
Not all customers are the same, so why waste your budget marketing to them like they are? McKinsey research shows that 71% of consumers want personalized shopping experiences, and 76% get frustrated when they don’t have them. That’s where demographic segmentation comes in.
But what is demographic segmentation, exactly? We define it as a process that helps you categorize your audience into meaningful demographic groups so you can reach the right people with impactful custom messages.
Businesses across industries are partnering with Experian to power smarter decisions and better results through solutions like demographic segmentation — but what does this look like in action? This article breaks down five real-world demographic segmentation examples, showing how businesses have worked with us to drive measurable success so you can see exactly how it can work for you.
What is demographic segmentation?
Demographic segmentation involves dividing your audience into smaller, more specific groups based on shared demographics like income, education, gender, job, family status, and more to gain a more granular understanding of your brand’s target segments. The better you know your audience, the better you speak to their unique needs — and the more effective your campaigns will be, as you’ll be able to target each segment with highly personalized content that resonates.
For instance, a company might market a new tech gadget to young adults in one way while promoting the same product to families with young children in a completely different way, ensuring the message speaks to each group’s lifestyle and priorities.
Demographic segmentation attributes
Some of the most common attributes used in demographic segmentation include:
Benefits of using demographic segmentation
Demographic segmentation offers several valuable benefits for marketers. Here’s why it’s one of the most commonly used and effective ways to target audiences:
- Improved targeting and personalization: Demographic segmentation powers highly customized campaigns so you can cater to different income levels, family structures, job types, and so forth. B2C brands can provide offers based on factors like age, income, and gender, while B2B brands can target by occupation to reach decision-makers.
- Better product and service development: Understanding which demographics use your product or service is a great way to inform future improvements.
- Higher engagement: With highly customized content, you can speak directly to specific demographic groups and increase engagement.
- Cost efficiency: As you target the most relevant segments, you optimize your spending around the most likely buyers and will see better returns.
- Increased conversion and retention: Relevant, targeted messaging leads to higher conversion rates, and when people feel understood, they’ll want to keep coming back.
- Clearer customer insights: Demographic data provides precise, actionable insights for refining your marketing strategy.
- Simplicity and effectiveness: Demographic insights are immediately actionable and easy to implement, which gives you a great starting point for focused campaigns.
When to use other segmentation types
While demographic segmentation provides valuable consumer insights, there are times when other approaches may offer a more effective strategy:
- Your business provides location-dependent services. If you strictly serve a local area, geographic segmentation would be more effective in targeting customers based on location.
- You have access to detailed behavioral data. If you collect data on customer behavior (like browsing history or purchase patterns), behavioral segmentation would allow for more personalized targeting than demographics.
- You’re selling high-end luxury products. While income is a useful demographic variable, factors like values, aspirations, and lifestyle better capture the desires of luxury consumers.
- Your target audience shares similar behaviors, regardless of demographic factors. Behavioral segmentation might offer more insight if your customers engage with your product or service based on shared behaviors rather than demographic traits.
- Your product or service targets specific needs or pain points. Segmenting by need or issue rather than traditional demographic variables would likely yield better results if you’re offering a solution to a particular problem (like a health-related product).
How our customers are using demographic segmentation to produce tangible results
Demographic segmentation is about knowing your audience and using data to create marketing strategies that drive measurable outcomes. Let’s look at some real-world use cases from brands like yours that have been successful in this effort, working with Experian to translate demographic insights into significant business growth.
Use case #1: Identifying customer spending potential to boost growth for a retail chain
These demographic segments provided the marketing strategy the retail chain used to target $1.1 billion in unrealized spend. This revealed how much additional revenue could be captured by targeting the right customers with tailored marketing and offers through demographic segmentation.
Use case #2: Helping a financial institution identify regional DE&I opportunities
Use case #3: Segmenting a health supplement ambassador program for enhanced engagement
Use case #4: Comparing customer bases: Insights for a retailer across two cities
These adjustments led to improved engagement and higher sales in both cities.
Use case #5: Optimizing direct mail to help a nationwide retailer maximize impact on a limited budget
Explore demographic segmentation with Experian
Now that we’ve defined demographic segmentation and provided real-world examples, it’s time to explore how Experian data can help you better understand and connect with your audience. Experian’s Marketing Attributes provide rich, privacy-conscious insights into consumer demographics, lifestyles, and behaviors. These insights empower marketers to personalize experiences, refine targeting strategies, and make more informed decisions. With a deeper understanding of who your customers are, you can create more meaningful, impactful campaigns that drive stronger engagement and results.
Connect with us today to see how our data and expertise can improve your targeting, personalization, and campaign performance.
