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Evaluation Forms provide a flexible framework for evaluating Human Agent and AI Agent interactions using separate evaluation configurations. They support configurable assignments, evaluation criteria, scoring models, duration thresholds, Not Applicable (N/A) scoring treatment, and version-controlled updates. QA Managers can create evaluation forms based on the interaction type. Each form supports only the metrics and workflows applicable to its assigned conversation type. Evaluation Forms support two assignment types:
  • Human Agent: Evaluates human agent interactions routed through contact center queues. Assign forms to Queues and use Human Agent capabilities such as dispute workflows and speech-based evaluation metrics for supported voice interactions.
  • AI Agent: Evaluates AI Agent interactions handled by Automation AI Experience Flows. Assign forms to Experience Flows and use AI Agent-compatible evaluation metrics. AI Agent forms don’t support Human Agent capabilities such as dispute workflows or speech-based evaluation metrics.
For AI Agent-to-Human Agent handoff conversations, the system evaluates AI Agent and Human Agent segments using their respective evaluation forms and applicable capabilities. QAI analytics provide filters to analyze conversations handled by an AI Agent, Human Agent, or both.
Select the assignment type when creating the evaluation form and don’t change it later. Assign each form to either Queues (Human Agent) or Experience Flows (AI Agent), not both.

Supported Conversation Types

Evaluation Forms support the following conversation types:
  • Human Agent conversations: Evaluated using Human Agent evaluation forms assigned to contact center queues.
  • AI Agent conversations: Evaluated using AI Agent evaluation forms assigned to Automation AI Experience Flows.
  • AI Agent-to-Human Agent handoff conversations: The system evaluates AI Agent and Human Agent segments using the applicable evaluation workflows and capabilities.

Key Capabilities


Evaluation Forms Structure

Defines the overall configuration of an evaluation form.

Access Evaluation Forms

Navigate to Quality AI > Configure > Evaluation Forms. Evaluation Forms.

Evaluation Forms List

The Evaluation Forms page displays the following list:
To create AI Agent evaluation forms, also enable the Automation AI Conversation Source.

Evaluation Processing

For conversations that transfer between an AI Agent and a Human Agent, By Question metrics can evaluate transcript context across both conversation segments. This provides additional context for AI-based evaluation while each conversation segment continues to use its own assigned Evaluation Form. This behavior applies only to supported By Question metrics.

Create a New Evaluation Form

Evaluation Form creation consists of three or four steps depending on the selected assignment type.

Configure General Settings

  1. Select the Evaluation Forms tab.
  2. Select + New Evaluation Forms.
  3. Enter the following details:
    • Name: Enter a name for the evaluation form.
    • Description: Enter a description (optional).
    • Language: Select one or more supported languages.
  4. Select a Handled By agent to assign a queue name:
    • Human Agent (Human Agent forms): Creates an evaluation form for Human Agent conversations using supported evaluation workflows.
    • AI Agent (Experience Flow name): Creates an evaluation configuration for AI Agent conversations using supported evaluation capabilities.
  5. Select a Channel type:
    • Chat: Display only chat metrics (excluding speech and voice-specific Playbook metrics).
    • Voice: Display all applicable voice metrics, including speech and Playbook metrics.
  6. Select a Scoring Type:
    • Percentage: Calculates scores based on configured metric weightages.
    • Points: Calculates scores based on assigned metric points.
  7. Select a Not Applicable Scoring Treatment to define how Not Applicable (N/A) metrics affect the final evaluation score for future evaluations only.
    • Exclude from Score (default): Excludes the N/A metric from score calculation by removing its weightage from both the numerator and denominator. The metric doesn’t contribute to the final score.
    • Award Full Weightage: Includes the N/A metric’s configured weightage in both the numerator and denominator, awarding full marks while the metric outcome remains Not Applicable.
  8. (Optional) Set the minimum interaction duration required for evaluation by entering values in MIN and SEC. The system excludes conversations below the configured threshold from evaluation scoring.
  9. Set a minimum Pass Score required for agents.
  10. Select Next. General Settings Configuration

Assignment Requirements

The selected Handled By type determines the available configuration options. Human Agent forms require queue assignments, while AI Agent forms require Automation AI Experience Flow assignments. For Human Agent forms, assign at least one queue before proceeding. The selected Contact Direction determines which interaction types the system evaluates for the assigned queues.
  • Changes to Not Applicable Scoring Treatment apply only to future evaluations created with the updated evaluation form version. Existing evaluations retain the scoring behavior configured when they were created.
  • Not Applicable Scoring Treatment applies consistently to both AutoQA and manual supervisor audit scores across all metric types and versions.
  • Attribute and scorecard scoring are configured separately at the Agent Scorecard level.

