Running a call center, or to be honest, any other business, is more about analyzing data and finding effective solutions than about anything else. Thus, call center analytics can become a powerful tool for driving your contact center forward and overcoming competition. Actionable insights provide call center managers with numerous options to reach set KPIs (Key Performance Indicators), monitor contact center performance in real time, improve phone calls processing, understand customer conversations and customer sentiment, reduce customer effort scores and streamline contact center operations.
Call center analytics work for internal and external processes, so you have to measure both customer experience and agent performance to find improvement areas and identify problems.
Let’s find out how call center analytics can be used for fast call center performance improvement and how can you get actionable insights.
What Is Call Center Analytics?
Call center analytics is a process of collecting, structuring and analyzing call center data regarding customer interactions, internal and external business processes, agent performance and experience, and other aspects of call center functioning. Contact center analytics software provides actionable insights, call volume trends and helps to reach business success.
Using call center analytics can provide you with all answers you have been looking for: why are customer dissatisfied? What are the reasons for customer churn? What stage of customer journey ruins customer-brand relationships? How can you improve sales?
Here is the list of benefits you can expect from proper use of call center analytics.
- Resolve common customer problems and increase customer satisfaction
- Segment customers and target audiences, create ideal customer personas
- Improve agent performance and satisfaction
- Build effective and healthy customer service teams that won’t suffer from high agent turnover
- Deal with inbound call volumes
- Provide effective quality assurance
- Boost your sales performance
- Improve employee engagement
How Does Call Center Analytics Work?
There are some popular call center analytics types.
- Speech analytics: This technique is used in IVR systems for understanding customer concerns without using legacy DTMF technology, yet it is not the only field where it is utilized. You can use speech analytics to track customer sentiment automatically, thus understanding customer experience.
- Text analytics: This technology works the same as speech recognition, but it analyzes text – messages in web chat, social media, etc. It can also understand customer sentiment, but also it can identify keywords and thus comprehend purpose of customer request.
- Interaction analytics: This technology is used to evaluate separate customer interactions and thus identify issues with agent performance or collect data about common customer inquiries.
- Self-service analytics: This technique analyzes the performance of your automated self-service channels, which is extremely useful to understand whether these channels are meeting customer expectations.
- Predictive analytics: This is the most advanced type of call center analytics that uses AI-driven tools to forecast customer behavior and agent behavior, and thus proactively react to issues or challenges.
- Cross-channel analytics: This type of call center analytics is used to understand how customer satisfaction and agent performance differs from channel to channel and thus segment customer audiences and provide more tailored solutions.
- Desktop analytics: This type of call center analytics is used to measure agent performance during operating in the desktop interface of call center solutions, where they spend most of their time.
- Mobile analytics: This type of analytics is used only when contact center agents use mobile devices for servicing customers.
To make call center analytics effective, they have to be processed automatically and provided in a comprehensive manner, which means you require a powerful contact center software to make it possible. Key metrics to track are included in the list below, some of them have industry standards.
- Customer satisfaction score (CSAT)
- Net promoter score (NPS)
- First contact resolution (FCR)
- Average handling time (AHT)
- Average Hold Time
- Service level (SL)
- Occupancy rate
- Customer retention rate
- Average Speed of Answer
- Agent utilization
- Revenue per call
- Outbound calls
How Call Center Analytics Boost The Customer Experience:
Customer experience is the thing that matters the most in the case of customer-brand relationships. Customer experience is the factor that either build customer loyalty or customer churn – depending on the quality of customer experience.
But how can you improve your customer experience? How can you make your customers happy and satisfied with the service? How can you increase your sales and profit?
Enhancing Customer Experience through Call Center Analytics:
Call center analytics serve as invaluable tools for gathering and analyzing data from call center operations, ultimately leading to improved customer experiences. These analytics aid in understanding customer behavior, optimizing operations, and enhancing agent performance.
Providing various communication channels such as phone, chat, email, and social media ensures accessibility for customers. Omnichannel Contact Centers further enhance customer service by offering seamless and personalized experiences across all channels.
To minimize customer wait times and difficulties, IVR call menus, skill-based call routing, and self-service analytics can be utilized. Predictive analytics also play a crucial role in anticipating and addressing customer issues proactively.
Understanding customer sentiments and intentions is facilitated through speech analytics, text analytics, and interaction analytics. Natural language processing (NLP) helps in identifying key customer keywords, expressions, and topics.
Tailoring results and offers to individual customers is made possible through cross-channel analytics, desktop analytics, and mobile analytics. CRM (Customer Relationship Management) Software assists in managing customer relationships and targeting customers based on their behavior and preferences.
Measuring and improving call quality and customer satisfaction is achieved through contact center analytics, call center metrics, and KPIs. Contact center call recordings provide valuable insights into call quality and compliance.
Crucial Criteria and KPIs for Tracking and Improvement:
Tracking and measuring call center performance is essential for operational improvement. Utilizing data and analytics helps in identifying strengths, weaknesses, and areas for improvement.
Key steps include understanding current performance, setting goals, planning strategies, tracking progress, and evaluating impact.
Common agent criteria and KPIs include average handle time (AHT), First Contact Resolution (FCR rate), service level (SL), occupancy rate, agent utilization, satisfaction, and development. Monitoring these metrics allows for assessing agent skills, productivity, and quality. This also allows you to make informed decisions and increase operational efficiency.
Identifying agent strengths and weaknesses enables targeted training, coaching, and feedback initiatives. Optimal agent scheduling, allocation, and routing ensure efficient matching of contact center agents with customers and channels.
By leveraging agent criteria and KPIs, agent performance, customer service, and overall business performance can be enhanced significantly. You can also use AI (Artificial Intelligence) in order to handle incoming calls, replace legacy IVR (Interactive Voice Response) with IVA, measure customer feedback, reduce response times, improve first-call resolution rates, improve customer satisfaction level and receive advanced analytics.