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Originally appeared on MarTech Series Marketing’s understanding of identity has evolved rapidly over the past decade, much like the shifting media landscape itself. From the early days of basic direct mail targeting to today's complex omnichannel environment, identity has become both more powerful and more fragmented. Each era has brought new tools, challenges, and opportunities, shaping how brands interact with their customers. We’ve moved from traditional media like mail, newspapers, and linear/network TV, to cable TV, the internet, mobile devices, and apps. Now, multiple streaming platforms dominate, creating a far more complex media landscape. As a result, understanding the customer journey and reaching consumers across these various touchpoints has become increasingly difficult. Managing frequency and ensuring effective communication across channels is now more challenging than ever. This development has led to a fragmented view of the consumer, making it harder for marketers to ensure that they are reaching the right audience at the right time while also avoiding oversaturation. Marketers must now navigate a fragmented customer journey across multiple channels, each with its own identity signals, to stitch together a cohesive view of the customer. Let’s break down this evolution, era by era, to understand how identity has progressed—and where it’s headed. 2010-2015: The rise of digital identity – Cookies and MAIDs Between 2010 and 2015, the digital era fundamentally changed how marketers approached identity. Mobile usage surged during this time, and programmatic advertising emerged as the dominant method for reaching consumers across the internet. The introduction of cookies and mobile advertising IDs (MAIDs) became the foundation for tracking users across the web and mobile apps. With these identifiers, marketers gained new capabilities to deliver targeted, personalized messages and drive efficiency through programmatic advertising. This era gave birth to powerful tools for targeting. Marketers could now follow users’ digital footprints, regardless of whether they were browsing on desktop or mobile. This leap in precision allowed brands to optimize spend and performance at scale, but it came with its limitations. Identity was still tied to specific browsers or devices, leaving gaps when users switched platforms. The fragmentation across different devices and the reliance on cookies and MAIDs meant that a seamless, unified view of the customer was still out of reach. 2015-2020: The age of walled gardens From 2015 to 2020, the identity landscape grew more complex with the rise of walled gardens. Platforms like Facebook, Google, and Amazon created closed ecosystems of first-party data, offering rich, self-declared insights about consumers. These platforms built massive advertising businesses on the strength of their user data, giving marketers unprecedented targeting precision within their environments. However, the rise of walled gardens also marked the start of new challenges. While these platforms provided detailed identity solutions within their walls, they didn’t communicate with one another. Marketers could target users with pinpoint accuracy inside Facebook or Google, but they couldn’t connect those identities across different ecosystems. This siloed approach to identity left marketers with an incomplete picture of the customer journey, and brands struggled to piece together a cohesive understanding of their audience across platforms. The promise of detailed targeting was tempered by the fragmentation of the landscape. Marketers were dealing with disparate identity solutions, making it difficult to track users as they moved between these closed environments and the open web. 2020-2025: The multi-ID landscape – CTV, retail media, signal loss, and privacy By 2020, the identity landscape had splintered further, with the rise of connected TV (CTV) and retail media adding even more complexity to the mix. Consumers now engaged with brands across an increasing number of channels—CTV, mobile, desktop, and even in-store—and each of these channels had its own identifiers and systems for tracking. Simultaneously, privacy regulations are tightening the rules around data collection and usage. This, coupled with the planned deprecation of third-party cookies and MAIDs has thrown marketers into a state of flux. The tools they had relied on for years were disappearing, and new solutions had yet to fully emerge. The multi-ID landscape was born, where brands had to navigate multiple identity systems across different platforms, devices, and environments. Retail media networks became another significant player in the identity game. As large retailers like Amazon and Walmart built their own advertising ecosystems, they added yet another layer of first-party data to the mix. While these platforms offer robust insights into consumer behavior, they also operate within their own walled gardens, further fragmenting the identity landscape. With cookies and MAIDs being phased out, the industry began to experiment with alternatives like first-party data, contextual targeting, and new universal identity solutions. The challenge and opportunity for marketers lies in unifying these fragmented identity signals to create a consistent and actionable view of the customer. 2025: The omnichannel imperative Looking ahead to 2025 and beyond, the identity landscape will continue to evolve, but the focus remains the same: activating and measuring across an increasingly fragmented and complex media environment. Consumers now expect seamless, personalized experiences across every channel—from CTV to digital to mobile—and marketers need to keep up. The future of identity lies in interoperability, scale, and availability. Marketers need solutions that can connect the dots across different platforms and devices, allowing them to follow their customers through every stage of the journey. Identity must be actionable in real-time, allowing for personalization and relevance across every touchpoint, so that media can be measurable and attributable. Brands that succeed in 2025 and beyond will be those that invest in scalable, omnichannel identity solutions. They’ll need to embrace privacy-friendly approaches like first-party data, while also ensuring their systems can adapt to an ever-changing landscape. Adapting to the future of identity The evolution of identity has been marked by increasing complexity, but also by growing opportunity. As marketers adapt to a world without third-party cookies and MAIDs, the need for unified identity solutions has never been more urgent. Brands that can navigate the multi-ID landscape will unlock new levels of efficiency and personalization, while those that fail to adapt risk falling behind. The path forward is clear: invest in identity solutions that bridge the gaps between devices, platforms, and channels, providing a full view of the customer. The future of marketing belongs to those who can manage identity in a fragmented world—and those who can’t will struggle to stay relevant. 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