5 min
Today’s call center analytics can provide managers and supervisors with unprecedented insights into operations and identify whether they are delivering the experiences customers expect and value.
Artificial Intelligence (AI) can take standard contact center data and transform it into actionable insights on customer behavior, agent performance, and operational efficiency; key information that cannot be ignored in a modern call center.
In today’s “experience economy”, organizations need to maximize the value of contact center data and know the “why” behind the metrics. Ideal for analyzing massive amounts of data, AI is the right tool to help call centers identify where they should focus their attention and resources.
What Benefits Does AI Bring to a Contact Center?
Core call center applications can leverage Artificial Intelligence to make processes and experiences better, more consistent, and more accurate. AI can help anticipate and predict customer needs to provide them with the customization of services they crave. In addition to helping them save time by providing the information they need more quickly. Artificial Intelligence can even make self-service easier to use by allowing the customer to tell the IVR or chatbot what they want, rather than having to press the keyboard or say specific phrases.
Customers are not the only ones who benefit from AI: Artificial Intelligence can also improve the agent experience (AX), handling repetitive and routine transactions, freeing them up and allowing them to manage more complex and value-added interactions. It can also be used to train agents in real-time, on every call, to constantly improve their performance, skills, and customer experience (CX).
By using AI to deliver faster and easier experiences, more customers will use self-service more often, giving businesses a better return on investment (ROI). According to Gartner, interactions that require a live agent cost an average of $ 8 per contact, while self-service channels can cost as little as 10 cents per contact.
How is AI Transforming the Way Contact Centers Operate?
1) Controlling Customer Behavior
Customer behavior is constantly evolving. Preferences and perceptions change, budgets change, and previously loyal customers begin to show signs of turmoil. AI-powered engagement analytics can help call centers stay on top of what dynamic customer bases are thinking and feeling.
Interaction analysis tools can focus on keywords and phrases to identify potential problems. For example, if the phrase “payment could not be made” is suddenly used more frequently, that can alert the contact center that there may be a problem with the website’s payment functionality.
Leaders can then inform the web team about the problem and in turn provide special instructions to agents. Proactively addressing emerging issues reduces the number of affected customers and also enables organizations to avoid contact-related issues.
Additionally, analytics tools can inform agents about up-sell and cross-sell opportunities. When handled well, introducing customers to the products they want can enhance their experience.
Businesses can also use interaction analysis to determine customer sentiment. This AI-powered tool is capable of analyzing each interaction of each channel and identifying how customers are feeling. For voice interactions, the pitch and volume of the voice, the length of pauses, and whether agents and customers interrupt each other have to be analyzed, this helps to determine if a customer is frustrated, happy, angry, etc.
Because sentiment scores can be calculated at the individual customer level, supervisors can close the loop on dissatisfied customers by calling them and trying to get it right. An agent can also track sentiment scores to identify best results and development opportunities.
2) Facilitating Agent Assistance
In the process of analyzing the information provided by the call center analysis tools, leaders can determine if agents need additional support to adapt to changes in demand.
AI and bots provide continuous assistance during voice and digital interactions, turning each agent into a specialist with all the information they need at their hand.
No matter how good the self-service channels are, many customers will want the assistance of an agent. The telephone is still a very popular and widely used channel. AI can help optimize these voice interactions by providing agents with real-time information, workflows, and step-by-step guidance. This will help eliminate those long pauses when agents are searching for information.
Artificial Intelligence tools can guide agents on the best responses to provide, how to adjust behaviors to build a better relationship and improve the CSAT (satisfaction survey), and even remind them if they are speaking too fast. And all in real-time.
Significant Benefits of AI-enabled Guidance and Training
- Lower handling times.
- Higher first contact resolution rates.
- Better customer sentiment and satisfaction.
- Greater commitment and satisfaction of the agents.
- Improved customer experience.
How Do you Know if you Are Getting These Benefits?
Some of the data will come from standard operational reports, and the analytics tool can fill in the gaps by providing information on customer sentiment and the CX. Call center analytics software not only helps leaders identify improvement initiatives, it also helps measure the effectiveness of post-implementation improvements.
3) Identifying Operational Efficiency Opportunities Through AI Analytics
While reviewing analytical insights, leaders can also identify opportunities to create efficiencies by improving self-service and streamlining agent processes. How?
- Improving efficiency with virtual agents.
- Optimizing efficiency with a conversational IVR.
Call center analytics can provide the information leaders need to stay competitive in the experience economy. AI analysis highlights new issues, identifies product gaps, and provides insight into what customers think and feel. These capabilities can also highlight opportunities to provide agents with further assistance or enhance self-service solutions. And on the back end, analytics tools can indicate whether initiatives to improve CX, agent effectiveness, and operational efficiency are working.
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