Real-time Call Centre Analytic Reporting Software

Frequently asked questions

What is call centre analytics?

Call Centre Analytics are the accumulation of data/statistics that gives insights to be able to make informed business decisions. Having full access to the MaxContact platform, you will be able to pull together specific data that will enhance both agent performance and campaign performance.

Why is call centre analytics important?

Having full transparency over your contact centre will allow you to plan shifts for your agents, and plan your campaigns accordingly. You will also be able to see what agents are performing above/below KPI and how each of your campaigns are performing.

What are the types of call centre analytics?

There are several types of call centre analytics, including:

• Real-time analytics: These provide real-time visibility into call center performance, allowing managers to monitor metrics such as average call wait time, agent availability, and call volume.
• Historical analytics: These provide a record of past call center performance, allowing managers to analyze trends over time and make data-driven decisions about staffing and other resources.
• Predictive analytics: These use statistical models and machine learning techniques to forecast call center performance, such as call volume and customer demand, in order to optimize staffing and other resources.
• Quality assurance analytics: These measure the quality of interactions between agents and customers, such as call handle time, first call resolution, and customer satisfaction, in order to identify training opportunities and improve overall customer experience.
• Speech analytics: This involve use of natural language processing and speech recognition to analyze the content and sentiment of customer-agent interactions.
• IVR analytics: To evaluate the performance and user engagement of interactive voice response systems
• Campaign analytics: which would relate to outbound dialer performance and campaign results, tracking metrics such as response rate and conversion rate.

How do you analyse data in a call centre?

There are several ways to analyze data in a call center, depending on the specific goals and metrics that need to be measured. Some common methods include:

• Analyzing call volume: This involves measuring the number of calls received, missed, and abandoned over a given period of time. This data can help managers understand how well the call center is handling the volume of incoming calls, and identify periods of high or low call volume.

• Measuring call handling time: This involves measuring the amount of time that call center agents spend on each call. This data can help managers understand how efficiently agents are handling calls and identify areas where training may be needed to improve call handling time.

• Assessing customer satisfaction: This can be done by surveying customers after they have completed a call, and measuring metrics such as Net Promoter Score (NPS) to understand how satisfied customers are with the call center's performance.

• Evaluating agent performance: This can be done by monitoring calls and measuring metrics such as average handle time, abandonment rate, and first call resolution rate to understand how well agents are performing in different areas of the call center.

• Identifying common issues: By analyzing the data from call transcripts, topics of conversation, customer feedback and other relevant data you can identify the common issues that are faced by customers.

• Investigating Root causes: By identifying the common issues as mentioned above, you can further investigate and identify the root cause of the problem.

These are just a few examples of how data can be analyzed in a call center. Other methods may be used depending on the specific goals and metrics that need to be measured.