meaningful way, to more customers, more market share, more revenues, more competitive advantage, more brand equity — and, ultimately, more profit:

• Greater relevance: Segmentation enables brands to create relevant marketing content and messaging.
• Strategies & tactics: Segmentation helps brands see which strategies and tactics are generating the most ROI — and which approaches aren’t worth the cost.
• Improving the sales pipeline: Segmentation helps brands identify and target their most valuable and profitable customers.
• Driving brand distinction: Segmentation helps brands closely monitor their overall messaging and story, so they can clearly distinguish themselves from their competition.
• Identify niche markets: Segmentation can reveal previously overlooked (or ignored) markets that have significant customer acquisition and/or brand equity-building potential.
• Staying on message: Segmentation can help brands verify they are effectively communicating all aspects of their brand and value proposition, and not just aspects that tend to get the most airtime. For example, if analysis, research, and data tell a vehicle manufacturer that a certain customer segment is highly interested in fuel efficiency, warranty coverage, build quality, and value, the marketing content delivered to this segment should cover all of these factors versus just one or two.
• Product improvement and development: Segmentation fosters relationship-building with customers through personalization, which facilitates both formal and informal dialogue, which supports successful product innovation and development. For example, a customer who truly feels she has an authentic connection with a brand and is treated as a unique individual will be more willing to share her feedback about a product (or any aspect of a product such as delivery/implementation, support, etc.). These insights can then be combined with other data sources to improve existing offerings and develop new ones.

There are five primary types of segmentation:

1. Demographic
2. Firmographic
3. Psychographic
4. Behavioral
5. Geographic

We dive into each in detail, including examples, below. Please note, however, that the order of the list does not indicate their importance. They are all valuable, and each plays a role in unleashing the benefits described in the previous section.

1. Demographic segmentation

Demographic segmentation uses non-identifying traits to build customer categories. These traits could include:

• Age
• Gender
• Income level
• Location
• Family status (single, married, parents, etc.)
• Education level
• Ethnicity
• Religious denomination

Demographic segmentation is the type of segmentation that most non-marketers think of when they hear or read the words “market research.” An example is a luxury home builder that uses income level to target high net worth individuals and families.

2. Firmographic segmentation

Firmographic segmentation is conceptually similar to demographic segmentation, except the non-identifying details used to create customer categories are based on an organization vs. an individual, family, group, or other non-commercial entity. These traits could include:

• Organization size
• Industry
• Sector
• Job function

An example of firmographic segmentation is a human resource information system (HRIS) software solutions vendor that targets benefit directors and other HR executives. While these individuals will doubtlessly be diverse in many ways, the fact that they are all decision-makers or influencers in the HR space makes them a critically-important audience to engage and, ideally, nurture into happy and loyal customers.

Before moving to the next segmentation category, keep in mind that conventionally — and still today to some extent — firmographic segmentation is rolled into demographic segmentation. Since there is conceptual overlap between these two — they both use non-identifying traits to create customer categories — there is logic in this approach.

We have distinguished them, however, because it is generally helpful to view them as separate, given that the traits used to segment B2C audiences (such as vehicle buyers, restaurant patrons, home appliance shoppers, etc.) are generally different from those used to segment B2B audience (such as HR executives, cybersecurity specialists, etc.).

Yet, there are scenarios where some non-identifying traits will apply to both B2C and B2B audiences. For example, a company that sells a sophisticated and feature-rich smartphone app to help people be more productive may use “income level” as a segment category (or part of a segment category) when engaging both individual users and employees/executives.

3. Psychographic segmentation

Psychographic segmentation creates categories by using traits rooted in customers’ personalities, habits, and preferences. These traits could include:

• Beliefs
• Values
• Goals
• Hobbies
• Interests
• Priorities
• Motivations

In some cases, gleaning psychographic data is as simple and straightforward as gleaning demographic or firmographic data. For example, when filling out a form to download an e-book, white paper, infographic, or any other digital asset, a customer may self-identify that they aspire to get a better job in their field, that they are committed to environmental sustainability, that they love playing golf, and so on.

However, there are other cases where brands need to dig deeper to uncover these insights through methods such as one-on-one interviews, surveys, focus groups, and audience testing.

It’s extremely important for brands to avoid making assumptions about psychographic traits, since these could be incorrect and lead to disengagement rather than engagement. For example, 100 customers may disclose (through one method or another) that they will only purchase a vehicle that offers above-average fuel efficiency. However, not all of these customers may be motivated by the same beliefs and views. Half of them may be motivated to reduce their environmental footprint, and half may be motivated to reduce their long-term ownership costs.

