Case Study: MonkeyLearn achieves automated NPS feedback analysis with Retently

How Retently Automated Customer Feedback Analysis Using MonkeyLearn

MonkeyLearn faced the challenge of turning large volumes of open‑ended NPS feedback into actionable, consistent insights: manual sorting was slow, error‑prone and lacked granularity. To address this, they worked with vendor Retently, using Retently’s NPS platform (and Zapier to connect systems) to collect and route customer responses into automated analysis.

Retently implemented an automated pipeline that sent NPS responses to MonkeyLearn for text analysis, trained a custom MonkeyLearn classifier on over 1,000 labeled replies, and applied a taxonomy of tags (Onboarding, Ease of Use, Product Features, etc.). Retently’s solution auto‑tagged responses and added a Response Tag Analysis dashboard, eliminating manual spreadsheets, delivering consistent 24/7 tagging, and producing measurable outcomes—frequency‑ranked themes across Promoters/Detractors and a clear signal that missing features were the primary driver for lower NPS.

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