Genesys KPI Insights (BO07) for PureConnect

From Genesys Documentation
Jump to: navigation, search
This topic is part of the manual PureConnect Use Cases for version Current of Genesys Use Cases.
Monitor and analyze interaction data to detect addressable service level anomalies

What's the challenge?

You need quick and easy access to data insights that will help you improve results. When data is missing or is inconsistent across channels, and when business users find it difficult to get to information they need to make good decisions, customer and agent experiences suffer.

What's the solution?

Improve the customer and employee experience by giving business users a full view into real-time agent and workgroup activity and tools to take timely action. Genesys KPI Insights monitors performance against operational goals and provides simple filtering, drill-down and reporting to address service issues in a snap.

Other offerings:

Use Case Overview

Story and Business Context

Business users must be able to report, monitor and make decisions regarding their contact center/customer experience to ensure ongoing improvement and the best business outcomes. Knowing when changes need to be made, the impact of the change, and when not to make changes requires the ability to rapidly identify anomalies and understand the root cause behind the anomalies. Maintaining alignment between routing, reporting, and resources is essential in streamlining the business and driving optimization. Companies set their business plans regularly along with the key performance indicator (KPI) objectives that they use to measure customer experience success. To manage the company's contact center objectives and meet end customers' business needs, there is a set of required operational KPIs.

A good business practice is to analyze contact center performance through the review of service level targets and agent performance. The goal is to assess areas of focus to improve the customer service quality and identify any remediation actions.

For example, a contributing factor for service level targets is the percentage of interactions answered within a time frame (target). A contributing factor for agent performance is the average agent negative/positive score. For example, an organization might set an objective to have the service level KPI and the average agent negative/positive score be within the reasonable limit that is set by supervisors according to business needs.

Use Case Benefits*

The following benefits are based on benchmark information captured from Genesys customers and may vary based on industry, lines of business or Genesys product line:

Use Case Benefits Explanation
Improved First Contact Resolution Provide visibility into call repetition pattern in reports
Increased Revenue Isolate and track anomalies to facilitate root-cause analysis to remedy issues
Reduced Administration Costs Increase visibility into training needs and skills-based routing through better reporting data. Provide readily available reports through KPI-based reporting
Reduced Interaction Transfers Reduce transfers because of additional visibility attained through KPIs that help identify areas of training and skills-based routing optimization
*You can sort all use cases according to their stated benefits here: Sort by benefits

Summary

Improve efficiency through real-time reporting to improve agent utilization, reduce churn, and enhance customer satisfaction scores. Companies need the ability to monitor and analyze detailed interaction data to discover anomalies inservice levels and agent performance. Mapping this data against business outcomes across all channels, and where appropriate, companies can make informed strategic and operational decisions that minimize future anomalies.


Use Case Definition

Business Flow

(1) Service Level Analysis


The flow below describes how a team lead or supervisor would perform a service level analysis. The reports needed for this analysis are defined in the Business Flow Description.

Business Flow Description

  1. The actor (team lead, supervisor, or business analyst) runs a dashboard. Reference - BL1
  2. The supervisor reviews the dashboard and checks it against business level KPIs for service level, interactions answered, and customer segmentation. Reference - BL2
  3. If the supervisor finds anomalies in the service level target, they analyze further reporting data to identify anomalies with factors that contribute to service level. Reference - BL3
  4. For further analysis, the supervisor looks at the service level target against the other variables and notices that the number of interactions answered is trending lower. Reference - BL4
  5. The supervisor analyzes the information for anomaly details and correlations and finds out that there were a few agents with higher than normal average talk times.(For example, workgroup, agent statistics KPI). Reference - BL5
  6. This information helps the supervisor identify the root cause for the service level anomaly. As an example, the supervisor looks into an agents’ interactions and discovers a very long interaction with multiple holds. After talking to the agent or listening to the call, the supervisor determines that the call was complex for agents to handle and it required multiple holds to get assistance. Subsequently, the supervisor identifies that the root cause is the training of agents who service a particular customer segment. Reference - BL6
  7. The team lead or supervisor takes appropriate action.

