Revamp Your Marketing Campaigns With AI Customer Segmentation | Pecan AI

Revamp Your Marketing Campaigns With AI Customer Segmentation

Learn the pitfalls of traditional customer segmentation, and check out how today's AI can revitalize your campaigns with precise targeting.

In a nutshell:

  • Traditional customer segmentation based on demographics is limited and assumes all people in a demographic act the same.
  • Artificial intelligence-powered customer segmentation is a modern solution that provides precision, dynamism, efficiency, and predictive capabilities.
  • AI segmentation allows for more accurate targeting, reflects real-time changes in buyer behavior, and improves ROI.
  • It can be applied to predict customer churn, assess potential lifetime value, and identify VIP customers and their preferences.
  • Incorporating AI customer segmentation into marketing campaigns can lead to stronger, more informed decisions and transformative results.

As a marketer, you deal with many moving pieces. From changing markets to surprising buyer behavior, something is always evolving.

Thankfully, customer segmentation simplifies giant audiences into a few groups that you can target, manage, and convert. But times are changing, and so are best practices regarding segmenting your customers. 

In this blog, we discuss the ways traditional customer segmentation falls short and argue for a more modern solution: AI-powered customer segmentation. We’ll explain the history and advantages of AI customer segmentation with machine learning and suggest some easy and simple ways to implement it into your data-driven strategy development.

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Limitations of traditional customer segmentation

When we think of traditional customer segmentation, basic demographics come to mind. Location, occupation, gender, and other characteristics define the foundation of our targeting. 

There’s a key assumption at play here: All people in that demographic act the same.

We know that’s not true. All CEOs don’t operate the same way, nor does any other subgroup we can think up. No demographic is a monolith, and we shouldn’t be building key marketing strategies off of the assumption that they are.

Traditional customer segmentation was ground-breaking when it first entered the marketing world, but that was in 1956. Things have changed; AI is changing the way we work, and our approach to segmentation should evolve with it. 

The rise of AI customer segmentation

AI-driven customer segmentation is the modern-day solution to overly simplified, traditional segmentation tactics. It skips the assumptions and leans into the reality that people and their purchasing behaviors are complicated. Essentially, it allows you to target customers with surgical precision.

In the past few years, you’ve probably seen AI-powered customer segmentation show up in the platforms you use for digital advertising and marketing campaigns. Google Ads has integrated AI customer segmentation into their audience targeting tools, for example.

But if you’re not taking full advantage of AI segmentation in your day-to-day marketing strategy, you’re missing out on some major opportunities for growth. 

AI customer segmentation has been on the rise because, simply put, it produces better results. It abandons traditional methods’ assumptions for nuance, and it’s extremely dynamic, changing with markets, audiences, and more.

Note: We know that learning about AI tools can be intimidating. You’re a marketer, not a computer scientist. We’ve created The CMO’s Guide to Predictive Analytics to help make the argument for AI in a way that’s easy to understand.

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Benefits of AI customer segmentation

Our State of Predictive Analytics report demonstrated that 100% of marketing decision-makers wanted to see expansion in their company’s AI-powered capabilities. AI segmentation using machine learning trumps traditional customer segmentation methods by almost every measure, discovering layers of nuance that basic analysis can’t compute.

Here are some of the benefits of incorporating AI into your customer segmentation practices.


AI tools — like Predictive GenAI — that assist in customer segmentation use data patterns that tell a more nuanced story of who is buying what. It doesn’t slice your target audience into chunky, assumptive demographics. Instead, it paints a precise picture of how individuals fit into different categories. 

Traditional segmentation methods have put precision to the wayside in exchange for simplicity. But buyers aren’t simple. 

Utilizing AI with predictive models to define your segments creates a far more accurate depiction of who your buyers are, which can have a massive impact on your bottom line. Settling for assumptions worked in the past, but AI offers you unbeatable precision and accuracy.


Chances are, your segmentation hasn’t budged too much despite the reality that people, groups, and markets are always changing. AI customer segmentation with machine learning is dynamic. These advanced algorithms skip any assumptions and portray an accurate image of what your target audience is doing in the present day.

Many things can affect buyer behavior. From changes in your competition to economic recessions, buyers are impacted daily by the things going on around them, and AI can help reflect those nuances. 

Traditional segmentation methods don’t leave space for yearly, monthly, and even daily evolutions. AI customer segmentation is built on the truth that the world is ever-changing. 

Efficient for your ROI

Here’s the truth: AI models have higher upfront costs than traditional segmentation models. However, the benefits are astronomical, producing an improved ROI despite a larger investment. 

With more precise and dynamic targeting, your ads and personalized content can reach only high-intent users, leading to higher customer LTV. AI customer segmentation tools' unmatched accuracy pushes clickthrough rates, conversion rates, and retention rates through the roof.

Predictive capabilities 

Finally, artificial intelligence can do something that no traditional model can: predict future behavior. Predictive analysis is our bread and butter, and we know the benefits of predictive capabilities on your bottom line. 

