Contact center analytics: Everything you need to know

Contact center analytics is the process of gathering and analyzing data generated from customer interactions in a contact center. This data includes customer conversations, self-service usage, and various metrics about the contact center’s performance.

Contact center analytics can help businesses track essential metrics in real-time to understand the customer experience at the moment, allowing them to optimize processes and adjust to changes before they can become major issues. For example, a business that notices the first call resolution rate is trending down may want to retrain first-touch agents to get figures back to an acceptable range. Contact center analytics also provides historical data to help businesses forecast upcoming needs, such as seeing an increase in volume or average handle time around the holidays indicating the need to hire more agents.

Common metrics tracked by contact center analytics can include:

• First call resolution rate (FCR): Measures the percentage of calls resolved on the first interaction, indicating the efficiency of problem-solving within the contact center.

• Average handle time (AHT): The average duration of customer interactions, including talk time and after-call work, reflecting the efficiency of agents.

• Abandoned call rate (ACR): The percentage of calls that are disconnected before reaching an agent, indicating potential issues in accessibility or call management.

• Repeat contact rate (RCR): Tracks the frequency of customers needing to contact the center again for the same issue, signaling the effectiveness of resolutions provided.

• Customer satisfaction (CSAT): Assesses customer satisfaction levels through surveys post-interaction, providing insights into overall service quality.

• Net promoter score (NPS): Evaluates customer loyalty by measuring the likelihood of customers recommending the company's services or products.

By leveraging this data, businesses can enhance the quality of customer service, improve agent performance, and ultimately contribute to higher customer satisfaction and loyalty.

Contact center analytics can be classified into five various types, each focusing on different aspects of customer interaction and service delivery. Understanding these types can help businesses tailor their strategies for enhanced customer experience and operational efficiency.

1. Interaction analytics

This type of analytics includes the analysis of quantitative data such as FCR, AHT, CSAT, and other metrics used by contact centers. Because this data is structured, it’s the easiest to analyze and set goals for improvement. It’s most commonly used to understand performance for the agent and contact center, but as noted, it also extends to customer experience metrics like CSAT and NPS.

2. Speech and text analytics

Speech analytics specifically focuses on analyzing verbal and written communications between customers and agents. This includes the transcription and analysis of voice calls, identification of key phrases, sentiment, and tone. It enables the extraction of meaningful insights from voice and text interactions, such as customer emotions, intent, and compliance with protocols. Speech and text analytics plays a crucial role in enhancing interaction quality and ensuring compliance with regulatory standards.

3. Predictive analytics

Predictive analytics uses historical data and statistical algorithms to forecast future outcomes. In contact centers, this can mean predicting call volumes, customer behavior, and potential service issues before they occur. This foresight allows for proactive measures, such as staffing adjustments prior to a period that’s expected to be busy like the holidays. It can also be used on an individual basis to assist with customer interactions by doing things like prompting agents with suggested text based on similar interactions.

4. Self-service analytics

This branch of analytics focuses on the effectiveness and usage of self-service options like IVR (Interactive Voice Response), chatbots, and online help portals. It evaluates how customers interact with these tools, the resolution rates, and the overall impact on customer satisfaction and call reduction. Self-service analytics is vital for optimizing these technologies to ensure they meet customer needs effectively, which reduces the volume of FAQs to agents.

5. Cross-channel analytics

Cross-channel analytics provides a holistic view of customer interactions across all touchpoints and channels, including voice, email, chat, and social media. This analysis helps in understanding the customer journey as a whole, identifying patterns and gaps in service across different channels. By leveraging cross-channel analytics, businesses can create a seamless and consistent customer experience regardless of the interaction medium.

Contact center analytics is not just a tool for measuring performance; it is a strategic asset that can fundamentally transform how a business interacts with its customers, leading to increased satisfaction, loyalty, and growth. With the right data, businesses can boost contact center efficiency and:

• Enhance the customer experience: Analytics helps in understanding customer needs and preferences, enabling businesses to tailor their services for a more personalized experience. This customization leads to higher customer satisfaction and loyalty.

• Improve operational efficiency: By analyzing contact center metrics, businesses can identify inefficiencies and bottlenecks in their processes. This leads to streamlined operations, better resource allocation, and reduced operational costs.

• Leverage data-driven decision making: Contact center analytics provides actionable insights from data, allowing businesses to make informed decisions. This data-driven approach leads to more effective strategies and solutions.

• Refine agent performance and training: Analytics provide valuable feedback on agent performance, highlighting areas of strength and opportunities for improvement. This leads to more targeted training and development efforts.