Configure Assignments

The Assignments step defines where the evaluation form applies. Based on the selected Handled By type, assign the form to Queues for Human Agent conversations or Experience Flows for AI Agent conversations. You can assign an evaluation form to Queues or Experience Flows, but not both.

Human Agent Assignments

  1. Search and select one or more Queues.
  2. Configure the Contact Direction (Inbound, Outbound, or both) and Conversation Source (such as Contact Center AI (CCAI), AgentAI, or Quality AI Express) for each selected queue.
  3. Review the selected queue assignments.
  4. Select Next. Human Agent Experience Flow
Evaluation metric availability depends on the conversation sources associated with the assigned queues. If an evaluation form includes both CCAI or AgentAI queues and Quality AI Express queues, the By Playbook and By Dialog evaluation metrics are unavailable because these metrics are not supported across mixed conversation sources.

AI Agent Assignments

  1. Search and select one or more Experience Flows.
  2. Review the selected Experience Flows.
  3. Select Next. AI Agent Experience Flow
Experience Flows are retrieved from the configured Automation AI environment.

Experience Flow Assignment Rules

Queue Assignment Rules

AI Agent Assignments

For Handled By = AI Agent, assign the evaluation form to Automation AI Experience Flows.
To create AI Agent evaluation forms, you must enable the Automation AI Conversation Source. If Automation AI isn’t enabled, Experience Flow assignments are unavailable, and you can’t assign AI Agent evaluation forms until the required Conversation Source is configured.
Then continue with:
  1. Search and select one or more Experience Flows.
  2. Review the selected Experience Flows.
  3. Select Next.

Configure Evaluation Metrics

Evaluation metrics define the criteria used to evaluate interactions for audits and AutoQA scoring. The available metric types depend on the selected Handled By type. Manual metrics require evaluator input, while AI-based metrics evaluate interactions by using the configured AI evaluation method. AI Agent Evaluation Metrics

Supported Metric Types

Metric Card Configuration

Configure each metric’s Weightage, Correct Response, and Fatal Error behavior based on whether you enable Trigger Scoring.
Configure negative scoring only at the outcome level.

Configure Dispute Allocation (Human Agents Only)

Dispute Resolution Assignment

  1. Turn on Dispute Resolution Assignment.
  2. Select a dispute routing option:
    • Same Auditor: Routes disputes to the original evaluator.
    • Different Auditor: Routes disputes to another QA evaluator from the selected auditor list.
  3. If you select Different Auditor, search for and select one or more auditors to handle disputes.
  4. Turn on Allow Multi-Round Re-Disputes to let agents raise additional disputes if they disagree with a QA evaluator’s re-evaluation decision. Turn off this option to make the QA evaluator’s re-evaluation final.
  5. Select Max Number of Re-Disputes to define the maximum number of additional dispute rounds allowed after re-evaluation.
If Dispute Resolution Assignment is turned off, agents can’t acknowledge or dispute completed evaluations.

Completed Audit Editing

  1. Turn on Completed Audit Editing to let authorized users update manual audit responses after submitting an audit.
  2. Under Select Auditor, select one or more auditors authorized to edit completed audits.
  3. Select Create to save the configuration.
Evaluation Metrics Dispute Allocation

Metric Rules

  • The combined positive weightage must equal 100% for percentage-based scoring.
  • Configure the expected response and score for every metric.
  • Human Agent forms support all available metric types, and Fatal Error settings apply only to supported metrics.
  • AI Agent forms support only AI Agent metrics used during Experience Flow evaluations.
Completed Audit Editing enables authorized users to update manual audit responses after an audit is submitted. Re-audits impact the auditor score and are recorded in the trial logs. Edit permissions are based on the users added for form re-audits.

Evaluation Processing

Evaluation Behavior

During evaluation, the system selects the applicable form based on the queue, channel, and contact direction. The system skips conversations without matching assignments. Manual metrics work only with points-based scoring and remain excluded from automated scorecards.

AI Agent-to-Human Agent Handoff Evaluation

For conversations that include an AI Agent-to-Human Agent handoff, each conversation segment is evaluated using its corresponding evaluation form:
  • AI Agent segment: Uses the AI Agent evaluation form assigned to the corresponding Experience Flow.
  • Human Agent segment: Uses the Human Agent evaluation form assigned to the corresponding Queue.
Supported By Question metrics can use transcript context from both segments when evaluating the applicable conversation segment.

