What is behavioral analytics?
Behavioral analytics is a subcategory of data analytics that looks at the way people behave, most often in regard to purchasing patterns. Behavior analytics tools are used to track users and the data they produce. Data can be gathered in a wide variety of ways, such as social media, online gaming, real time internet browsing, mobile applications, and even voice interaction with smart devices. A data analysis can then be performed to provide insights into ways of targeting these users.
A large volume of raw event data can be gathered any time a user interacts with a software system. This can track not only what they looked at, but also how long they looked at it, what interactions they had with it, and what they looked at immediately before and after. By tracking the customer journey, behavioral analytics can help predict future patterns or identify areas of concern. This type of data analysis is most often conducted as a cohort analysis. When conducting a cohort analysis, users are grouped together in ‘cohorts’ that share commonalities, such as a similar user journey or identifying characteristics like age. By performing a cohort analysis, companies can identify patterns across the life cycle of a user and make changes or recommendations as necessary as a way of increasing engagement.
Behavioral analysis can even be utilized to see how customers interact with different products. By looking at product analytics, businesses can see how effective, or ineffective, marketing strategies are. Then, companies can compare the product analytics to available behavioral data and make changes as necessary to help sell the product.
However, behavioral analytics is not just limited to the retail sector. Analytics solutions can help identify trends within political parties in order to determine how best to court new voters. These analytics can also help charity groups identify which leads from their websites are best worth following up on, and the order in which to do so.
This type of behavioral analysis allows for seemingly disparate data points to be woven together to create clear connections that can enhance the interaction between customer and company. While there are numerous benefits to behavioral analytics, some of the most impressive include:
- Increased customer engagement:By conducting a cohort analysis to learn about different cohorts and what most appeals to them, businesses can figure out how best to advertise new products and services to these different groups. By identifying what appeals to the customer, it is easier to identify the best way to interact with the customer to achieve the desired outcome, such as selling items or securing a vote for an upcoming election.
- Better business insights:The large amount of raw event data that is available for analysis can help identify trends in user engagement. This can the be used to address any gaps or areas of opportunity.
- Application development:By looking at the user journey through an application, companies can forecast future trends and design upgrades that will appeal to a large portion of the user base.
- Enhanced security: Behavioral analytics can help identify compromised information by noting activity that is suspiciously outside of the normal range. This can allow for near real time identification of security breaches and help identify where and how the breach occurred.