Role of Big Data in User Behavior Identification
User behavior identification is the system of monitoring, tracking, collecting, and assessing user data to identify their behavior and traffic pattern. Big data is just an evolved term for large amounts of structured, unstructured, and semi-structured data that can be mined for important information. The voluminous data is analyzed and used to identify user behaviors at a much larger scale. Used by digital marketers and other companies to determine demands and necessities amongst the crowd, big data plays a crucial role in user behavior identification.
How is big data collected?
User behavior analytics collect various types of data including user activity, accounts, permissions, digital interactions, user roles, titles, security alerts, geographical locations, and more to determine user behavior. The extensive and varied data collected by capturing first-party cookies, randomly generated IDs for desktops, and an SDK for mobile users. Big data can come from various different source including results from scientific experiments, business sales records, or even the streaming data from different sensors. The collected data plays a critical role in understanding user behavior and determining their needs and requirements. Companies use the collected big data to determine the demand in the market so that they can provide products and services accordingly.
How big data helps user behavior identification?
- The E-commerce sector has been largely impacted and continues to use the application of big data to identify their user behavior. The collected data helps them analyses the users entire shopping experience through product impressions, viewing of product details, product clicks, an addition of products to the cart, initiating the checkout process, transactions, refunds, and such. The e-commerce giants can get a better visual over their products and services that are in-demand and the ones that are being ignored and rejected.
- Bigdata allows event tracking to determine accurate and enhanced user behavior. Event tracking basically means independently tracking user interaction through screen load or web-page loads. Generally, mobile apps use these event tracking techniques to analyze how much and what content is being shared, how are the app functions being used, and what type of content is gaining more attention. Events are also used to track file downloads, gadget interactions, and more.
- Big data is also used to keep track of the active users. Companies generally like to stay in touch with their customer’s activities and behaviors to ensure continued user interest. It allows companies to stay notified if the numbers are below expectations. As a result, they can reevaluate their marketing efforts and brainstorm new and effective strategies to target the appropriate audience. Companies can also keep a close track over any positive or negative press they might be getting online. They can look for the negative content and work on the issues to keep their customers happy and satisfied.
Apart from using the big data for marketing endeavors, it is also used to recognize security threats and anomalies. User behavior identification keeps a track on all abnormalities and restricts authentication if the behavior involves sensitive topic like personally identifiable information and such.
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