• Improve compliance and quality assurance: Speech and interaction analytics ensure compliance with regulatory standards and internal policies. They also help in maintaining high-quality customer interactions.

To truly leverage contact center analytics, embracing certain contact center best practices is essential. These practices not only ensure the precision and relevance of insights but also align them with overarching business objectives.

1. Look at data across all channels

While call centers used to be the core of a business’s support, changing consumer preferences led to the adoption of contact centers to include other channels including social media, email, chat, and texting. When you’re gathering contact center analytics, make sure to get data from all of the channels you offer support through, and look at that data through the same lens. Case in point, some point solutions will measure certain metrics for voice differently than messaging, social, email, or SMS — creating headaches and extra costs for operations teams to “marry” the data between channels.

Looking at cross-channel data through the same view can help you understand support capabilities and the customer experience for each channel, including potential areas for improvement. Ideally, you should use a solution that allows you to dive into analytics for channels individually and for everything at once in a single dashboard like the one from Khoros’s solution below:

2. Prioritize the goals and data you want to track

You may find that contact center analytics allows you to gather more data than you know what to do with, and having so much information may lead to questions about what’s important and how to utilize findings. To avoid data overload, it’s a good idea to meet with other decision-makers throughout the organization to prioritize the goals and data that you want to track closely. You can then use contact center analytics to collect this data, establish benchmarks, and set goals that you track over time. Many solutions like Khoros allow you to customize a dashboard with the most important information available in a single view, with the option to dive deeper when you need to.

3. Wait and assess changes individually

With contact center analytics, you’ll likely find lots of ways to improve your customer experience including a mix of small tweaks and complete process overhauls. It may be tempting to do everything at once, but it’s better to space changes out so you can determine the impact of each thing you adjust on an individual level. It’s best to implement one thing at a time, measure that change’s impact, and then determine if it was successful or if it should be reverted. The amount of time you should wait to make that decision is situational, just make sure you have enough data to draw a clear conclusion.

4. Continuously evolve your analytics strategy

As technology advances and consumer preferences change, your contact center analytics strategy should be updated to utilize new features and shifting customer behaviors. Check-in to see what new features your analytics software has added regularly, and reassess your approach to contact center analytics annually to ensure it’s still relevant to the way your audience engages with your agents. For example, if you notice fewer people reaching out to agents over phone and instead favoring digital media channels — it’s a good idea to update your contact center analytics dashboard to show the performance of each digital channel alongside voice channel metrics. Depending on your solution, you may need to manually enable tracking for certain metrics as well. By staying agile and responsive, you can maintain a competitive edge and better meet the evolving needs of your customers.

Contact center analytics software can be equipped with a range of features designed to enhance customer service operations and provide deep insights into customer interactions. Although each solution is unique, the most common and crucial features you should look for include:

• Real-time analytics: Provides immediate data analysis and reporting, enabling quick decision-making and response to customer interactions.

• Speech and text analytics: Utilizes natural language processing to analyze customer conversations, identifying sentiment and trends for improved communication strategies.

• Predictive analytics: Employs historical data to forecast future trends, helping in proactive decision-making and resource allocation.

• Customer journey mapping: Tracks customer interactions across multiple channels, offering insights into the complete customer experience.

• Quality management: Monitors and evaluates agent performance and customer interactions, essential for maintaining high service standards.

• Cross-channel analytics: Analyzes customer interactions across various channels like phone, email, and chat to ensure a consistent customer experience.

• Self-service analytics: Evaluates the performance of automated customer service tools, crucial for optimizing self-service options and reducing call volumes.

When selecting a contact center analytics solution, be sure to keep in mind the specific needs of your organization and how each feature aligns with those needs. Consider the scalability, integration capabilities with existing systems, and the ease of use for your team.

Khoros Service offers advanced features tailored for today's leading brands. Our solutions can help you improve every aspect of your call center, including deflecting calls with intelligent self-service options, managing high volumes effectively through chatbots, and enhancing service and agent efficiency with AI. By leveraging these innovative tools, you can optimize your KPIs — such as customer satisfaction and first call resolution rate — and drive significant results, ensuring a more streamlined, efficient, and customer-centric contact center operation. For more information and to see these features in action, request a demo to explore the full potential of Khoros' solutions or take a product tour today.

Looking for more information about the digital contact center? Be sure to check out our resources like a comprehensive contact center whitepaper, an informative webinar, and a detailed agent onboarding checklist. These resources will provide you with a deeper understanding of how to optimize your contact center operations, enhance agent performance, and improve customer satisfaction.