Reports

Analytics Reports

General Call Report

Total call count

This represents the total number of calls received. Monitoring the total call count helps measure the volume of interactions and can aid in resource planning and workload management.

Analyzed call count

Indicates the number of calls that were analyzed. Helps to see the analysis process and completion.

Average call duration

Shows the mean time spent on each call. This allows managers to measure efficiency and identify where the process can be made quicker.

Average silence

The average amount of silence time per call. Reducing silence durations can be a key indicator of improved process efficiency.

Hold ratio

Refers to the proportion of customer calls that are placed on hold during a given time. Reflects the efficiency of call handling, signaling effective call management and resource allocation.

Average hold

Average hold time is the average duration that customers are placed on hold during their calls. Shorter average hold times contribute to better customer experiences, reducing frustration and improving perception of service quality.

Non-FCR Rate

The percentage of calls that were not resolved on the first contact. Reducing this rate can greatly improve customer satisfaction and efficiency.
Transferred Call Rate: Represents the ratio of transferred calls to total number of calls. This would help to examine if customers can land the right queue on their first call.

Mostly Used Phrases

This chart represents mostly used phrases by customers, agents or both. Phrases are different in size according to their importance score, which refers to the distinctiveness of a phrase in conversations.
This metric helps to see important phrases also among the categories, which would eventually help the customers to examine the topics more in depth in terms of trends in customer interactions.

Analysis Status Report

The above pie chart refers to amount of analyzed, not analyzed and no speech call counts among the whole conversations. The process of calls’ analysis can be followed here.

Category Distribution

This graph displays the distribution of call categories based on the number of occurrences. Identifying which categories receive the most attention helps in allocating resources efficiently. High frequency in certain categories might indicate areas requiring more dedicated support or team specialization. By analyzing the distribution, targeted strategies can be planned to address frequently recurring issues. For instance, if "scam blocking" is a high-occurrence category, creating specific protocols or information resources to handle these calls more effectively can be beneficial. Moreover, knowing the categories with higher occurrences helps in tailoring training programs for agents to better manage such calls.

In addition, when a category is filtered, categories that matched with the same conversations are shown in this graph. This would help to see categories' overlapping proportions and leads us to examine these categories' commonalities.

Net Promoter Score

NPS is calculated based on the data from the customers, and the graph tracks their views of the service over time, helping to identify patterns and trends in customer satisfaction. Allows for quick detection of significant drops or improvements in customer loyalty, enabling timely interventions to address issues or reinforce positive experiences.

Daily Conversation Count

The graph represents how the call and chat conversations are distributed in a daily format. Tracking the conversations amounts on a daily basis, helps to understand busy periods. For instance, if a problem occurred with the service of the company, the call numbers could increase. Or if a campaign is launched, interaction may increase for the information exchange. Thus, the customers could foresee such cases and allocate more resources when more agents are needed to handle increased conversation volumes.

Non- First Contact Resolution Category Distribution

This bar chart shows the number of non-FCR cases across different categories. It helps to identify problem areas by highlighting which categories have the most non-FCR cases, optimizes resource allocation by focusing efforts where they are most needed, and improves processes by revealing specific issues that require attention to reduce repeat contacts.

Predicted Customer Satisfaction

This graph shows Predicted CSAT over time, can be seen in daily and monthly format. Predicted CSAT score is calculated based on our sentiment analysis technology, therefore customers satisfactions can be observed even without solid survey data. This allows the companies to see trends in the contentment of their customers with their services, so that they can take action to improve the possible cases where the satisfaction trend is low.

Agent Performance Reports

Total conversation count:

Shows the cumulative number of conversations handled. Helps in determining workload distribution among agents.

Average conversation time:

Indicates the average duration of conversations. Helps measure efficiency and effectiveness in customer interactions. Long or short average conversation times can indicate areas where agents may need further training.

Average hold duration:

Reflects the average time customers were put on hold during a call. Minimizing hold times can improve customer experience and satisfaction, agents that need further intervention about this process can be observed here.

Transfer ratio:

Denotes the percentage of calls transferred to another agent. High transfer ratios can indicate a need for improved initial issue resolution or better initial call routing. This ratio also helps in identifying areas where agents may need additional training to handle.

Average silence ratio:

Measures the percentage of silence during conversations as an indicator of engagement. Helps pinpoint agents who may need additional training or tools to access information more quickly, improving efficiency.

AQM Reports

Agent Performance

Automatically evaluated conversations:

Indicates the percentage of conversations that have been assessed using automated processes. The automatic evaluation process progression can be checked here.

Average score (Automatic):

Represents the average score given to conversations based on automated evaluations. Provides a quick snapshot of the overall service quality, helping to set and maintain performance standards. Identifies the agents that need further improvements and training.

Manually evaluated conversations:

Displays the percentage of conversations that have been assessed through manual, human-led processes.

Average score (Manual):

Shows the average score given to conversations based on manual evaluations. Reflects more nuanced assessments, considering aspects like empathy, tone, and context that are difficult for automated systems to measure.

