How to optimize the chats per agent metric

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Chat volume is the total number of chat requests that are initiated in a particular time frame. This live chat metric by itself doesn't give you much to work with and needs to be analyzed in combination with other chat metrics. For example, if your chat volume is a lot higher than your team's capacity, you'll need to set up a chatbot to lend a helping hand. If a lot of these incoming chat requests are focused on a particular set of topics, you could create a live chat knowledge base that customers can refer to before reaching out. If you regularly get a substantial amount of traffic from a page and there's a sudden dip, it could indicate a page loading error or that your chat widget isn't working. Peak hours Peak hours signify specific time periods during which the chat volume is significantly higher than usual. Looking at past data and identifying your daily, weekly, monthly, or seasonal peak hours can help you allocate resources effectively so that a higher number of agents are available during these times to handle the chat influx.


Tags Chat tags are labels assigned to chat conversations to Bulgaria Phone Number List categorize them for later reference. If a significant percentage of your chat volume falls under a specific tag—that is, they're about a particular topic—all you have to do to take some load off your team is either provide that information upfront on your website or create a live chat knowledge base. In addition, you could also deploy a knowledge base chatbot that can assist customers with frequently asked questions. Chat tags also help you with agent training and resource optimization. If a lot of customers need help with a particular product/module, it signals the need to train your team in that area. You can also assign agents with the most expertise in these topics to specialized departments identified through chat tags, allow agents to select the topic before a chat, and route them to the corresponding department for swift assistance.




Chats per agent This chat metric measures the average number of chat conversations handled by each support agent within a specified period. It helps you assess agent productivity, workload management, and the overall operational efficiency of your live chat support. Live chat metrics- Chats per agent Determining the optimal number of chats per agent depends on several factors like the complexity of inquiries, agent experience and efficiency, available resources, and customer expectations. Monitoring other live chat KPIs like average handling time, first contact resolution rate (FCR), and customer satisfaction (CSAT) scores alongside chats per agent can help determine if agents are managing an optimal workload. A high number of chats per agent along with an unsatisfactory FCR and CSAT score may indicate a heavy workload that could lead to burnout or a compromise in support quality, while a low number could suggest underutilization of agents. How to optimize the chats per agent metric