AI models utilize historical customer data patterns identified in the past and make incredibly accurate predictions for the future. The level of analysis that an AI program can handle is far beyond any basic analytics program, and it can have a huge role in improving your marketing campaigns’ efficacy.

49% of marketers often or always feel like they’re guessing when making day-to-day decisions. AI’s predictive capabilities help clarify the guesswork, so you can count on your customer segmentation strategy to be accurate for the present and future.

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Real-world applications of AI-driven customer segmentation

If you’re considering integrating AI segmentation into your high-level marketing strategy, you’ll want to identify key spots where you’ve reached conclusions based on basic demographic analysis. 

Replacing those basic assumptions with AI customer segmentation data is the key to reaping the full benefit of an artificial intelligence tool. Here are a few different areas that can be honed in based on AI customer segmentation data:

Predicting customer churn

What makes a customer stop using your product or service is a question that AI customer segmentation can provide great insight into. Chances are, the answer isn’t simple enough for basic demographic analysis to answer.

An AI customer segmentation tool can zoom in on exactly the types of users who are ditching your product, providing rich insights about what segments need more care and investment so you can preemptively predict and combat churn and boost customer loyalty

Assessing potential lifetime value (LTV)

Not all customers are created equal, and the potential lifetime value (LTV) metric proves it. Identifying accurate LTVs allows you to make data-driven decisions on who to invest your marketing budget into.

Perhaps a group with a low LTV needs more investment, or maybe you want to continue to nurture segments with high LTVs. Regardless of your strategic decisions, AI segmentation with your customer data is going to give you a more precise and accurate image of different customer groups’ LTVs.

Identifying VIP customers & their preferences

Finally, AI customer segmentation allows you to unlock information about your VIP customers. An insightful AI customer segmentation process will provide a richer picture of those VIP customers and help you expand that bracket of spenders. You can also learn how to improve your user experience for customer segments that you know are already benefiting from your service.

Which AI-powered tools can help in enhancing customer segmentation?

  • Predictive Analytics: AI-driven models analyze historical data to forecast customer behaviors and lifetime value, enabling more accurate, forward-looking segmentation.
  • Machine Learning Clustering: Automatically groups customers based on multiple variables, uncovering hidden patterns.
  • Natural Language Processing (NLP): Analyzes customer experience feedback and social media to conduct sentiment analysis and establish preferences for segmentation.
  • Recommendation Engines: Track behavior to suggest products, revealing customer affinities useful for segmentation in digital marketing and elsewhere.
  • Chatbots: Collect data on customer preferences and behaviors while providing service, enhancing segmentation insights.
  • Personalization: Data from these AI tools enables tailored marketing strategies for specific customer segments.

What are the practical steps involved in implementing AI in customer segmentation?

Here are the practical steps involved in implementing AI for customer segmentation using a predictive analytics platform:

  1. Data Collection and Preparation: Gather relevant customer data from various sources. Clean and preprocess the data (unless you're using an automated data preparation method). Ensure data quality and consistency.
  2. Define Segmentation Objectives: Clarify business goals for segmentation. Identify key metrics and outcomes to measure success.
  3. Select and Set Up Low-Code Predictive Analytics Platform: Choose a platform that fits your business needs and technical capabilities. Set up the platform and integrate it with your data sources. Familiarize yourself with the platform's interface and capabilities.
  4. Configure Segmentation Model: Use the platform's interface to select relevant variables for segmentation with predictive modeling. The platform will guide you as you set up options.
  5. Run Automated Analysis: Initiate the platform's automated modeling process. Allow the system to identify patterns and create segments. Review initial results and adjust configurations if necessary.
  6. Segment Creation and Analysis: Examine the segments created by the platform. Analyze segments for actionable insights and characteristics. Use the platform's visualization tools to understand segment differences.
  7. Implementation and Integration: Use the platform's export features to integrate results into marketing and CRM systems. Set up automated processes for updating customer segments.
  8. Testing and Validation: Use the platform's testing features to validate segmentation effectiveness. Compare results against previous segmentation methods.
  9. Continuous Monitoring and Refinement: Regularly review the platform's performance metrics. Use the platform's features to refine and update models as needed.

This approach leverages the low-code platform to simplify the technical aspects of modeling, allowing you to focus more on business objectives and interpreting results. You can begin making an impact on your customer outcomes without worrying about the technical details behind the scenes.

Start targeting the right customers – every time

The AI customer segmentation process can have a transformative impact on your marketing strategy. With precise, dynamic, and useful AI-powered insights, you can count on making stronger, more informed decisions. 

While integrating good AI tools can seem complicated, it’s easier than you think. Pecan specializes in helping businesses take full advantage of predictive AI with innovative machine learning algorithms and an infusion of generative AI. This technology can radically impact your bottom line, increasing revenue and engaging customers like never before.

Give it a try yourself now with a free trial, or sign up to get a personalized demo.