Social Reputation: Is Your Call Center at Fault for Bad Reviews?

Research indicates that the majority of consumers read reviews when they make purchasing decisions. Consumers look for social proof that they are making the right decision. This is particularly the case in this internet age, where you can find online reviews for virtually any product or service imaginable, making your companys social reputation more important than ever.

The two biggest review sites are Google and Yelp. Google emphasizes online reviews, search for virtually any business name and you will see a Google reviews pane alongside the results. For many searches, Google brings up a list of three suggestions, complete with their average ratings, as a score out of five. Indications are that the majority of searchers opt for the search result with the highest rating.

Examining a Bad Social Reputation

Some businesses regularly receive bad ratings; often really bad ratings. Seeing reviews for your business like 1 star is a compliment to this inept, useless company can be a sole destroyer for business managers and owners, who try to grow their companies despite their social reputation.

The above review is a genuine comment given to a service company, who will remain anonymous. This is just one example of many loathsome reviews left visible for all to see online. As a result of, the company has a major task ahead of itself in improving their social reputation. They need to prove to potential clients that they are better than these bad reviews suggest.

Does this mean that the company provides poor service? Not necessarily. The employees who physically provide the service everyday may do a capable job. However, they are human, and there will be situations where the results are not perfect. Some customers will choose to complain to the call center, and it may be here that the real problem lies.

Using Predictive Voice Analytics to Combat a Bad Social Reputation

In many ways, working in a companys customer service call center must be the most challenging position for a call center employee. It is unlikely that you are dealing with clients who are emotionally neutral. In most industries, only 5-10% of dissatisfied customers choose to make a complaint. Therefore it is probable that those who go through with making a complaint are genuinely angry or upset.

Of course, it helps if you know the complainants emotional state. There should be clear processes in place of how to handle customers, depending on the emotions they are demonstrating.

Predictive voice analytics software helps with the challenge of properly identifying the customers emotional state. It ensures that customer service agents understand how the customers on the other end of the telephone truly feel. By analyzing the voice based emotions, predictive voice analytics tools give the phone agent a subjective queue for how to best handle the customer.

Often, its not what you say, but how you say it. This can be the case when a customer service agent tries to deal with a complaint made by a very angry customer. The customer may have a genuine gripe. However, their message could become lost in his anger, which can limit the abilityof the customer service agent to successfully resolve the problem. If the customer service agent fails to resolve the compliant, the customer is more likely to take their gripe to social media, thus leading to a bad social reputation.

Final Thoughts

A call center manager aims to bring about resolutions to complaints as quickly as possible, ideally with just one phone call. The alternative is that the firm is likely to receive many follow-up calls and terrible online reviews.

This is just one example where companies can use emotional analytics to provide customer insight, and ultimately enhancing the customer experience and their social reputation. Hopefully, the next review from a satisfied customer might read 5 stars  this company really gets customer service.

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