03/20/2025 by Everton Gago, COO infinity6
#businessAI #infinity6 #AI #artificialintelligence #dataintelligence #datadriven
In today’s landscape, where personalization and artificial intelligence (AI) are critical for business success, understanding user behavior is essential. In the race to provide more convenience, efficiency and opportunities, three key dimensions shape behavioral modeling: characteristics, actions and time. Together, they enable precise recommendations and personalized experiences, driving value for both customers and companies. The impact goes beyond user satisfaction—it directly influences revenue growth, engagement, retention and brand strength.
1. Characteristics: Defining the Individual and Items
The first dimension encompasses user attributes and the features of the items they interact with. In e-commerce, this includes purchase history, brand or category preferences and product attributes such as price and popularity. In streaming services, favorite genres or preferred artists play a crucial role in content recommendations.
This combination allows AI systems to identify patterns and provide suggestions beyond the obvious. For example, a customer purchasing a smartphone may receive recommendations for complementary accessories like cases or chargers. This level of personalization not only increases average order value but also enhances brand perception by demonstrating an understanding of the customer’s needs.
2. Actions: What the Individual Does
The second dimension involves user actions, which reflect their interests and intentions. Browsing behavior, clicks, purchases and cart abandonment provide valuable insights into what a user is looking for. On content platforms, metrics such as time spent on an article or skipping a movie help refine recommendations in real-time.
In B2B, for instance, a pharmacy’s purchase history can indicate a need to recommend flu medicine during colder seasons, aligning with consumer demand. By proactively responding to these insights, businesses not only boost engagement but also strengthen customer loyalty by becoming trusted partners that understand their clients’ needs.
3. Time: When Behavior Occurs
The third dimension, time, is crucial for maintaining the relevance of recommendations. Recent behaviors carry more weight and AI systems must prioritize them. Additionally, factors like seasonality and consumption cycles influence purchasing decisions. In e-commerce, key periods such as Christmas or seasonal promotions require quick adjustments to highlight high-demand products.
In streaming services, timing also plays a role. Relaxing playlists at night or lighthearted movies on weekends are examples of how temporal context enhances user experience. Delivering recommendations at the right moment increases engagement and retention—critical factors for revenue growth.
Integrating the Three Dimensions
When combined, these three dimensions create highly personalized recommendations. In a B2B marketplace, for example, understanding customer characteristics (purchase patterns), actions (products bought) and time (replenishment cycles) enables businesses to suggest complementary products or seasonal offers. This approach not only boosts sales volume but also strengthens customer relationships by demonstrating a deep understanding of their business needs.
The Role of AI and Continuous Learning
AI plays a fundamental role in dynamically integrating these dimensions. Machine learning systems continuously refine recommendations based on user interactions, anticipating future needs. This capability allows businesses not only to meet expectations but also to surprise users with exploratory suggestions, such as niche content or products outside their usual preferences.
This continuous adaptation and innovation provide a competitive edge, enhancing customer loyalty and positioning the brand as a leader in personalization. Furthermore, by delivering unique experiences, businesses can increase customer lifetime value (LTV), driving long-term revenue growth.