Form Selection Logic

During evaluation, the system selects the applicable Evaluation Form based on the configured assignment criteria.
  • Human Agent conversations: The system selects the Evaluation Form based on the assigned Queue, Channel, and Contact Direction. An interaction is eligible for evaluation when it’s associated with a queue that has an active evaluation form matching the configured channel and contact direction.
  • AI Agent conversations: The system selects the Evaluation Form based on the assigned Automation AI Experience Flow and Channel. An interaction is eligible for evaluation when it’s associated with an Experience Flow that has an active Evaluation Form for the configured channel.
For Human Agent conversations, the system determines evaluation eligibility based on the conversation’s queue assignment and associated Evaluation Form, not the handling agent’s queue membership or workforce management assignment. Conversations remain eligible when the queue, channel, and contact direction match an active Evaluation Form.

Contact Duration Evaluation

The system evaluates contact duration before scoring.
Threshold updates apply only to future interactions. A contact may qualify for one evaluation form but not another.

Scoring

Scoring Logic

  • Pass: Final score ≥ Pass Score threshold
  • Fail: Final score < Pass Score threshold
The system calculates the final score using positive and negative metric weights.

Not Applicable Scoring Treatment

A metric can have a Not Applicable outcome when a Dynamic metric’s trigger condition isn’t met or an auditor manually marks the metric as Not Applicable. Choose one of the following scoring treatments: Example: A form contains five metrics, each weighted 20, for a total weightage of 100:
  • 3 Adhered metrics = 60 weightage
  • 1 Not Adhered metric = 20 weightage
  • 1 Not Applicable metric = 20 weightage
The system applies this treatment to all metric types and versions for both AutoQA scores and manual supervisor audit scores. The treatment changes only the metric’s weightage contribution. The Not Applicable label, AI justification, and adherence state remain unchanged. Changes to this setting apply only to new evaluations. The system doesn’t rescore previously evaluated conversations.

Points-Based Scoring Formula

Kore Evaluation Score calculates the weighted impact of met and not-met metrics, subtracts penalties, divides by total positive weights, and multiplies the result by 100. ((Myi×Wyi)(Mni×Wni)(Wyi))×100\left(\frac{\sum(M_{yi}\times W_{yi})-\sum(M_{ni}\times W_{ni})}{\sum(W_{yi})}\right)\times100 where,
  • Myi, Wyi = Adhered metrics and positive points.
  • Mni, Wni = Non-adhered metrics and negative points.

Percentage vs. Points Comparison

Quality AI supports two scoring methods.

Weight Assignment Rules

Fatal Error Behavior

Fatal error configuration remains the same for both scoring types. When a fatal metric fails, the system sets the final score to 0 and marks the interaction as failed, regardless of other metric scores.

Manage Evaluation Forms

Edit a Form

Select Edit from the Evaluation Forms list. You can modify: General Settings, Queue or Experience Flow assignments, Evaluation Metrics, and Dispute Allocation (Human Agent only). Select Update to save changes.

Delete a Form

Select Delete from the Evaluation Forms list. Before deleting:
  • Remove all Queue or Experience Flow assignments.
  • Resolve dependent metric or attribute references.
If the form is in use, the system displays a warning before deletion. Select Update to save changes.

Versioning

Every update creates a new version of the Evaluation Form. Existing evaluations continue to use the version that was active when the evaluation started, while future evaluations use the latest published version. Changing the Not Applicable Scoring Treatment follows the same rule. It applies only to evaluations that start after the change, and it never re-scores evaluations already completed or in progress. The system also maintains a history of assignment and configuration changes, including changes to the Not Applicable Scoring Treatment setting.

Conversation Type Support Summary

Switching Scoring Type

Changing the scoring type clears all existing metric weights and requires reconfiguration. Percentage totals must equal 100%, and points-based values must meet the validation rules.

Unsupported Language Issues (Form-Level)

The system blocks the update when a new language doesn’t match the supported languages for one or more associated metrics. For example, adding Hindi to a form with metrics that support only English and Dutch triggers this error. To resolve it, review each metric’s language configuration, update metrics to support the new language, and then add the language to the form once all metrics are compatible.

Metric-Level Language Limitation

The system displays this warning when you add or update a metric that doesn’t support a language configured on the form. Resolve it by configuring the required language on the metric or selecting a metric that supports all form languages.

Language Selection Behavior

Multi-language selection uses an AND condition. The system displays only By-Question metrics available in all selected languages. For example, when you select English and Dutch, the system displays only metrics available in both languages.

Channel Mode Change

Switching between Voice and Chat triggers a warning and removes speech-based metrics. Update remaining metrics and adjust weights before saving changes.

No Dispute Workflow

AI Agent evaluation forms don’t include Dispute Allocation. Agents can’t acknowledge or dispute AI Agent evaluations.

Speech Metric Limitations

Speech-based evaluation metrics aren’t available for AI Agent evaluation forms because Experience Flow evaluations analyze bot interactions rather than voice quality characteristics.