Net Promoter Score (NPS) is a leading indicator of growth for your business. Collecting NPS surveys is a great way to gather information about your customer’s user experience, satisfaction, and brand loyalty.
The average response rate of NPS surveys ranges from 30% – 50%. This means for the large majority of your customer base, there will not be a NPS. Thus, making it a challenge to understand how to tailor updates for your business.
Use Machine Learning to learn customer behaviors and predict the NPS score for the other 50 – 70% of users who have not responded. Vidora’s Cortex makes it easy to build a predictive ML pipeline and helps you gather a more representative picture of 100% of your customer base.
Watch a quick demo below on how to build a predictive NPS pipeline in Cortex.
Want to learn more about building predictive Machine Learning Pipelines in Cortex? Email us at email@example.com or fill out the form below.