A regional hotel chain client benefited from predictive content selection by adding more than 2,100 new site traffic visits daily.
A regional hotel chain client wanted to serve dynamic content to its web and mobile site visitors by using digital behaviour analytics.
Gathered structured, unstructured and semi-structured data into a datamart. Reserached all visitor ID based applicable factors that impacted bounce rate, A/B testing, and successful call to action behavior. Normalized and synthesized variables in a predictive model and connected the model to dynamic content database.
The project sponser was able to confirm 10% decrease in the bounce rate, 85% accuracy on chosen content with A/B confirmation and 5% increase in new site traffic (2100 new visitors on the average) traffic to prioritize more accurate content delivery in real time.
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