What are Contact Center Analytics?

There’s more to contact center performance than meets the eye. If yours is falling behind or you’re looking to tap into the industry’s latest trends, contact center analytics are precisely what your organization needs. 

Call center analytics involve collecting, measuring and analyzing metrics and key performance indicators (KPIs) related to your contact center. The goal is to optimize your agent performance, improve customer experience (CX) and gather insights to make data-driven decisions. With a thorough analysis, you get more than surface-level insights. You get information that will help you streamline efficiencies and predict future behaviors to enhance the contact center experience.

Why Do Contact Center Analytics Matter?

Call center analytics matter for reporting processes since they’re all about tracking, evaluating and maximizing your data. At the core, these analytics are also key to creating exceptional experiences for consumers. Consumers expect positive interactions and seamless support across multiple channels. Consider these statistics:

• 97% of consumers say customer service interactions determine whether they stay loyal to a business.
• 60% of consumers have taken their business elsewhere because of a negative contact center experience.
• 70% of companies see a connection between performance and customer service.

Call center analytics give you a snapshot of customer interactions. You can use the insights you gain to make improvements, resulting in happier customers and boosted revenue.

Understanding Call Center Analytics

Your contact center is a data gold mine. You can track and analyze numerous metrics to drive bottom-line results.

Types of call center analytics

You might consider using various call center analytics based on your goals. Four common areas to focus on include:

• Historical analytics: These analytics give you an understanding of the customer journey so you can offer tailored service and build valuable customer relationships. A customer relationship management (CRM) system can give you historical context from past interactions. With this data, you can identify churn risk and view communication across various touchpoints.
• Real-time monitoring analytics: Real-time analytics give you a live overview of collected data. With to-the-minute analytics, you can take immediate action if issues arise. Supervisors can monitor calls to guide agents through complex queries or step in and take over to minimize consumer friction. Real-time analytics tools compile a dashboard of consumer sentiment and call center performance.
• Predictive analytics: Many analytics focus on past or current interactions. Predictive analytics use machine learning algorithms to forecast outcomes and future issues. These predictions can help you make proactive decisions. For example, analytics might help you determine how many agents you need to handle call volume at a given time or season.
• Speech analytics: Speech analytics software analyzes recordings and picks up sentiment through positive and negative words. You can leverage machine learning and conversational artificial intelligence (AI) to automate analysis and identify opportunities to enhance consumer experiences.

Key metrics tracked

Tracking the right contact center metrics is essential to gauge your service’s efficacy and efficiency. Key metrics include:

• Call volume and distribution: Monitoring call volumes and distribution will help you understand peak call times and effectively assign resources. Call volume refers to the total number of calls within a given time frame. Distribution refers to the way the calls are divided up among your agents. By analyzing call volume and distribution, you can optimize staff levels. Having enough staff to deal with an influx of queries promotes swift service, reducing wait times and offering better CX overall. The insight-driven approach will also streamline your workflows.
• First call resolution (FCR): FCR is a key metric, measuring the percentage of consumer queries resolved within the first interaction with your team—no escalation needed. FCR is important for customer satisfaction. Contact Center Satisfaction Index scores decline as issues require multiple contacts. A high FCR rate shows that your contact center is effective and your team has the resources to handle various issues satisfactorily. You can reduce operational costs by systematically monitoring and refining processes to advance problem-resolution capabilities and CX.
• Average handle time (AHT): AHT measures the typical duration your agents take to handle a call from start to finish. AHT includes talk time, hold time, transfers and after-call note-taking. Monitoring AHT can help you improve your contact center’s efficiency. A moderately low AHT means your agents are empowered and have the resources to deal with queries effectively. An extremely low AHT can be a sign that agents aren’t dedicating enough care to each consumer. Customer satisfaction declines significantly when call handle time extends beyond 10 minutes.
• Customer satisfaction (CSAT) scores: CSAT scores measure customer satisfaction ratings. These scores are generated through customer surveys after a contact center interaction. CSAT surveys are individually collected online, either by email or in-app. The higher the score, the better your CX.
• Net promoter score (NPS): NPS measures consumer loyalty and satisfaction by asking one question: How likely is it that you would recommend (organization x/product x/service x) to a friend or colleague? Customers provide a rating between 0 (not at all likely) and 10 (extremely likely). Depending on their rating, customers are classified as promoters (9 or 10), detractors (0 – 6), or passives (7 or 8). To calculate NPS, you subtract the percentage of detractors from the percentage of promoters. NPS measures consumer advocacy, helping you understand sentiment and find areas to improve your customer experience and drive growth.

