Here’s an important question not enough marketers ask themselves. How many unopened promotional emails are currently sitting in your personal inbox, and more importantly, why haven’t you opened them?
The answer in almost every instance is the same. Those emails are irrelevant to you. They are targeting you with one-size-fits-all blanket promos and making you feel like a name in a database. If you’re guilty of sending emails like that, it’s time to consider adopting an AI-driven marketing segmentation strategy.
By adding Artificial Intelligence (AI) into the mix, you can uncover even deeper insights at scale, refine your segments, and deliver more meaningful connections.
In this guide, we’ll explore segmentation—best practices, examples, pitfalls, AI-powered strategies, and more. Let’s dive in!
Understanding Marketing Segmentation Strategies
Marketing segmentation involves sorting a market into smaller consumer groups with similar traits, behaviors, or needs.
The goal is to personalize experiences by identifying each group’s unique preferences and behaviors and tailor messaging and offers accordingly. This customer-centric approach leads to more effective campaigns, better resource allocation, and greater return on investment (ROI).
Studies regarding these results speak for themselves but also show further need for innovation:
- According to McKinsey & Company’s Personalization report, 76% of customers favor businesses that personalize their services, and 78% are likely to make repeat purchases.
- The report also indicates that personalization can lead to a 10% to 15% revenue increase, with specific gains for individual companies ranging from 5% to 25%, depending on their sector and execution capabilities.
- According to SAP Emarsys research, almost three-quarters of U.S. marketers have increased their investment in AI in 2024.
- Business leaders are not reacting swiftly enough. A BCG survey of over 1,400 global C-suite executives reveals that 85% intend to boost AI spending in 2024. Yet, a significant portion is allocated to cost-saving measures rather than personalization. This approach is flawed.
According to the Harvard Business Review, personalization will emerge as the most thrilling and lucrative benefit of the upcoming AI boom—but only for those companies that prioritize it strategically.
The 5 Most Common AI Segment Types
Complex segmentation allows businesses to identify and target specific customer groups with highly relevant and personalized marketing messages.
AI segmentation in SAP Emarsys is a game-changer for delivering precise, relevant messages at scale. The platform’s continuously learning algorithms spot trends in customer data and create segments that adapt in real-time.
Below are five of the most commonly used AI segment types, along with brief descriptions and potential use cases.

These AI-powered segments are dynamic: as new data flows in, each segment updates automatically, reflecting changing behaviors and preferences.
By focusing on the most relevant segment types, you’ll spend less time tinkering with manual lists and more time creating meaningful experiences that drive conversions and loyalty.
Below, we’ll examine real-world examples of successful segmentation strategies that boost engagement, retention, and overall revenue.
Example 1: Personalization in Entertainment with Village Roadshow Theme Parks
Village Roadshow Theme Parks is a leading entertainment company that uses personalization to create meaningful guest experiences.
To manage customer data effectively and deliver highly targeted communications at scale, Village Roadshow Theme Parks used SAP Emarsys’ relational data segmentation capabilities.
"The ability to deliver those personalized communications on this scale, I believe, is what sets us apart from other entertainment people within that industry."
Village Roadshow achieves this level of personalization by collecting data from various touchpoints, including ticket sales, app usage, and social media engagement. SAP Emarsys enables their team to make data-driven decisions around segmentation.
"SAP Emarsys' relational data segmentation allowed us to utilize that and empowers the team to make decisions based on that segmentation."
The theme parks segment their audience based on key factors such as demographics, family size, visit frequency, and past purchase behavior.
"We mostly segment based on demographic data because that influences what ticket type they normally like to purchase."
Beyond this, Village Roadshow uses SAP Emarsys’ relational data to enhance the entire guest journey, from initial interaction to building long-term customer loyalty.
Tips for replicating Village Roadshow’s success:
- Collect and consolidate customer data from multiple sources to gain a holistic view of your audience.
- Use advanced segmentation tools, such as SAP Emarsys’ relational data segmentation, to identify meaningful customer groups based on demographics, behavior, and preferences.
- Tailor your communications and offers to each segment, ensuring relevance and value for the individual customer.
- Engage with customers at every journey stage, from initial awareness to post-purchase loyalty building.
Example 2: Data-Driven Marketing with Wella Company
Wella Company, a global leader in the beauty industry, effectively uses data-driven marketing through sophisticated segmentation strategies. Leveraging the SAP Emarsys suite of tools, Wella Company creates highly targeted and personalized campaigns that engage different customer segments.
One example of Wella Company’s data-driven approach is its personalized email campaigns. Analyzing customer data and behavior allows Wella Company to provide relevant product recommendations that drive conversions.
Tips for replicating Wella Company’s data-driven success:
- Gather customer information from diverse sources, such as purchase history and social media.
- Use segmentation to reach audience subsets with content that resonates.
- Employ automation features to create and distribute campaigns efficiently.
- Continually track performance and refine your approach to keep engagement strong.
In addition to personalized campaigns, Wella Company also uses integrated loyalty programs to build and maintain customer loyalty across different segments. Rewarding customers for engagement and purchases helps Wella Company foster long-term relationships and increase customer lifetime value.
Crafting Targeted Strategies That Drive Results
As we have learned, effective marketing segmentation strategies are essential for driving engagement and conversions. Leveraging personalization, data-driven insights, and AI technologies enhance your marketing efforts.
Prioritizing the most valuable segments ensures your resources go where they make the most significant difference, which aligns with the Pareto principle.
To begin, remember to start with these steps:
- Collect and consolidate customer data from various sources.
- Identify key customer segments based on demographics, behavior, and preferences.
- Develop personalized marketing campaigns tailored to each segment.
- Use automation tools to scale efforts and optimize performance.
- Continuously monitor and refine strategies based on data-driven insights.
Embracing these best practices allows for a more targeted, effective marketing strategy that resonates with your audience and drives business growth.
Ready to optimize your marketing segmentation? Contact SAP Emarsys today to learn how our AI-powered personalized omnichannel platform can support your goals and deliver better business outcomes.