Once the relevant data is collected and behavioral patterns are identified, the data is cleaned and transformed to ensure greater accuracy and consistency in its interpretation.
We then implement a predictive model to forecast future customer behavior, analyzing historical patterns to make accurate predictions.
And finally, we classify and segment the data to group them into different categories according to their behavioral patterns, allowing us to better understand customer needs.