Experience the New NPS AI
Editor's note: Success Drivers and Codit.co held a webinar on how AI can improve NPS survey on Oct. 18, 2018. Duration 57:46.
How AI reveals the hidden loyalty drivers in your text feedback
- Turn a simple 2-question NPS survey into an insights goldmine.
- Analyze text responses faster, cheaper, and more efficiently
- Employ AI to reveal hidden insights and avoid costly mistakes, which can produce misleading results when using traditional analyses
In this webinar, we’ll present powerful solutions to address these challenges and answer the following questions:
- Is it possible to automate manual coding and achieve equivalent or higher validity?
- How can we understand what truly drives loyalty – simply reported in a standardized way?
- Can this framework be applied to other programs (e.g., brand tracking or product concept testing) that would also benefit from an AI approach to coding and modeling?
NPS studies typically use open-ended questions to provide deeper understanding of the underlying reasons for customer loyalty. Using open-ended feedback comes with two significant challenges. It’s expensive to manually code and quantify text feedback. And second, companies typically assume the topics with the most mentions have the largest impact on loyalty – not always the case.
We’ll showcase a solution that has been tested with many brands including Sonos. We’ll illustrate how AI coding of open-ended responses with codit.co does in fact generate predictive power that surpasses even the most elaborate customer surveys. And, you’ll learn how the NPS.AI approach has the power to elevate your CX programs to another level with continuous, automatic evaluation of key drivers that enables companies to take immediate action on emerging trends.
Presenters: