10 Ways Speech Analytics can improve Customer Experience to derive business outcomes
Using Speech Analytics for enhancing one’s understanding of customer service and experience: To be direct, call center analytics can be transformative for the knowledge of customers’ experience for many. The interactions one has with their customers are the insightful training they can receive for their business. These calls are precious; they can be analyzed to find phrases, sentiment, emotions, and keywords. The mood of every exchange will be evident as soon as one hears the conversation between their customer and agent. The role of speech analytics stands out because it can help gather a good volume of helpful information, and it is objective.
Building a platform for cross-selling: Speech analytics can help create an excellent customer experience by fixing issues customers were facing with the help of the information gathered. New customer experience strategies can be developed with the use of such information. With satisfied customers, one can create an efficient cross-selling platform.
Setting new standards and taking a new approach to agent coaching: using automated call scoring, the gaps in communication with customers can be easily picked up, even those missed by the management. Speech analytics can help to set up score cards easily and quickly. Setting new standards generally means that they will be kept in mind. Speech analytics becomes a powerful way of training agents because it scores neutrally and objectively, an AI judges them. Hence, there is no scope for complaints of bias in the scoring method either. The scale of data is also essential. Aggregate conversational data can be used successfully to educate and train agents.
In sales: Selling something depends a lot on convincing and even cajoling. Thus, the key to making it in sales is to ensure that the communication with the customer is stable and satisfactory. These interactions are crucial to gaining the loyalty of the customers.
Using AI to Predict NPS, CES, and C-SAT scores: Interaction analytics can help identify the reasons behind familiar sources of satisfaction and make corresponding changes to better customer experience. AI is also used to predict Customers Effort Score (CES), Customer Satisfaction (C-SAT), and Net Promoter Score (NPS)- this means that customers’ reactions to the actions of the agents can also be predicted with this data.
Identifying customers who are dissatisfied and convincing them to stay: Speech analytics can get to the root of why customers may be at risk of churning and help agents handle the situation. With the help of such data, organizations can train agents to deal effectively with churning customers and retain them.
Omnichannel view: It can help gain knowledge about the complete picture of the customer journey. Analyzing every customer’s experience across all channels can be very helpful, and the leaders can guide the agents correctly based on this information.
Combining all kinds of feedback to get the complete picture: by analyzing all of the calls, one can combine both the solicited and the unsolicited feedback given by the customers. This insight will contain both the Voice of the Employee (VOE) and the Voice of the Customer (VOC) as well. It’s invaluable.
Demonstrate empathy: Training of agents to turn negative emotions into positive ones can also be achieved via speech analytics and the information thus gathered because we can predict what phrases, sentiments, keywords will lead to a customer being upset, so we can hope to stop it before it happens.
Listening: It is essential that listening is a part of one’s brand value. Most customers report that they have unpleasant or unproductive experiences with call center interactions. This can be changed by using AI to analyze all conversations and arriving at patterns.