Personalization in eCommerce: Beyond Demographics 

Demographics is often considered the go-to statistics for targeting and segmenting specific audiences. Age, gender, education, work, and financial status are the key starting points for segment profiling. But there is a fundamental problem with this approach — it makes a number of assumptions that don’t really provide any real insight into the actual buyer behavior. 

The fact is, misjudging customer needs can contribute to 42% of business failures.

It is foolish to place customer preferences in boxes and assume that they all want the same thing. The generalizing nature of this approach doesn’t make any valuable contribution to personalizing customer experience. 

Why Demographic-based Personalization Unable to Give a True Personalized Experience 

• Oversimplification: Grouping customers based on demographics overlooks individual preferences, leading to generic and often irrelevant recommendations.
• Missed Opportunities: Businesses miss out on micro-moments when a customer’s behavior deviates from typical demographic assumptions.
• Customer Alienation: Irrelevant or stereotypical targeting can alienate customers who don’t identify with the assumptions made.

The question now is, what should we do if we do not assume a customer base? 

A Better Approach to eCommerce Personalization: Psychographic Profiling

To better understand the customers and their preferences, eCommerce brands need to start supplementing their personalization strategies with data based on their customer’s motivations, rather than demographics. 

After all, knowing why customers visit your site is more important than their gender and where they live. A study by Dynamic Yield reveals that intent-based personalization can increase click-through rates by up to 20-30% compared to non-personalized experiences.

Furthermore, demographics lead you to continually update the personas requiring you to adjust as the customer’s life and stages evolve. 

On the other hand, psychographic profiling provides a more holistic, individualized understanding of the consumer, moving beyond traditional, broad demographic segmentation. It allows eCommerce brands to create personalized, meaningful experiences closely aligned with customers’ needs, desires, and behaviors. It enables brands to connect with customers on a deeper level, driving long-term loyalty and higher conversion rates. 

Psychographic profiling is the key to enhancing modern personalization strategies such as behavioral, collaborative, or predictive personalization. It helps in understanding the deeper “why” behind a customer’s behavior, mixing it with real-time data and predictive models to personalize the customer experience dynamically. 

Modern Personalization Strategies 

Behavioral Personalization

This approach helps tailor experiences based on a customer’s actions, such as clicks, searches, and purchase history. This approach ensures that recommendations are timely and contextually relevant, making the shopping journey smoother and more engaging. 

How it works? Machine learning algorithms analyze patterns in customer behavior to deliver relevant recommendations. For example, a user frequently browses fitness gear. The system will analyze this and suggest workout shoes or resistance bands to the user browsing fitness gear. 

Collaborative Filtering

This approach suggests products based on shared preferences among users with similar behavior patterns. It introduces products to customers they might not have discovered independently. 

How it works? Algorithms evaluate similarities in customer activity — such as purchase history and browsing patterns — providing recommendations like “people who bought this also purchased” or “you may also like”. 

Real-Time Personalization 

This approach adapts to the experiences as the customer interacts with the website or the app. This helps keep the experience relevant, catering to the shifting preferences during the same session. 

How it works? AI-driven tools help monitor live customer behavior and interaction with the website and refine the displayed content according to it. For example, if a customer switches from browsing for casual shoes to formal shows, the site immediately updates the recommendation, often leading to a purchase. 

Predictive Personalization

As the name suggests, it predicts what customers might need or prefer based on their historical and behavioral data. This proactive approach enhances convenience, often leading to a quick purchase. 

How it works? This approach identifies trends and patterns, offering suggestions often through emails or social media sites before the customer explicitly browses for them. For example, a website suggests a subscription box for skincare products after multiple beauty-related purchases. 

Putting Psychographic Profiling to Work: Tools and Applications

For e-commerce brands to fully leverage psychographic profiling, the right tools and applications are essential:

• AI-Driven Recommendation Engines: Tools like Dynamic Yield or Salesforce Einstein use psychographic data to generate precise, customer-centric recommendations.
• Customer Feedback Tools: Platforms like Qualtrics and SurveyMonkey gather insights about preferences, attitudes, and motivations.
• Data Analytics Platforms: Google Analytics and Segment provide deeper insights into customer behavior, integrating psychographic data into actionable metrics.
• CRM Integration: Syncing psychographic profiles with CRM systems like HubSpot or Zoho enables brands to create personalized customer journeys at scale.

Netflix is the biggest example of a company leveraging psychographic and behavioral data for personalization. The platform uses sophisticated algorithms to analyze viewing habits, preferences, and interactions. 

So, Are Demographics Really Dead? 

Demographic-based personas aren’t dead, they’re just primitive. 

If you are completely new to the market, collecting the basic data should be your first step in personalization. However, to get deep into the whys of the customer, you must understand their motivation and intent to get truly personal. But make sure to avoid the creepiness factor. 

Businesses must remember one thing: it is not about who the customer is — it’s about understanding who they aspire to be.