4 ways AI can vastly improve your behavior tracking process

In today's business climate, the ultimate goal for any brand is to get a complete and inclusive view of the customers who buy from them and the prospects they want to attract. Failure or success in achieving this simple objective often makes all the difference to a company's visibility and growth potential. Therefore, it is no longer enough for companies to collect personal information such as demographic and geographic data. Companies need to start with behavioral tracking, a process that uses user behavior data to get a complete picture of customers and what influences each individual's purchasing decisions.


Gedragstracking is het proces van het verzamelen, verwerken en analyseren van gegevens over het surfgedrag van klanten en interacties met websites, apps, emails en pagina’s op sociale media. Dit omvat gegevens zoals bekeken pagina’s, tijd besteed per pagina of browser sessie, gekochte items, aangeklikte e-mail links, enz. Daarom gaat deze techniek verder dan het kennen van de leeftijd en het netto-inkomen van een klant om te begrijpen waarom ze winkelwagentjes verlaten of veel tijd besteden op specifieke productpagina’s. Gebruikersgedrag kan worden gevolgd met behulp van methoden zoals cookies, tracking pixels en logbestanden. Vervolgens worden gegevens die met behulp van een van deze methoden zijn verzameld, geanalyseerd om inzichten te verschaffen om het bedrijf vooruit te helpen.

The insights generated by behavioral tracking can be used in many ways to mutually benefit the company and customers. All of these benefits come from the enhanced customer understanding that follows user behavior monitoring. This allows companies to better tailor and personalize their communication with all customers. This strengthens a brand's ability to retain its customers for the long term, leading to higher lifetime value and revenue. Tracking user behavior also provides companies with valuable information for improving products and services. For example, it can reveal pain points that cause browsers to leave your website. Acting on such information will serve as a driver to increase conversions and sales. The benefits are almost limitless, proving that this technique should be part of any company's marketing and advertising strategy.


It's almost impossible to do these days AI to circumvent. The robust capabilities of artificial intelligence (AI) and machine learning (ML) extend to behavioral tracking, and companies can leverage the power of these technologies to improve the efficiency of their tracking.

Here are four proven ways AI can help your business better track user behavior and extract more value from the process:


One reason for AI's ability to vastly improve behavior tracking is the presence of the automated analytics feature. Automated analytics tools can automate data collection by pulling data from a variety of sources, reducing the need and risk of manual data entry. It can also process large amounts of data faster and more accurately than the capabilities of traditional systems. In addition, AI can automatically segment customers based on their behavior patterns, making it easier to personalize messages and services. For example, AI can segment all customers who spent several minutes on a particular product page without proceeding to checkout. Companies can then respond by creating drip marketing campaigns to convince the customers in this segment to buy the product.


Insights are more valuable when they prompt immediate action. An important contribution of AI to behavioral tracking is that it provides real-time insights when customers perform specific actions or inactions, enabling companies to trigger instant responses that increase the likelihood of achieving the desired outcome. For example, AI can perform a real-time analysis of a customer's browsing behavior using machine learning algorithms and make product recommendations based on the insights generated. Similarly, AI-powered chatbots can be programmed to initiate online or email reminders for customers who abandon shopping carts. Using real-time analysis and quick actions, AI can make it easy to optimize behavioral targeting and provide satisfying service to customers.


According to McKinsey, predictive analytics can marketing reduce costs by up to 30%, while increasing the effectiveness of marketing campaigns by approximately 20%. Predictive analytics is a valuable AI functionality that can improve behavioral tracking for businesses. AI can make accurate predictions about customers by analyzing customer data and using techniques such as statistical analysis, machine learning and neural networks. So, by combining behavioral targeting and predictive analytics, companies can take actions that solve current problems and then anticipate future customer needs.

This is especially useful for recommendations, so that products and content that may interest customers can be accurately predicted. It can also be useful for inventory management by using behavioral data to predict products that are likely to be in high demand in the coming weeks. For example, if multiple customers keep searching for a particular item of clothing on your catalog page, AI can use this as an indicator to alert your inventory managers to stock up on that product and even send emails with discount offers to interested customers.


AI has the power to identify patterns in customer behavior that are difficult for humans to spot. Training AI to recognize patterns in data can yield rich insights from behavioral data. In addition to providing personalized recommendations, pattern recognition is helpful in detecting irregularities in customer behavior. For example, a company may notice a sudden spike in website traffic. In that case, image recognition can be used to analyze website heatmaps to identify the specific pages that attract the most attention. Similarly, pattern recognition can be reasons for customer churn or abandonment shopping carts identify. This AI capability puts businesses in a great position to quickly identify issues and take action to address them.

In short, the behavior tracking is a strategy that can be very useful for companies that approach it in the right way. AI has several innovative techniques that can be used to make user behavior tracking easy and convenient. As a downstream effect, revenue will increase and customer engagement will reach an all-time high, making it a strategy worth investing in today.


As Google, Facebook, Amazon and Microsoft have been doing for years, it is important to also create 360-degree customer profiles. All available data that can be linked to a person is important to get a better picture of your (potential) customers. All data from behavioral tracking is important for these types of customer profiles. A CDP system is the best place to capture all data and create 360 garden customer profiles. In some CDP systems, extensive analysis functionality is also available. This makes it an “all in one” solution for demanding marketers.


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