Artificial Intelligence To Improve Customer Service Metrics. Customer service metrics can become the obsession of many companies. Although there are many ways to evaluate the service offered First Contact Resolution (FCR) or Average Handle Time (AHT) are two of the most valuable.
These indicators are related to the efficiency of the teams or the time taken to resolve queries, in short, very important aspects for customer satisfaction. According to a Forrester study, almost 70% of people feel that the best thing a company can do for them is to have adequate customer service and to be efficient in resolving incidents or doubts.
But, how is it possible to improve them? The key to this comes from upbeat and its artificial intelligence solutions. Thanks to the application of these technological developments, contact center agents see their customer service capabilities increased, offering a more agile service and problem resolution.
How to improve customer service metrics with AI
While technology is not the end-all and be-all of the contact center and its services, it is a vehicle for delivering improved customer service and is a helpful tool for agents. Thanks to upbe’s AI tools the time to resolve issues, as well as the average time required to do so, will be significantly reduced. What are the effects of technology on metrics?
A better understanding of emotions: today’s customers need a solution to their problems, as well as for the agent to understand the conflict involved in calling for a consultation. Thanks to conversational intelligence, the agent gets a better analysis of the customer’s feelings, makes the decision, and offers the most appropriate solution for each of them.
Reduction of repetitive tasks: the agent’s manual work is significantly reduced, making this the human value of the service. As a consequence, administrative procedures are reduced and more efficient analysis and resolution are obtained.
More agile agents: data analytics implemented thanks to artificial intelligence makes it possible to detect possible incidents more quickly and offer operational improvements. With this, it is possible to scale the agent’s knowledge, reducing resolution time.
Service customization: adapting to the context of each customer can be complicated. However, thanks to the information offered by artificial intelligence and the possible suggestion of solutions adapted to the customer, it allows a personalized service for each context.
Reduction of over-checking: one of the biggest problems of contact centers, and one that generates the greatest despair on the part of customers, is the repetition of information. Thanks to the recording of information, the agent has all the context of the query, reducing waiting times and offering faster solutions.
In short, Artificial Intelligence solutions will not only improve customer service metrics but will also be an advantage for offering a quality service to increase customer satisfaction.
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