Agent Objection Reports

Total objection count:

Shows the total number of objections raised against evaluations. Assists in understanding the frequency of disputes regarding evaluations, indicating potential areas of improvement or miscommunication.

Acceptance rate:

Percentage of objections that were accepted upon review. Provides insight into the fairness and accuracy of initial evaluations.

Rejection rate:

Percentage of objections that were rejected upon review. Helps identify the strength and validity of objections raised by agents. Also, if there are agents who frequently make objections, they can be identified and clarification regarding the evaluation criteria can be provided.

Average first evaluation score:

The average score given during the initial evaluation before any objections.

Average last evaluation score:

The average score after objections have been reviewed and accepted/rejected. Reflects adjustments made to scores, providing a more accurate measure of final performance.

Difference rate:

The percentage difference between the first and last evaluation scores. Highlights the impact of successful objections on overall performance scores.

Agent Question Based Reports

Average score per department:

This graph shows the average performance scores of various departments within the company. By comparing departmental performance, management can identify which departments are excelling and which may require additional support and resources. This helps in directing training programs and improving overall organizational efficiency.

Average score per agent:

This graph displays the average performance scores of individual agents. Tracking individual agent performance enables the identification of top performers who can be rewarded or used as examples for others. It also highlights agents who may need more coaching or training, ensuring that support and development are provided where most needed.

Average score per question:

This graph highlights the average scores that agents received regarding specific quality metrics in forms. By analyzing scores for different aspects of the conversation, the company can pinpoint specific areas that need improvement. This aids in the refinement of communication strategies, ensuring agents can provide more effective and higher-quality interactions with customers, ultimately enhancing customer satisfaction and loyalty.

Evaluator Performance

Total evaluation count:

Shows the number of evaluations conducted by evaluators. Helps in workload distribution analysis and assessing evaluation coverage.

Average score:

Represents the average score given across all evaluations. Useful for identifying overall scoring trends and benchmarking evaluator consistency.

Total calibration count:

Indicates the number of evaluations compared against a standard for consistency. Ensures evaluators are aligned with organizational scoring standards and reduces subjectivity.

Precision:

Measures the accuracy of evaluations by comparing them with calibrated scores. Helps in assessing the reliability of each evaluator's scoring.

Total objection count:

Number of objections raised against evaluations done by evaluators. Highlights potential areas where evaluator judgments are frequently contested, indicating a need for review or retraining.

Objectivity:

Measures the impartiality of evaluations by comparing initial score of evaluations and post-objection scores. Helps to ensure evaluations are balanced and accurately reflect agent performance, promoting trust in the evaluation process.

Evaluator Question Based Reports

Objectivity:

This graph shows the objectivity scores for different evaluators. Comparing evaluator objectivity ensures that the feedback provided to agents is fair and unbiased. It helps maintain the integrity of the evaluation process and ensures consistent performance assessment across the board.

Average score per evaluator:

This graph displays the average performance scores provided by different evaluators. By examining the average scores given by each evaluator, the company can identify inconsistencies or biases in evaluations. This helps in training evaluators to deliver more accurate and consistent assessments, which improves the reliability of the feedback provided to agents.

Average score per question:

This graph highlights the average scores that evaluators give for specific evaluation criteria from the forms. By analyzing scores for different aspects of the conversation, the company can pinpoint specific areas that need improvement. This aids in the refinement of communication strategies, ensuring agents can provide more effective and higher-quality interactions with customers, ultimately enhancing customer satisfaction and loyalty.

Premium Reports

We specialize in providing comprehensive conversational analytics, offering a range of insightful reports to our clients. For those seeking even deeper insights and greater customization, we offer premium reports through our seamless integration with Tableau. These premium reports provide more detailed information, tailored to meet specific needs, and empower clients with advanced customization options to derive maximum value from their data. Our premium reports are mainly categorized as Dashboard, Agent Report, Operation Report, Quality Management, and User Defined Category Report.

Some examples of this feature:

Montly FCR status

Montly FCR status can be observed monthly with premium reports. By displaying monthly trends, the graph helps businesses quickly identify and analyze their efficiency in resolving customer issues at first contact. Monitoring these trends allows companies to pinpoint areas needing improvement, enhance their call resolution strategies, improve customer satisfaction, and reduce operational costs associated with repeated interactions.

Agent monthly quality point trend

Agent monthly quality point trend shows the monthly changes in agents' evaluation scores at a glance, allowing managers to track individual performance trends over time. It specifically helps in identifying which agents consistently perform well and which ones may need additional support or training. This targeted insight enables managers to provide personalized feedback, set specific improvement goals, and recognize high-performing agents, thereby enhancing overall team effectiveness and service quality.

Form section drill down

This graph provides detailed insights into average individual agent performance across different evaluation forms at a glance. By breaking down specific evaluations scores, it allows managers to pinpoint precise areas where agents excel or need improvement. These detailed insights helps to ensure a more focused approach to performance enhancement and helps to maintain consistent service quality across different assessment criteria.