Call center analytics and reporting software

Hold your team to the highest standards with actionable business insights

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Gain actionable call center data and insights from every customer

Uncover patterns and relationships in your customer base and your workforce through predictive data mining unified on a single, integrated application. Discover up-to-the-minute metrics and key performance indicators (KPIs) on a customizable dashboard and data platform to better inform business-critical decisions for contact center management. Utilize both predefined and custom reports to share analytics with your team and stakeholders for measurable change.

text and speech analytics

Use text and speech analytics to spot trends

Observe trends and changes in customer interactions with agents through intelligent speech and text analytics instead of simply analyzing volume and pitch. Extract meaning from complex conversations and pair that with customer data and analytics to automate your call scoring to create a predictive model for determining call disposition.
monitor performance

Monitor and improve customer satisfaction while improving agents’ performances

Align your business operations with goals by offering communication channels that users want to use, not what agents are used to using. Use predictive analytics for better call flows and customer interaction strategies. Follow the customer journey across multiple channels (SMS, chat, email, and social media) to align employee engagement and operations with a pleasant and consistent user experience.
enhance team performance

Enhance team performance with call center analytics ownership and accountability

Connect the dots between investment and return on customer engagement for better ownership and accountability in your contact center.

Frequently Asked Questions about call center analytics and reporting

Call center analytics and reporting refer to both the processes and the technologies that organizations use to gain actionable insights into the different aspects of their business performance. Through the systematic processing of unstructured data from different data sources into useful reports, analytics allow your company to discover, interpret, and communicate patterns that can be used to formulate new strategies for different purposes like to enhance agent performance and to improve customer experiences.

RingCentral Cloud Contact Center solution includes a wide range of call center software analytics and reporting tools that organizations can use to get in-depth information needed to make critical business decisions.

Whether for real-time or historical analytics capabilities, RingCentral’s flexible cloud call center reporting tools gives your company an overarching view of how your call center is handling customer engagement and lets you dig deep into data to get a better understanding of evolving call trends.

Call center metrics and KPIs (key performance indicators) are measurable values that show how effective your organizational setup and contact center software are at achieving their goals and objectives.

Each contact center operation will have different sets of reports and data produced that is unique to them. It can depend on the business type and the type of calls they get. It means that each organization may have different KPIs to measure success.

That said, there are general call center metrics and KPIs that are used in many contact centers across different companies to measure both agent performance and customer experience.

Some of the key metrics used for customer experience analytics include:

  • First contact resolution

    This refers to the resolution rate within the first contact with the customer. The goal is to find ways to increase this metric because it not only means better customer satisfaction but also lower call volume for your agents.
  • Customer effort

    This refers to how easy or how difficult it is for customers to either find what they are looking for or get connected to an agent. The goal is to make it as easy as possible for customers to connect to the resource(s) they need to resolve their problems.
  • Queue, ring, and hold time

    These are three separate customer call metrics, but they have one thing in common—the customer is left waiting. Queue time refers to the average time customers are in call queue before they are connected to an available agent through the automatic call distribution feature. Ring time refers to the number of rings it takes before an agent answers a call. Finally, hold time refers to the amount of time a customer is put on hold during a live call. Of course, the goal here is to reduce customer wait time as much as possible.
  • Abandonment rate

    This refers to the rate of customers hanging up before they get a resolution or are connected to an agent, which is also related to customer effort and “wait” time metrics. Like those, you want to have low numbers for these.
  • Self-service effectiveness

    A lot of modern contact centers implement self-service, options, usually through the interactive voice response (IVR) feature with a combination of artificial intelligence and machine learning. You want to measure its efficacy so you can continuously configure it to be able to resolve more phone calls and reduce the burden on your agents.

Those are just some of the metrics used to measure customer experience for better customer retention. Now let’s see examples of metrics used by call center managers to measure how good agents are at their job.

Call center agent performance KPI examples include:

  • Agent productivity

    This is a general metric used by contact centers to refer to the amount of time spent on different agent activities. This includes productive activities like being on a call or attending training. It also includes non-productive activities such as idle time, waiting for calls, and breaks. Note that non-productive activities are not automatically negative, this metric just gives a picture of when production is highest and when it is not.
  • Quality score

    This is the performance rating given to the interaction of an agent with a customer based on the standards set by the company. It helps identify areas of strength and weaknesses.
  • Call handling time/Number of calls handled

    Call handling time refers to the average time an agent handles a call. It starts from the moment the call comes in, and ends the moment the call is terminated. This is also connected to the total number of calls answered. Shorter call handling times usually result in more calls handled.
  • Phone etiquette and adherence to procedures

    This measures the quality of the agent’s etiquette during a live call and their ability to follow protocols. Quality assurance teams usually base this metric on a number of factors that can be checked off; examples include properly greeting the caller and by-the-book transfer of the call to another department.
  • Product/service knowledge

    This measures the agent’s knowledge base with regards to the product or service of the company.

Aside from the goal of better call center experiences for both agents and callers, call center analytics software can also be used to get insights into how a company can allocate resources and reduce operational costs. It is also the driving force for better contact center workforce management and workforce optimization.

There are a lot of different ways to use call center data to gain insights into your contact center operations.

First, you can use static historical reporting to make more tactical and strategic decisions outside the flow of operations or to modify predictive analytic models for improving processes, workflows, and profitability. Historical analytics is great for looking at past trends to make more informed choices in the future.

Realtime reports, on the other hand, are best suited for making operational decisions within the flow of your contact center operations. With it, you can run existing predictive models and get current insights immediately.

Note that neither mode of reporting is better than the other. Historical and real-time analytics can co-exist and actually work as complement to each other.

There are also a variety of ways to capture important data from your call center. Each has its own advantage in providing actionable insights into different aspects of your operations—it is up to your business to make the most out of it.


  • Predictive analytics

    Through a combination of different processes and methods, which include data mining, statistics, and even AI, predictive analytics applications are able to analyze huge amounts of data - both structured and unstructured - to come up with predictive intelligence. This helps you modify strategies and procedures to improve agent performance and customer relationships.
  • Customer satisfaction survey (CSAT)

    This is a common way of determining customer satisfaction scores. This is used to track and monitor the degree of satisfaction with regards to your company’s products and/or services.
  • Call recordings

    This may not directly provide reports and numbers, but it is used by quality monitors to determine call center agent’s performance. In combination with other data sources, it can provide your call center the details you need to make more informed decisions
  • Speech analytics

    Uses algorithms to analyze tone of voice to measure agent and customer’s emotion for both inbound calls and outbound calls. Data from this can be used to improve agent skills and fill in gaps in knowledge.
  • Text analytics

    Your contact center is no longer just limited to voice; it now also communicates through different channels like email, chat, and social media. Text analytics analyzes the text in typed communications, similar to how speech analytics is used for voice calls.
  • Omnichannel/cross-channel analytics

    Because your customers connect with you on multiple channels, this type of reporting and analytics ensures that data flows across all channels, allowing you to optimize and streamline customer experience.
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