Business Flow

(2) Agent Performance Analysis


The flow below describes on how a team lead / supervisor would perform an analysis of agent performance. The reports needed for this analysis are defined in the Business Flow Description.

Business Flow Description

  1. The actor (team lead, supervisor or business analyst) runs a dashboard. Reference - BL1
  2. The supervisor reviews the dashboard against business level KPIs for agent performance and customer segmentation. Reference - BL2
  3. If the supervisor finds anomalies in the average agent score, they analyze further reporting data to identify anomalies with factors that contribute to agent score. For example, the supervisor might be able to determine which workgroup and/or agent show high average agent negative/positive scores. Reference - BL3
  4. The supervisor looks further into the details (for example, by filtering and sorting against workgroup and agent). Reference - BL4
  5. The supervisor analyzes the information for anomaly details and correlations (for example, workgroup, agent statistics KPI). Reference - BL5
  6. This information helps the supervisor identify the root cause for the average agent score anomaly. As an example, they may identify that high average agent negative/positive score is driven by certain agent statistics, Workgroup, etc. Subsequently, the supervisor identifies that the root cause is a particular agent servicing a particular customer segment. Reference - BL6
  7. The team lead or supervisor takes appropriate action.

Business and Distribution Logic

Business Logic

Parameters and Business Rules

Service Level Analysis

BL1: Assign reports to roles within the company

  • The business decides during implementation and operation which roles have access to view dashboards. The roles are based on users' access rights and are configurable in Interaction Administrator.
  • The roles are then assigned to report users to have a login to the online reporting.
  • This is part of CX Insights standard capabilities.

BL2: Comparison of reports with business level KPIs:

  • The actor analyzes the Multiple Workgroup Interval Analysis dashboards and notices that the service level target is low for the current shift or period.
  • The actor reviews the report against business level KPIs for service level and customer segmentation.
  • The actor reviews the service level in the report and notices that the number of interactions answered is low and decides to investigate.

BL3: Analysis of contributing factors

  • The parameters that drive service level target are interactions answered and average talk times of an agent.
  • When an anomaly is seen in service level target on the reports, the actor investigates the cause of the anomaly and makes a decision by evaluating the multiple workgroup intervals.
  • The actor has the service level set for their team and measures against these values. The service level target parameters are part of the reporting. Threshold values can either be set by the actor or be automatically calculated in Interaction Administrator.

BL4: Filter into details

  • The reporting user starts to filter the reports to identify the underlying root cause of the high average talk times and lower interactions answered.
  • The reporting user makes a decision as to where the underlying driver of the service level target is coming from and compares different KPIs with other agents.
  • The service level parameters are part of CX Insights. For example, calls answered, calls on-hold, and average talk time.

BL5: Identify correlations

  • The filtering continues to identify the underlying root cause of the high average talk times and lower interactions answered.
  • When an anomaly is seen in the reports, the actor investigates the cause of the service level anomaly and identifies that average talk time and average hold time have risen at the same time that the service level was not met by evaluating the Multiple Workgroup Interval and Agent Dashboards.
  • The actor sees that the average talk time for the period exceeded the service level.

BL6: Identify root cause

  • The parameters are part of CX Insights reporting.
  • The actor investigates the agents and decides whether the newly hired agent(s) require training to reduce the average talk times and hold times or if other corrective action should be taken, such as making changes to the routing, scheduling, skill levels, etc.

Agent Performance Analysis

BL1: Assign reports to roles within the company

  • The business decides during implementation and operation which roles have access to view dashboards. The roles are based on the access rights the user has and are configurable in Interaction Administrator.
  • The roles are then assigned to report users to have a login to the online reporting.
  • This is part of CX Insights standard capabilities.

