Optimize your customer service with Machine Learning!
Customer Service has two clear objectives:
- Reduce the costs of operations.
- Improve the customer experience and increase customer satisfaction
The traditional operation of customer service centres has become obsolete with the incorporation of artificial intelligence. Thus, through mechanisms such as Machine Learning (more information here) it is possible to execute a service optimization and obtain advantageous functionalities and business forecasts.
What can Machine Learning do?
First, automate tasks. Many tedious or routine manual tasks can be replaced by automation.
- For example, the sorting of incoming requests.
- The intelligent routing of agents. That is, directing the request to the most appropriate or qualified agent based on past cases and other factors.
- Automatic case assignment. Call centers have supervisors who assign cases. With Machine Learning this task can be done automatically based on previous experience.
- Automatic data capture. After each interaction, agents must collect and fill in all case information. With the natural language processing they will save that time.
- Also, automatic response to emails. Using text analytics, Machine Learning can know the customer's question and respond with a mapped email template.
On the other hand, it benefits the agent's orientation and productivity.
- Through suggestions of similar cases obtained with text analytics. In this way, the agents will have help to solve a case knowing the procedure followed in previous cases. Machine Learning is able to determine semantic similarities between the current doubt and other cases and thus suggest a solution.
- Microsoft Knowledge Base article suggestions. Also useful for resolving issues based on similar content.
- It also offers suggestions for the best "next steps". That is, it compares the current situation with how a similar issue was addressed in the past.
Another benefit is the reduction in customer effort.
- Self-detection of the client's intention. Machine Learning can help find similar paths. Thus, the client's intention can be predicted.
- Proactive notifications to build customer loyalty Also based on your track record.
- Customer's preferred channel suggestion.
- And suggestion of the client's preferred time.
And finally, it is worth mentioning the KPI prediction that offers an advantage when it comes to solving cases and knowing the client's feelings.