10 ways Speech Analytics can improve customer experience to drive business results
- Using Speech Analytics to improve understanding of customer service and experience: To be blunt, call center analytics can be transformative for customer experience insights 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, sentiments, emotions and keywords. The mood of each exchange will be evident as soon as you hear the conversation between the customer and the agent. The role of speech analysis stands out because it can help gather a good amount of useful information and it is objective.
- Building a cross-selling platform: Voice analytics can help create a great customer experience by solving problems that customers were facing using the information gathered. New customer experience strategies can be developed with the use of this information. With satisfied customers, an effective cross-selling platform can be created.
- Setting New Standards and Taking a New Approach to Agent Coaching: with automated call scoring, gaps in customer communication can be easily detected, even those missed by management. Speech analysis can help set up scorecards easily and quickly. Setting new standards usually means that they will be kept in mind. Speech analysis becomes a powerful way to train agents because it neutrally and objectively scores, an AI judges them. Therefore, there is also no room for complaints of bias in the scoring method. The scale of the data is also essential. Aggregated conversational data can be successfully used to educate and train agents.
- On sale: Selling something depends a lot on convincing and even cajoling. Thus, the key to success in sales is to ensure that the communication with the customer is stable and satisfactory. These interactions are crucial to building customer loyalty.
- Using AI to predict NPS, CES, and C-SAT scores: Interaction analysis can help identify the reasons behind familiar sources of satisfaction and make corresponding changes for a 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 customer reactions to agent actions can also be predicted with these data.
- Identify dissatisfied customers and convince them to stay: Speech analytics can get to the root of why customers may be at risk of attrition and help agents manage the situation. With the help of this data, organizations can train agents to effectively manage rotating customers and retain them.
- Omnichannel view: This can help gain insights into the full picture of the customer journey. Analyzing each customer's experience across all channels can be very helpful, and leaders can properly guide agents based on this information.
- Combine all kinds of comments to get the full picture: by analyzing all calls, one can combine solicited and unsolicited feedback given by customers. This overview will contain both the voice of the employee (VOE) and the voice of the customer (VOC). It's priceless.
- Show empathy: Training agents to turn negative emotions into positive emotions can also be done through speech analysis and the information thus gathered, because we can predict which phrases, sentiments, keywords will lead to an upset customer, so we can hope to stop it before it happens. .
- Listen: It is essential that listening is part of the value of its brand. 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 arrive at patterns.