BL2: Comparison of reports with business level KPIs:

  • The actor analyzes the agent overview and multiple workgroup overview dashboards and notices that the agent negative/positive score is high for the current shift/period.
  • The actor reviews the report against business level KPIs for agent performance and customer segmentation.
  • The actor reviews the average agent score in the report and notices that the agent negative score exceeds the set threshold value and decides to investigate.

BL3: Analysis of contributing factors

  • When an anomaly is seen in average agent scores in the dashboards, the actor investigates the cause of the anomaly and makes a decision by evaluating the agent and the subsequent workgroup.
  • The actor's team has set threshold values and measures scores against these values. The average agent score parameters are part of the reporting and the threshold values can either be set by the actor or be calculated automatically based on the percentage range.

BL4: Filter into details

  • The reporting user starts to filter the dashboards to identify the agents having high average agent negative scores.
  • The reporting user makes a decision as to the source of the high average negative score and comparesdifferent KPIs with other agents. For example, calls answered and calls on-hold.
  • The average agent negative score parameters are part of CX Insights.


BL5: Identify correlations

  • The filtering continues to identify the underlying root cause of the agent negative score.
  • When an anomaly is seen in the reports, the actor investigates the cause of the high agent negative score.
  • The actor views the average negative score time for the period that exceeds the threshold value.

BL6: Identify root cause

  • The parameters are part of CX Insights reporting in the agent and workgroup dashboards.
  • The actor investigates the agent performance and decides whether the newly hired agents require training to improve the call quality or if other corrective action should be taken, such as making changes to the routing, scheduling, etc.

Distribution Logic

N/A

User Interface & Reporting


Agent UI

N/A

Reporting

Real-time Reporting

The agent and workgroup dashboards provide users with an easy way to see a wide range of real-time agent and workgroup activities to understand the current state of the contact center. The visualizations include the number of agents on- and off-queue, time in statuses, and insight into the interactions answered and on-hold, complete with filtering and sorting capabilities.

Master Filters on Dashboards:

  • Workgroup selection
  • Interval selection
  • Agent Selection

Agent Dashboards -It is possible to report the following KPIs:

  • Avg Wait Time
  • Avg Talk Time
  • Avg Hold Time
  • Longest Talk Time
  • Longest Wait Time
  • Agent Availability
  • Average Agent Negative/Positive Score
  • Average CustomerNegative/Positive Score
  • Workgroup Dashboards -It is possible to report the following KPIs:
  • Avg Wait Time
  • Avg Talk Time
  • Avg Hold Time
  • Total Talk Time
  • Total Wait Time
  • Total Hold Time
  • Service Level Missed Target
  • Service Level Target
  • Abandon Rate Missed Target
  • Abandon Rate Target
  • Longest Talk Time
  • Longest Wait Time
  • Longest On-Hold Time
  • Agent Availability


Release Notes:https://help.genesys.com/cic/mergedprojects/wh_rn/desktop/cx_insights.htm

Historical Reporting

Use Interaction Reporter for some performance analysis reports.

Customer-facing Considerations

Interdependencies

All required, alternate, and optional use cases are listed here, as well as any exceptions.

All of the following required: At least one of the following required: Optional Exceptions
None None None None


General Assumptions

  • Customer should have new analytics feature license enabled to view the dashboards.
  • Drill down capabilities are available for some reports in Interaction Reporter.
  • This use case is for Inbound interactions only.
  • The following user roles will be supported within the scope of this use case: Team Lead, Supervisor, Business Analyst.
  • Other requirements
    • KPI captured and analyzed is part of CX Insights
    • This essential use case is based on the Servicel Level metric and Agent Performance
    • Once anomalies are identified in reports, the team lead/ supervisor can take actions:
      • Agent performance in terms of call quality, average wait times
      • Train additional agents with the impacted skill to take care of the call quality influencing interactions.




Document Version

  • Version ver 1.0.1 last updated February 26, 2021