Predicting Customer Satisfaction by Replicating the Survey Response Distribution

• URL: http://arxiv.org/abs/2411.12539v1
• Date: Tue, 19 Nov 2024 14:39:29 GMT
• Title: Predicting Customer Satisfaction by Replicating the Survey Response Distribution
• Authors: Etienne Manderscheid, Matthias Lee,
• Abstract summary: Call centers can benefit from a model predicting customer satisfaction on calls where the customer did not complete the survey. We introduce a method such that predicted CSAT (pCSAT) scores accurately replicate the distribution of survey CSAT responses for every call center.
• Score: 4.896237759904916
• License:
• Abstract: For many call centers, customer satisfaction (CSAT) is a key performance indicator (KPI). However, only a fraction of customers take the CSAT survey after the call, leading to a biased and inaccurate average CSAT value, and missed opportunities for coaching, follow-up, and rectification. Therefore, call centers can benefit from a model predicting customer satisfaction on calls where the customer did not complete the survey. Given that CSAT is a closely monitored KPI, it is critical to minimize any bias in the average predicted CSAT (pCSAT). In this paper, we introduce a method such that predicted CSAT (pCSAT) scores accurately replicate the distribution of survey CSAT responses for every call center with sufficient data in a live production environment. The method can be applied to many multiclass classification problems to improve the class balance and minimize its changes upon model updates.

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