Introduction
According to Deloitte’s article: “How Generative AI Will Change the Way We Do Customer Service” AI in customer support will grow with a CAGR of 24% until 2032. The total market for customer service will be $2.3 billion. This article gives a clear understanding which areas of customer service are interesting for AI.
Customer engagement
Customer engagement is the pre-service stage. With the help of generative artificial intelligence, analysis of customers can be done perfectly and faster. Plus it helps to generate better content for their customers. By better understanding their customers agents give better personal answers. This leads to a higher satisfaction score.
Service delivery
Service delivery is the in-serving stage. Companies should use advanced AI features such as call summarization and smart ticket routing. These tools ensure that customer support agents can do more in less time. Thereby, these features help to reduce the average time spend per customer. This will eventually lead to better and happier customers.
Customer retention and advocacy
Customer retention and advocacy is the certain post-serving stage. Identifying possible customer concerns before they contact customer support will boost the NPS. A possible way to achieve this is by using personalised tutorails. These tools help your customers to know your product better, resulting in a reduction of support tickets.
According to Deloitte there are four critical choices companies have to make.
What customer service opportunities do we prioritize?
The main question can be easily answered by asking the following questions:
Does the solution meet user needs (Desirability)?
What’s our ability to deliver the solution (Feasibility)?
Will the solution generate lasting business value (Viability)?
What platform will we choose?
There are multiple tools to help with generative artificial intelligence. As a company you should use the one that is most suited to your needs.
How are we going to develop our capabilities for customer service improvement? What Target Operating Model do we envision?
Customize the deployment of Generative AI to align with the specific requirements of the business. Evaluate its potential to enhance existing customer service procedures and workflows, and establish the essential competencies to maximize its benefits. This could mean providing training to the team, adjusting the organizational framework, or introducing new strategies.
How do we manage our risks?
Similar to any emerging technology, generative artificial intelligence presents risks. It is crucial to acknowledge and mitigate these risks by establishing robust safeguards. By implementing a thorough risk management strategy, it will eventually lead to happier customers.