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TIBCO Spotfire's Business Intelligence Blog


Predictive Analytics to Detect and Mitigate ‘Customer Rage’

The number of households experiencing “customer rage” or outright anger at their experiences with various companies rose from 60% in 2011 to 68% this year.

shutterstock 489065981 150x150 Predictive Analytics to Detect and Mitigate ‘Customer Rage’Meanwhile, the number of people who yell at customer service reps has jumped from 25% to 36% over the same time period, according to a recent study.

The findings carry a number of implications for companies. Despite efforts by many firms to improve customer service, US consumers are less happy with purchases when they end up complaining to companies.

The fact is 56 million American households experienced at least one customer service-related problem during the past year, with roughly $76 billion in revenue at stake for the companies involved, the study notes.

In addition, when customers in the study felt a company didn’t handle their complaints well, their loyalties dropped 12% lower than if they hadn’t complained at all.

Business leaders who want to get at the root causes of customer rage can apply predictive analytics to different types of customer experiences – from phone-based contact center interactions with agents to product quality and sentiment that customers share about brands in social channels.

In most cases, if a customer has had a history of fairly consistent experiences with a company, he likely will have developed some level of trust in that brand. So if a customer has a history of purchasing or interacting with a company and he suddenly has one poor experience, he’s less likely to fly off the handle.

In some cases, customer anger is the result of a snowball effect.

A thorough analysis behind the triggers for customer churn with a leading pay TV provider led to some interesting revelations, according to a recent Harvard Business Review blog post.

Although the company is among the best in the industry at managing churn, it wanted to gain a deeper understanding as to whether improvements in customer experience could reduce churn and build competitive advantage.

What the company discovered was that its customers weren’t dissatisfied with any single call center interaction or home visits from technicians or email exchanges. What reduced customer satisfaction were customers’ cumulative experiences over multiple touchpoints over time.

Real-time analytics can help companies spot customer dissatisfaction as it occurs, enabling service agents and other customer-facing employees to take corrective action quickly.

Studies have shown that responding to customer complaints quickly and effectively can generate strong business outcomes.

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