When was the last time that your customers visited the banks? Customers have become tech-savvy with the onset of AI technology. AI has changed the face of technology and it has become a new friend that customers find easy to deal with. And why not? It gives a quick solution to all the problems.
What AI does to solve customer service problems?
- Speech synthesis and recognition is available now
- Processing a large amount of data to draw meaningful insights is easy now
- It has become easy to interpret customer’s emotions and fetch the intent
“Why do you want to use certain technologies?” asks Sachin Bhatia, at ET BFSI CXO Conclave, Mumbai.
He has mentioned the importance of ‘Whys’ while prevalently ticking the clock against these questions:
A large amount of data churned to nudge, push, and force the customers when they like is what AI does to increase the coverage. Typically, a customer who works 9-5 does not want to be disturbed at 11 AM and a message alert could be sent at 6.30 to ensure that more calls are answered is what the intelligence is.
An agent dealing with 100 customers a day could easily miss out on small details and thus an increase in average handling time (AHT). With emotion detection and auto display of customer information, agents would be able to preserve the context. Relevant content like Knowledge Base helps them solve queries faster.
Automation on Customer Engagement
When customers are routed to the right queue and are connected with the agent possessing the best skills, you can easily find an increase in CSAT score in less time. Chatbots answering basic queries gives agents space and time to put the effort in critical cases.
Enablement of the Agent
Now, if the agents are struggling to find customer’s information, you are losing the customers to your competitors. Agents should see the information in one interface without having the need to ask repetitive questions and scouting for information.
Automation of Ticket Transfer
When the customer has raised a ticket, the real game starts. The tickets should be transferred to the right department without any delay, thus ensuring that the SLAs are met and customers are not escalating. In a typical customer-centric environment, it is necessary to keep their emotions at priority from the moment the ticket has been raised.
What is Ameyo’s Recent Innovation in the field of AI?
- Best Time to Call: For high connect rates, it is significantly important to analyze customer data and predict call around time. Automation tools detect that a person will typically answer the call between 1-2PM on the basis of historical data.
- Speech-to-text: With speech to text algorithm, we can easily fetch out the post-call summary, call sentiment and call score with up to 80% statistical significance and 100% coverage.
- Sentiment and Emotions Analysis: Empowering agents with sentiment analysis like positive or negative feedback along with their emotions of the last call that varies between Happy, Sad, and Angry equips them with the right information to handle the best call with the same customer.
Start with ‘Why’ and ‘What’ & ‘How’ will eventually fit in. What it is that you would want to solve for your customers should be led by why it is important to be solved. With AI reigning in, the customer service department has more tools to excel at CX game. So, what are the questions that you would want to ask before choosing a technology?