This video introduces Smart Vision’s Predictive Promoter solution and 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. The hotel chain’s management team wanted to address three key questions:
- Understand what transactional and operational factors are most strongly related to the score
- Estimate whether other hotel guests are ‘Promoters’ or ‘Detractors’, even if they haven’t been asked to provide a score, and use these estimates to target high-spending ‘Passives’ for a special offer
- Uncover patterns in customer comments/verbatim text that help to predict the guests’ recommendation scores