Read Time: 12 minutes
Table of Contents
Introduction
Looking to understand and use contact center analytics to boost efficiency and build customer loyalty? You’re in luck! In this article, we’ll explore what contact center analytics are and cover some of the best practices for using contact center analytics to improve business performance and strengthen customer relationships.
Key takeaways
- Understanding contact center analytics: Contact center analytics collect consumer data to help you review customer interactions and make informed business decisions.
- Benefits for business: Tracking analytics can increase customer satisfaction, employee performance, and business efficiency.
- Types of analytics: Performance metrics are measured using different approaches, including descriptive, predictive, prescriptive, interaction, speech and text, self-service, and cross-channel analytics.
- Best practices: Anticipate future customer demands by focusing on the most critical metrics, using consumer data responsibility, and leveraging real-time and historical data.
- Getting started: Define your goals and objectives to set up analytics tracking properly to view customer satisfaction and agent performance
What are contact center analytics?
Contact center analytics involve gathering and reviewing data from customer interactions to help make data-driven decisions that improve the customer experience. This data comes from multiple channels, including phone calls, email conversations, and chat sessions. It’s used to track valuable KPIs, including:
- First-call resolution (FCR): Measures how many issues agents can resolve during the first call, usually expressed as a percentage.
- Average handle time (AHT): Tracks how long an agent takes to complete a customer service interaction.
- Call abandonment rate: Expresses the percentage of calls customers hang up on before speaking with an agent.
- Customer satisfaction (CSAT): Evaluates customer satisfaction through post-interaction surveys, asking them to rate their experience on a scale.
- Net promoter score (NPS): Guages customer loyalty by asking how likely they are to return and recommend your services to a friend on a scale from 1-10.
- Customer effort score (CES): Rates how easily agents could resolve customer concerns.
These are just a few metrics to measure contact center performance
The critical role of contact center analytics
Now that we’ve defined contact center analytics, let’s discuss why analytics tracking is so essential. Contact center data analytics are central to improving business performance and customer satisfaction. By analyzing customer data, you can discover insights into how call agents interact with customers and identify opportunities for operational efficiency.
Tracking first-call resolution (FCR) and other metrics, for example, help you pinpoint where agents excel and where they can improve. Additionally, using contact center reporting and analytics allows you to stay ahead of the curve and reduce churn by predicting future customer behavior.
Types of contact center analytics you need to know
With a clear understanding of the importance of contact center business intelligence, let’s take a closer look at the seven types of contact center analytics that can transfer your customer support strategy.
Descriptive analytics
Descriptive analytics focus on using past data to look for patterns and trends. This is useful for call centers to understand customer needs and make informed decisions.
Predictive analytics
Predictive analytics use historical data to predict future call volume and identify problems before they arise. Knowing these trends can help you plan how to assist customers in the future.
Prescriptive analytics
Prescriptive analytics use descriptive data to give specific recommendations on actions to take, allowing you to adjust strategies in real time.
Interaction analytics
Interaction analytics evaluate all customer-agent interactions to identify patterns, quality of service, and the need for more training.
Speech analytics and text analytics
Speech and text analytics review verbal and written customer interactions via phone, email, and social media to understand common customer queries and trends.
Self-service analytics
Self-service analytics measure how customers use automated tools like chatbots, interactive voice response (IVR), or frequently asked questions (FAQs) to help improve these self-serve options when agents are unavailable.
Customer journey or cross-channel analytics
Cross-channel analytics track the customer journey across multiple communication channels to uncover the most effective ones to use.
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Advantages of using contact center analytics
While we’ve briefly discussed a few advantages of contact center analytics, let’s dive deeper into the three key benefits of using contact center analytics.
Improved customer satisfaction
When it comes to improving customer satisfaction, personalization matters. Based on data from McKinsey, 71% of consumers want personalized experiences in their company interactions. With real-time analytics, call agents can tailor their responses by gathering consumer data across multiple channels and anticipating customer needs before they arise, all while reducing wait times.
Increased operational efficiency
Contact center analytics can drive operational efficiency using data-driven insights. With these insights, you can track how many calls are being resolved and how much time an agent spends with each customer. These metrics allow you to anticipate staffing needs, make informed decisions, and look for opportunities to cut costs.
Enhanced employee performance
Contact center data analytics allow you to monitor calls, chats, and emails shared between call agents and customers. With specific metrics in place, you can see if agents are hitting their goals and pinpoint where they might need additional training.
Mastering contact center analytics: best tips for success
Becoming a master of anything takes time, and mastering contact center analytics is no different. Here are a few tips to increase your chances of success.
Focus on the most impactful metrics
Instead of monitoring every metric, focus on tracking analytics relevant to your business goals and objectives. For example, if customer satisfaction is a top priority, use metrics like the net promoter score or first-call resolution. Narrowing down your focus allows you to make effective data decisions without overwhelming employees.
Combine real-time and historical data
Real-time data provides insights into how many agents are available and how many customers are in the phone queue, allowing contact centers to take calls in an orderly manner.
Historical data, on the other hand, keeps track of trends, patterns, and recurring customer pain points. Using the two together, you can adjust staffing needs and workflows to ensure customers are being cared for.
Leverage predictive and prescriptive analytics for better forecasting
Predictive and prescriptive analytics make it easier to stay ahead of customer needs by forecasting future trends and offering actionable recommendations to make any necessary adjustments.
Prioritize data privacy and compliance
Handle customer data safely and responsibly by encrypting sensitive data and collecting information with explicit consent, like Europe’s general data protection regulation (GDPR)
Strategies for tracking performance with contact center analytics
So, you know what contact analytics are and their importance, but what about monitoring them? Here are the steps you need to take to track contact analytics to improve your business performance effectively.
1. Select the right tool
Before searching for the right tool to track call center data analytics, reflect on your goals and objectives. Once you’ve defined your goals, list the desired features and functions you’d like to have in an analytics tool. For example, if you want to track the customer journey across multiple channels, find a contact center analytics software that uses omnichannel tracking. You might also want to consider if the tool integrates with your customer management system.
2. Define performance benchmarks
Measure your call center goals and objectives by setting a few performance benchmarks for agents to focus on, such as first-call resolution, call transfer rate, and average abandonment rate. Having these benchmarks set proactively will clarify expectations between agents and customers.
3. Set up tracking
Now that you’ve selected the right tool and set specific performance benchmarks, it’s time to track analytics. Start by enabling call recording with a pre-recorded message letting customers know their conversation is being recorded. This will allow you to gather all the data you set up to track and view on an analytics dashboard.
4. Analyze agent performance
With call monitoring and tracking in place, you can view whether agents are hitting their goals. You can also use speech analytics to learn the tone and phrases agents use with customers. Accessing this feedback allows opportunities for coaching and retraining.
5. Evaluate and refine
Monitor analytics and feedback as often as possible to improve business performance and customer satisfaction. For example, you can adjust KPIs to track new customer data that meets your goals and objectives
By following these five strategies, you can set your agents and customers up for success.
Contact Global Response to see how we can support your call center goals.
