User behavior analytics (UBA) refers to the practice of using data to understand consumer behavior in order to develop effective campaign strategies. By gaining insights into what users are searching for, why they are interested, how and when to engage with them etc., brands can increase their chances of converting prospects into customers.
Analyzing consumer behavioral data provides valuable information about audience segments and preferences. This knowledge can be used to personalize customer experiences, offer proactive support, and optimize ad campaigns and sales events for better results.
What is behavior analytics
Behavior analytics is a business intelligence concept that involves monitoring and analyzing customer behavior across various electronic channels such as websites, online stores, mobile apps, chats, emails, etc. Each interaction with a user through these channels provides valuable insights into their preferences, needs, and purchasing intent.
Behavioral analytics, a subset of digital analytics, aims to anticipate and monitor customer needs by understanding their stage in the customer journey, identifying the information or support they require, and anticipating any potential challenges they may encounter. While there are various insights and analytics methods available, behavioral data stands out as it is user-generated and highly predictive of their intentions.
Who needs behavior analytics
One of the advantages of behavior analytics is that it enables brands to make customer profiles accessible to everyone within the workgroup. While this benefits the entire organization, there are specific professionals who can derive the most value from it.
Marketing department
With access to analytics and predictive insights about user behavior, marketers can develop relevant and personalized customer interactions. This enables them to tailor marketing strategies, deliver targeted messaging, and provide customized experiences that resonate with individual users. By integrating behavior analytics with other customer data, such as transactional and demographic information, marketers can create comprehensive and multi-dimensional customer profiles.
Sales department
Behavior analytics fosters collaboration between marketing and sales teams, enabling them to develop a cohesive and successful strategy. Marketers leverage behavioral data to create impactful campaigns, while sales teams analyze the ROI and refine the sales funnel.
For instance, by tracking user habits and responses, the sales department can identify opportunities to upsell complementary products or cross-sell to potentially interested customers. This targeted approach is highly effective in increasing both the number and volume of sales.
Customer service department
Despite thorough preparation, it is possible to overlook certain aspects. Users who are not a good fit for your marketing campaigns may express their dissatisfaction online through social networks, chats, or emails. This feedback is valuable and can be promptly accessed by your customer service department. With the help of behavior analytics, the frontline support team can be equipped with the necessary knowledge and responses to address customer concerns effectively.
Which types of data to analyze?
Behavior analytics provides insights into how users engage and interact with digital channels, and user data can be categorized into three types:
- Recorded data. This refers to data that is stored in CRM systems or marketing tools. It includes information such as user profiles, purchase history, and engagement metrics.
- Observed data. This category comprises a summary of user interactions, including their interactions with different elements of a website or app. It captures data such as click-through rates, session duration, and navigation patterns. Observed data helps identify user behavior patterns and optimize the user experience.
- Customer opinions. This type of data encompasses information about customers’ feelings and their active or reactive methods of expressing them online. It includes feedback, reviews, comments on social media, and other forms of user-generated content. Customer opinions provide valuable insights into user satisfaction, preferences, and areas for improvement.
Classical insights
Analyzing user behavior is a common practice, and there have been numerous developments in this field. While the relevance of these developments may be subject to debate, it is important to acknowledge them. Here are some examples:
- Focus area. The upper left corner of a webpage is typically the first area that visitors tend to focus on. Consider the information placed in this specific area of your website and evaluate its usefulness to the visitor. While there may be exceptions to this general rule, it is still advisable to take this information into account when designing your website.
- Attention zones. You can also divide the webpage into four equal parts, with the top left corner being the high attention zone and the bottom right corner being the low attention zone. It is recommended to place buttons and recommendations for further actions in the fourth so-called “end” zone. This is the area where visitors have already viewed the content, become familiar with it, and are ready to take further action.
- Eye movement pattern. When reading, the pattern of eye movement often resembles the shape of the letter F. The majority of users tend to scan the content diagonally. Eye-tracking studies have revealed that visitors typically focus on two horizontal lines before their gaze moves vertically, resembling the shape of the letter F. Considering this pattern, it is advisable to position the website menu in the top bar of the page. This placement ensures that it falls within the initial gaze trajectory of visitors, increasing the likelihood of them engaging with the menu and navigating the site more effectively.
- No need for scrolling. It is recommended to ensure that the main information of a webpage is visible within the initial screen without the need for scrolling. Consider that some users may choose not to scroll down due to various reasons, such as laziness or the perception that it is unnecessary.
Conclusion
User behavior analytics is a valuable tool for businesses as it enables them to attract, comprehend, and retain users while driving growth. By gaining insights into the underlying reasons behind user behaviors, brands can develop a comprehensive understanding of their customers. This understanding, in turn, allows them to identify multiple entry points across various digital channels and optimize the customer journey accordingly. Ultimately, leveraging behavior analytics can contribute to the overall success and expansion of a business.
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