Of course, this doesn’t mean customers cannot have multiple beliefs and views — they’re humans after all. Someone shopping for a car can be interested in both environmental sustainability and saving money. But brands must determine how to convey these value propositions in a way (or in multiple ways) that foster the most engagement and populate the sales funnel with the maximum number of qualified leads. If a car brand understands that sustainability is the most important value for a specific customer, leading with that could help close the sale.

4. Behavioral segmentation

As the term suggests, behavioral segmentation categorizes customers not on what they believe or think, but by what they do. These variables could include:

• Purchasing history
• Spending and budgeting habits
• Offline interactions with a brand
• Online interactions with a brand (such as URLs visited, referral source, time spent on site, number of visits, shopping cart value, campaign history, etc.)

An example of behavioral segmentation is targeting customers who have made a purchase within the last two years, or customers who have left a review within the last six months.

5. Geographic segmentation

While psychological segmentation is typically the most complex data source to glean (but also potentially the most valuable), geographic segmentation is usually the easiest. It simply captures information about where a customer is located, such as their:

• Country
• City
• State/province/region
• Zip code/postal code

An example of geographic segmentation is a when a brand that makes insulated and weather-resistant winter clothing targets customers who live in cold climates, or a vendor that offers tax preparation software targets customers who must comply with region-specific (state/country) filing rules and regulations.

Just as there is no one-size-fits-all way to engage and convert customers, there is no generic strategy to drive and optimize segmentation. Approaches that work for one brand may not work for another. What’s more, approaches that generate positive results today may not necessarily work in the future. Customers and marketplaces are dynamic rather than static. They are always changing, and it’s up to brands to adjust to these shifts — and ideally, to influence and lead them.

There are three fundamental segmentation tools that all brands should have in their martech stack, regardless of whether they’re aiming to engage customers in the B2B, B2C, B2B2C, or B2G space: a customer journey map, auto-personalization, and a customer data platform.

1. Customer journey map

A customer journey map is a visual representation of the totality of interactions and touchpoints that various segments experience along the buyer’s journey. Steps in the customer journey mapping process include:

• Identifying all stages that exist along the buyer’s journey (such as awareness, research, evaluation, purchase, usage, and advocacy)
• Ensuring all relevant teams (such as sales, marketing, customer success, etc.) understand and reach consensus on what is supposed to happen in each stage
• Determining the touchpoints for each stage
• Establishing the key customer activities that should happen at each stage
• identifying the content that should exist at each stage

For this latter objective — identifying content — it can be helpful to create a digital relevancy map that highlights:

• Customer intent at each stage of the journey (such as evaluating options, narrowing choices, searching for a specific product/service, etc.)
• Goals the brand wants customers to take at various touchpoints (such as watching a video, using an online calculator, scheduling a consultation, etc.)
• The precise content that exists (or will exist) to help customers fulfil their goals at each touchpoint, and in each stage (such as white papers, checklists, e-books, data sheets, use cases, etc.)

2. Auto-personalization

Auto Personalization uses AI to deliver personalized content to customers in a way that is both cost-effective and operationally efficient. This approach uses machine learning to identify and categorize segments. It also enables marketers to select the most relevant metrics for evaluating content and campaign performance.

3. Customer data platform

A Customer Data Platform (CDP) is a packaged software solution that establishes an ongoing, centralized, and standardized customer database. Key features of a robust CDP include the capacity to:

• Collect data from multiple sources (such as servers, CRM, email, etc) and unify it to create individual profiles
• Segment customers into custom audiences
• Integrate with external systems so data can be shared through emails, apps, social media, web, and mobile
• Use rules and predictive analytics to make smart decisions that reveal the most valuable customers to reach, how and when to engage them, and what content will have the greatest impact
• Activate customer insights in real-time to create unique and memorable experiences for customers across advertising, marketing, e-commerce, and customer service

Given the enormous benefits of getting it right and the costs of getting it wrong, segmentation is more than a “nice-to-have.” It’s increasingly a fundamental requirement. Regardless of how complex, multifaceted, and sophisticated marketing becomes, at its core it will always be about sparking interest, establishing trust, and fostering relationships with customers.

Segmentation is not a magic wand that makes this happen. But it is a pivotal piece of the puzzle — and for those looking to scale, it may be the most important.