How SONOS Understands Drivers of NPS by Using AI: Better, faster, cheaper – Understanding of loyalty drivers by analyzing NPS’ open text responses with AI

Sonos, an US consumer electronics company, shapes its product development strategy by analysing open text responses, but wanted to categorise them into meaningful content strategies.

Introduction

Text data is an untapped goldmine: by using text categorizations, Al can predict NPS (Net Promoter Score) even better than with quantitative questionnaires. NLP analytics had been used for auto-coding with great precision. Results shaped Sonos' product development strategy.

NPS open text responses are an underleveraged asset. When text categorizations can predict NPS better than quantitative questions, this means that a simpler two item questionnaire can have more validity than a decent quantitative questionnaire. We learned that with help of NLP text analytics software, even manual coding of text data can be automated with expectable accuracy.

Overall this means...

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