Clickstream Process Analysis

Process Driven AI for Clickstreams with websites or app's are beneficial for companies looking to improve their customer experiences and introduce new features, products or services. 

In clickstream process analysis can be used to predict where the customers are more likely to click next, given their previously followed patterns. This insight can be used to 

• Create data-driven customer personas, influenced by their behavior.

• Determine the most frequent product journeys of customers on our website or app in a very data-driven manner

• Predict the next actions of our customers/ users based on their previous activities

• major pain points such as a long delay between app installation and user engagement in podcast apps,

• processes that can be made more efficient such as optimizing checkout experience within shopping apps,

• events that get triggered more often than not, such as app uninstall immediately following podcast download events

For example, a digital startup deployed process driven AI from Perceptif to analyze mobile and website usage behavior in online shopping. Perceptif enabled the company to design process driven AI models to detect clickstream interactions and customer segmentation, measure KPIs, and analyse customer behaviour based on these customer segments. The firm identified the key patterns in these customer segments to make process-driven marketing campaigns.

In another example,  a global sales company, deployed process driven AI to understand why they were losing customers. The analysts found that website processes were one of the major factors leading to high customer churn. Therefore, the advice was to improve website processes by streamlining home-page user interface.

There are many other examples of benefits using process driven AI for marketing process analytics & optimisation.