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AI Case Study

Northstar Location Services decreases customer call escalation by 54% and handle time by 35% implementing Castel Detect to monitor emotional thresholds during customer service calls

Northstar Location Services uses Castel Detect to monitor customer services debt collection calls while in-process and monitors for emotional signals which automatically trigger legal compliance alerts for the customer service representative at certain thresholds. This has resulted in a 54% decrease in escalated customer calls and 35% decrease in call handle time.


Professional Services

Professional Services Other

Project Overview

"The team identified areas in which they could eliminate non-compliance risks through Castel Detect’s easy-to-use monitoring system shown right on agent screens. For example, the team determined agents could self-monitor their calls by visibly seeing when the call was broaching/exceeding business thresholds. By viewing emotion levels for both sides of the call, agents were able to better respond to customer’s feelings and statements while also managing their own. In doing so, agents were able to recite necessary disclosures and legal statements to customers in a suitable process allowing such important information to be relayed without talkover (customer and agent speaking at same time), or emotional discourse. Once a predetermined threshold associated with a business risk was detected, a visible and audible alert was generated and sent to the appropriate trained employee."

Reported Results

Northstar Location Services claim the following:

* 54% decrease in escalated customer calls
* 63% decrease in customer complaint letters
* 35% decrease in call handle time




General Operations


"Northstar Location Services is a full service receivables management company utilized by major financial firm... its offerings include first and third-party collections, customer
service and skip tracing. To improve operational excellence and enhance customer experience, the compliance group within Northstar determined the company could increase efficiency and customer satisfaction through identifying key issues during live customer/agent conversations."




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