This video series shows how data science can be applied to net promoter scoring to help you gain a much deeper understanding of the factors driving your customer recommendation ratings and how you can take action to influence them influence them.
Jarlath provides a brief history of the concept of net promoter score before introducing the case study whereby Predictive Promoter was applied to data from the guests of a major hotel chain.
Predictive promoter part 1 – introducing predictive promoter scoring Read More »
In this video Jarlath shows how to automatically produce a model that predicts customer’s recommendation scores based upon transactional and operational data.
Predictive promoter part 2 – building a net promoter score predictive model Read More »
In this video Jarlath shows how easy it is to take a previously built model that has been generated based on known outcomes and apply it to customer data where the outcome is not known.
Predictive promoter part 3 – scoring with a net promoter score model Read More »
In this final part of our predictive promoter video series, Jarlath Quinn tackles the project’s most ambitious task: mining the open-ended guest comments to uncover important insights. Here you can discover how we can use text analytics to extract a series of concepts and sentiments from customer comments in order to categorise the guests’ responses.
Predictive promoter part 4 – text mining and conclusions Read More »
