Many businesses outsource their customer support needs to contact center solutions providers like ROI Solutions. These contact centers manage interactions throughout multiple communication channels ranging from phone calls to emails, live chat, and social media platforms.
With the growing importance of good customer service, providing good experiences in every interaction is a must. This is where contact center analytics come into play. Here we will learn more about what these analytics are and how they can impact your business.
What Is Contact Center Analytics?
Contact center analytics is the collective term for the tools and processes used to track and measure the contact center’s performance when handling customer interactions. They help the organization understand its services’ performance. For example, how quickly do they currently respond to inquiries? How effectively can employees resolve issues?
How Contact Center Analytics Impact Businesses
Companies can use the results from these analytics to determine which aspects of their operations still need work, thus improving their business as a whole. Besides gleaning data such as how long the average interaction takes, they can also learn other information like:
- How satisfied are customers with their overall experience?
- Did customers find the answers they wanted?
- What demographics do your inquiring customers belong in?
- What kind of problems did customers face with your products or services?
Getting the answers to questions like these can help businesses know, for instance, how to address a recurring problem with their products. In turn, this would increase their customer’s satisfaction with their purchases, which can boost sales. Another example is if they use their findings to develop better responses to inquiries or provide more employee training, which boosts satisfaction and grows their relationship with customers.
Difference Between Contact Center and Call Center Analytics
Call centers mainly focus on interacting with customers through voice calls. As such, the data gathered in call center analytics are more call-related. These include metrics or Key Performance Indicators (KPI) such as:
- Average call handling time
- Time put on hold
- Time waiting in the queue
- First call resolutions (issues that were resolved in one call and didn’t need repeats)
- Abandoned calls
These help the call center measure its effectiveness in handling calls and help find ways to improve the quality of each call interaction.
But since contact centers handle more communication channels than call centers, the data types and methods used to gather them vary far more than with call centers. For example, suppose a business lets customers contact them through social media. In that case, the contact center can use social media insights tools to study how they interact with customers on those platforms. If they use email, they can have an email response management system analyze the inquiries coming in.
Metrics Measured in Contact Center Analytics
Besides the metrics measured in call center analytics, contact centers can also gather these other metrics to understand how your business and customers fare during interactions:
Number of Customer Interactions
This measures the number of customer interactions on all channels and not just phone calls. It can include inquiries on the company’s website contact page, emails, chat, and so forth. The metric can also indicate which channels are more popular with customers.
This KPI refers to the degree of effort customers exert to get in touch with the business and have their inquiries addressed. For instance, they might’ve already tried contacting through several channels for hours before they were served on one. This KPI can also tell why customers may prefer one channel over another—or companies with multiple communication channels.
Complaint Type Volume
This metric indicates the different types of complaints the company receives in each channel. For example, social media channels may get more complaints about after-sales services, while email and chat channels receive product-related ones more often.
The visitor intent metric helps businesses learn why customers want to get in touch with them in the first place. Are they complaining about a product defect or subscription error? This metric also helps identify the most common issues customers face and the causes behind them.
Types of Contact Center Analytics Approaches
Depending on the types of channels a business utilizes, some of the methods used in contact center analytics include:
Speech or Voice Analytics
In speech analytics, the contact center gathers data by studying past recorded calls. For instance, they can use software that analyzes the customer and agent’s words and emotions in the customer’s tone of voice. It then determines the inquiry’s topic and whether the customer is more content or aggravated as the call goes on. This helps the company work on how to improve the customer’s experience during calls.
Similar to speech analytics, text analytics are used to collect information in past conversations. However, this time, the contact center is studying interactions in text format, such as those in live chats and emails.
Companies can use the data to, say, help them craft better responses to common inquiries or tweak the AI responder to provide effective solutions before it needs to direct to a live human contact agent.
Desktop analytics look into the contact center agent’s desktop computer and how they interact with customers. This helps them see if their current systems are working effectively. The contact center may monitor the agent’s activity on the computer to check on their productivity or any processes and software that hinder their ability to provide solutions to customers.
Self-service refers to tools like self-service online portals or chatbots that help reduce the customer’s need to connect with a live human agent. Self-service analytics is the study of the customer’s experiences while using a business’s self-service features. The analytics help determines whether the business can effectively address customer concerns on their own or if certain types of inquiries need a human agent’s intervention.
Predictive or Proactive Analytics
Contact centers use predictive analytics when studying all the data they’ve gathered in previous studies. They use past interactions and performance reviews to predict future customer interactions, anticipate problems, and proactively develop solutions for them.
For example, an organization can study the volume of interactions in previous years to determine which months will likely get the most inquiries next year. They can then assign more contact center agents to work in a specific period.
Omnichannel or Interaction Analytics
Omnichannel analytics method reviews all the information gathered from all the communication platforms. It involves studying which channels customers prefer the most and how they interact on each channel. This helps the company understand how to improve the customer’s experiences in each preferred platform.
Contact center analytics are vital to improving a customer’s experience and their relationship with your business, which is why a good contact center should know how to use these effectively.