AI-backed personalization tools can be game changers for your e-commerce brand. When helping our direct-to-consumer clients build win-win experiences (where both they and their customers win), my agency has used many tools that bring AI into the personalization equation. These tools promise tailored experiences that boost conversion rates (CVR) and customer lifetime value (LTV). However, they are only as effective as the data they’re fed, and that’s where the challenge lies.
Personalization Relies On Knowing Your Customers
To get personalization right, you have to understand your customers deeply. Think about how traditional salespeople thrive—they can see and respond to customer cues like facial expressions and specific questions. They are tuned in and they are strong listeners.
Digital personalization AI and supporting algorithms, however, don’t have that luxury. They rely on data, and unfortunately, we are feeding them an overabundance of digital fingerprint behavioral data (i.e., clicks, page views, email opens and purchase history).
The Limits Of Digital Behavioral Data
While it’s automatically collected and can help shape stronger e-commerce experiences, digital behavioral data has its limits. It tells you what a customer did but often misses the “why.” For instance, a customer might abandon their cart because the checkout process is too complex. However, the algorithm might just flag this as a lost sale without understanding the reason behind it.
Additionally, this data is pretty sparse at first, requiring several interactions (often over many months or years) before there’s enough information to make personalization meaningful. It’s like trying to piece together a puzzle with only a few pieces.
It’s not that this data isn’t useful, but it can’t be the foundation of your personalization efforts.
Building A Stronger Core
Digital behavioral data is valuable, but it’s not enough by itself. You need a stronger data foundation for meaningful personalization.
Here’s my advice:
• Research your target market and segments. You have to understand your target market and its different segments. If you haven’t already, identify at least three distinct segments, making sure each represents groups with different needs, preferences and problems. If instead you have 100 segments, whittle them down to three at first. This helps tailor experiences right from the start.
• Feed segments into your personalization setup. Once you have these segments, integrate them into your personalization tools. Make sure the content and paths supporting these segments create segment-driven experiences, and then you can enhance these experiences with behavioral data. This two-layer approach enriches your personalization engine, making it more effective. It’s almost like giving your algorithms a detailed road map instead of vague directions.
• Implement segment-specific learning. Go beyond general customer insights and focus on segment-specific trends. Study how different segments interact with your product catalog. For example, don’t just look at bundling trends across your entire customer base—break it down by segment. Feed this refined data back into your personalization tools to boost each customer’s lifetime value.
Personalization Is A Continuous Effort
You can’t just set and forget personalization. Even the best AI algorithms are limited by the quality and scope of the data they receive, and while software companies strive to maximize the value of digital behavioral data, it’s rarely enough to fully realize personalization’s potential.
To truly succeed, you must focus deeply on your customers and the tailored conversations you have with them. Continuously feed this nuanced, segment-specific data back into your personalization tools. This approach isn’t just the best way forward—it’s the starting point for significant impacts on CVR and LTV.
Invest In Your Customer Knowledge
AI-backed personalization tools hold incredible promise, but their effectiveness depends on the depth and breadth of how they understand the people they’re helping in your e-commerce ecosystem. You have to go beyond digital behavioral data by incorporating robust customer segmentation and continuous learning to drive meaningful personalization.
This multilayered approach enhances customer experiences and drives tangible business results, so invest in knowing your customers better and feeding that knowledge back into your systems. The results will speak for themselves.
This article originally appeared on Forbes.