The Benefits of Implementing Contact Center Analytics

Call center analytics help you understand what’s currently happening in your contact center operations—and they give you future insights to boost efficiency and CX. Analytics can help you in three core areas:

1. Improved operational efficiency

In-depth analytics will benefit your operational efficiency through:

• Resource optimization: Predictive analytics will help you forecast the resources you’ll need at a given time, so you have enough skilled agents ready to assist customers. Historical analytics will indicate what you need to optimize for better results and what you need to implement to serve consumers best. 
• Workforce management: Analytics play a significant role in workforce optimization. By monitoring and analyzing call volumes, peak times, agent availability and consumer interactions, you can make informed decisions about scheduling, training and empowering your team with the right resources. Workforce analytics can help you streamline operations, maximize productivity and efficiently handle consumer queries. You save on costs and boost your service level. 

2. Enhanced customer satisfaction

Today’s consumers expect fast, convenient and personalized service. Contact center analytics help you identify ways to delight consumers, delivering exceptional satisfaction through:

• Personalized consumer interactions: Leverage past engagements to tailor call center interactions. If you have an omnichannel contact center, you can use analytics to personalize calls.. Your agents can enter conversations with context and knowledge of any previous pain points i so consumers don’t have to repeat themselves.
• Proactive issue resolution: Analytics uncover changes or trends in consumer behaviors. For example, you may notice that call volumes increase after a promotional email blast or after a sale. You can use these trends to bolster resources and prepare to serve consumers quickly when demand is high. 

3. Data-driven decision making

Analytics enable you to make data-rich decisions. You can:

• Identify trends and patterns: Call center analytics help you collect, process and analyze data effectively. By analyzing historical data, you can identify patterns in peak call times, typical queries and agent performance. Continuous trend monitoring will help you identify shifts in consumer behavior and other critical changes. 
• Make informed business strategies: There’s no need to guess how to improve efficiency and cut costs when you have tangible insights. You can quickly identify whether you need more resources or training. You can adapt to disruption and make adjustments based on real-time data, continuously driving your business forward.

Challenges in Implementing Contact Center Analytics

With the right approach, contact center analytics deliver valuable benefits—but some organizations hesitate to use them due to friction points in the implementation process. Three common challenges to leveraging contact center analytics include:

• Data quality and integration: Your contact center analytics platform must integrate with your CRM, email, apps and chat to be effective.
• Employee resistance to change: Call center agents may resist real-time call tracking and supervision.
• Initial implementation costs: If you opt for rip-and-replace models, the initial cost of a system that delivers the insight you need may be expensive. 

Most challenges are simple to overcome with the right solution and solutions provider.

Improve Call Center CX With CSG Xponent

Building a better call center CX starts with understanding customer needs, interactions with your brand and friction points. CSG Xponent, our industry-leading customer experience solution, combines customer data analytics, digital communication and decisioning to help you track customer interactions and deliver exceptional call center customer experiences. Journey analytics tells you what is happening as customers engage with your call center (by measuring key service indicators such as first call resolution, dropped calls and customer satisfaction).

Xponent analyzes interactions and customer behaviors from other technologies (e.g., CRM, billing) to determine the next best action in the contact center, such as:

• Delivering personalized prompts through the IVR
• Routing customers to a specific agent group based on customer needs (e.g., prioritizing tier 2 support)
• Coordinating and sending the right messages for cross-channel consistency (e.g., leveraging a chatbot on the website to inform the agent of the context of a customer call)

Automated self-service, proactive call deflection, intent-based call routing and proactive agent guidance reduce call volume—and provide faster, better customer service when customers speak with an agent.

Success Stories

See how CSG helped a global tech company reduce misrouted calls by 30% and cut transfer rates by over 27%.

Contact us today to learn how to save money, improve CX and boost revenue with Xponent. CSG’s solutions have helped world-renowned businesses access actionable data to boost efficiency and performance. We’ll help you understand and anticipate consumer needs, increase retention rates, and empower your team to communicate quickly and effectively.