Behavioral analytics reveals insight into how users act on online games, eCommerce platforms, websites, mobile applications, etc. Besides the usual ‘page views’ or monthly activity, this type of analytics shows how engagement with a product impacts revenue, conversion, retention, and the outcomes that interest you. Understanding this type of analytics is crucial in order to increase retention, engagement, and ultimately help your business prosper and increase revenue.
This type of analytics uses massive amounts of raw user event data which is captured during session in which users are active on a website, game, app, etc. This includes everything from traffic data, clicks, purchasing decision, social media interactions, and marketing responsiveness. The data is then complied and get analyzed, allowing for future trends and actions to be predicted. There are different types of behavioral analytics designed for specific purposes and specific platforms. For example, when ti comes to online gaming, it is important to predict user preferences in future release and trends. When it comes to retail and eCommerce platforms it is important to analyze product recommendations and predict future sales trends.
Ideally, a behavioral analytics solution includes real time capture of massive amounts of raw data across all platforms that were used during sessions, a visualization component, extensive library of analysis functions (for example, path, cohort, and funnel analysis), automatic aggregation of event data into relevant data sets, and the ability to query data into different ways.
User behavior analytics have at their core “events”, which represents the action the users perform when using your product (for example, watching a video, making a purchase, opening an app, etc.). You will need to understand the user’s challenges, insight into which features your customers are using and which ones they do not, and you also need to understand how customers get the most value out of your product.
First and foremost, you need to set up your analytics goals and be focused on improving in order to achieve it. For example, if you want to increase revenue, you will have to increase retention for paying customers, onboarding conversion, and checkout funnel conversion. You will also need to decide if you need cross-platform behavioral analytics, in case your product exists on multiple platforms (for example as a website and as an app). This will depend on the product and if you’re expecting users to behave in different ways on different platforms. If you are expecting behavior to be different then you will most likely want to know how each platform is performing independently, which means cross-platform analytics will not be a priority. You will also want to make sure that events are being tracked correctly, and in real time.
Instrumenting user behavior is an important part. Once all data is gathered you will need to put it to good use. You will have to view critical paths and also increase conversion with funnel reports, create behavioral cohorts, run experiments, calculate user retention over time, measure the impact of new features, etc.