The Limits of Customer Segmentation in Ecommerce Personalization

We've already covered the basics of segmentation in a previous article, where we explored how breaking your audience into targeted groups can improve personalization efforts. However, while customer segmentation is a step in the right direction, it has significant limitations for ecommerce personalization:

• Sub-optimal: Segmentation is based on predefined attributes identified by the marketeer, often rooted in purchase history, but this approach sometimes misses other important factors such as traffic sources or more nuanced individual customer preferences that might have not been on the radar of the marketing team
• Operationally demanding: Running A/B tests requires continuous setup, tracking, and result analysis, making it resource-intensive to maintain over time.
• Time-consuming and expensive: Reaching statistical significance for tests can take weeks, sometimes months, leading to costly delays before actionable insights are obtained.
• Needs constant updating: Seasonal shifts or macroeconomic changes can disrupt segmentation models, requiring frequent adjustments to keep the data relevant.

Ultimately, segmentation provides a somewhat sub-optimal solution, which doesn’t engage customers on a truly personal level, while requiring significant resources and investment. To overcome these challenges, leading brands are moving beyond segmentation toward more dynamic, user-level personalization that is rooted in AI —something we'll dive into next.

How AI Overcomes the Limitations of Segmentation

AI-powered 1:1 personalization goes beyond basic segmentation, addressing its core limitations and enabling a more efficient, effective approach to engaging customers individually. Below, we’ll explore four key ways AI enhances personalization in ecommerce, from reducing operational load to adapting in real-time to market changes. Each of these points highlights how AI transforms segmentation into a powerful, scalable solution for driving higher engagement, conversions, and revenue.

No Need for Predefined Segments

Manually hypothesizing on which consumer attributes are relevant to inform segmentation is quickly becoming a thing of the past. Perhaps the biggest advantage of AI in personalization is that it doesn’t rely on predefined segments. Because human behavior is sometimes unexpected and often doesn’t function in a straight line, AI models can be used to analyze data and identify behavior patterns that would be unexpected at first glance. Moreover, AI models can identify if different business outcomes have different relevant consumer attributes to inform segmentation. A personalization strategy rooted in AI might optimize for list growth with a different set of attributes than a strategy calibrated to optimize for conversion. This results in more optimal recommendations, leading to improved performance.

Less Work, More Results

 Traditional segmentation requires continuous oversight. Setting up campaigns, organizing lists, tracking impact, and analyzing results - all manual efforts. By automating the entire process of segmentation, testing, and optimization, AI reduces the operational workload considerably. With an AI-driven solution, brands can scale their personalization efforts without needing a large team to monitor and adjust campaigns. This not only decreases overhead costs but also allows brands to allocate resources to other growth initiatives. In practice, brands often see an increase in the number of personalized touchpoints they can offer, leading to improved customer satisfaction and retention.

Faster Insights and Continuous Improvement

Traditional A/B testing tools require lengthy testing and analysis phases to reach statistical significance. Monocle uses an "Explore-Exploit" model that merges these phases, simultaneously optimizing and dynamically adjusting as data rolls in. Rather than waiting for a single treatment to reach statistical significance, this approach allows merchants to quickly identify trends and start leaning toward optimal decisions in real time, driving higher revenue per user.

Adapts in Real-Time to Market Changes

Finally, AI-driven personalization is responsive to macro trends and shifting markets such as seasonal trends or economic changes. An additional benefit of the explore-exploit model is a decision making tool called a multi-armed bandit model.

A multi-armed bandit model is meant to be used when you have multiple choices, each with an uncertain outcome. Imagine a gambler choosing between several slot machines, each with a different chance of winning. The gambler needs to figure out which machine pays out the best by trying each one and then sticking with the machine that seems to win the most.

In ecommerce terms, the multi-armed bandit model is useful during A/B testing where potential outcomes change frequently. So whether it’s BF/CM season or the middle of May, or there’s a major election or a slow ads cycle, the discounting model you’re using shouldn’t rely on assumptions. Instead, Multi-arm bandits  can continuously analyze signals and adapt predictions based on real-time results,offering incentives in a way that’s attuned to recent seasonal cyclicality or recent changes in macro environment.

How AI-Powered 1:1 Personalization Drives Better Results

AI-powered personalization allows ecommerce brands to deliver tailored experiences at scale, surpassing basic email segmentation. Monocle’s AI takes this a step further by applying these models to inform incentive decisions on an individual level. This means merchants are able to personalize offers and discounts  with greater precision and efficiency than with a traditional A/B test.

By analyzing real-time behaviors and preferences, you can increase conversion rates by up to 20% and average order value by 25%. Beyond immediate sales, AI-driven 1:1 personalization strengthens customer loyalty, boosting retention rates by 30% and lifetime value by 40%. Through smart promotions and continuous learning, AI enables brands to adapt to evolving customer needs, driving incremental profit and sustainable growth.

Ready to see how AI-powered personalization can transform your ecommerce strategy? Get in touch with Monocle to start the conversation.