Score candidate responses using preferred answers

Last updated: May 27, 2026

Feature Overview

The preferred answers feature allows you to define ideal responses for campaign questions and automatically score candidate answers against your criteria. When you input preferred answer components, the system generates a detailed scorecard that evaluates how well candidates address each aspect of your ideal response. Candidates receive percentage scores based on how many scorecard elements they mention, enabling objective evaluation of open-ended responses and providing comprehensive scoring across multiple campaign questions.

Available Actions

This feature enables you to perform the following actions:

  1. Define preferred answer criteria - Specify what you're looking for in ideal candidate responses

  2. Generate automatic scorecards - System creates detailed evaluation criteria from your input

  3. Score candidate responses - Automatically evaluate answers against preferred criteria

  4. Calculate percentage scores - Provide objective scoring for subjective responses

  5. Track multi-question performance - Combine scores across multiple campaign questions

  6. Generate overall campaign scores - Calculate average performance across all scored questions

  • Step-by-Step Instructions

    Setting Up Preferred Answers

    Accessing Question Configuration

    1. Navigate to Campaign Setup: Go to your campaign creation or editing interface

    2. Select Question Type: Choose to create a "broad question" (open-ended question)

    3. Input Your Question: Enter the question you want to ask candidates

    4. Example Question: "How do you approach providing post-sale customer service and support?"

  • Configuring Preferred Answer

    1. Locate Preferred Answer Section: Find the preferred answer input field below your question

    2. Optional Feature: Note that preferred answers are optional but highly recommended for objective scoring

    3. Define Ideal Response: Input what you consider the ideal answer or key components you want to see

    4. Comprehensive Criteria: Include all important aspects you want candidates to address

  • Example Preferred Answer Input

    For a customer service question, you might input criteria such as:

    • Proactive follow-up communication

    • Issue resolution tracking

    • Customer satisfaction measurement

    • Escalation procedures

    • Relationship building techniques

  • Understanding Scorecard Generation

    Automatic Scorecard

    1. System Processing: Popp analyses your preferred answer input

    2. Criteria Breakdown: System breaks down your preferred answer into specific evaluation points

    3. Example Generation: For customer service question, system might create 5 distinct scorecard criteria

    4. Scoring Structure: Each criterion becomes a measurable component of the candidate's response

  • Scorecard Components

    1. Individual Points: Each aspect of your preferred answer becomes a scoring point

    2. Equal Weighting: Each point typically carries equal weight in the final score

    3. Clear Criteria: System creates specific, measurable evaluation standards

    4. Comprehensive Coverage: Scorecard covers all important aspects of ideal response

  • Candidate Scoring Process

    Response Evaluation

    1. Answer Analysis: System analyses candidate's response against scorecard criteria

    2. Criteria Matching: Identifies which scorecard elements the candidate addressed

    3. Point Assignment: Awards points for each criterion mentioned or demonstrated

    4. Score Calculation: Calculates percentage based on criteria fulfilled

  • Scoring Examples

    Perfect Response (100% score):

    • Candidate mentions all 5 scorecard criteria

    • Addresses proactive follow-up, issue tracking, satisfaction measurement, escalation, and relationship building

    • Receives 5/5 points = 100%

  • Partial Response (20% score):

    • Candidate mentions only one scorecard criterion

    • Addresses only relationship building aspect

    • Receives 1/5 points = 20%

  • Moderate Response (60% score):

    • Candidate mentions 3 out of 5 scorecard criteria

    • Receives 3/5 points = 60%

  • Multi-Question Campaign Scoring

    Individual Question Scores

    1. Per-Question Evaluation: Each question with preferred answers receives individual scoring

    2. Question Performance: Track how candidates perform on specific topics

    3. Detailed Feedback: Understand candidate strengths and weaknesses by question area

    4. Comparative Analysis: Compare candidate responses across different question types

  • Overall Campaign Score

    1. Average Calculation: System calculates average score across all scored questions

    2. Comprehensive Evaluation: Provides overall assessment of candidate performance

    3. Campaign Dashboard: Overall scores displayed in campaign management interface

    4. Candidate Ranking: Enable comparison and ranking of candidates based on overall performance

  • Campaign Dashboard Integration

    Score Visibility

    1. Individual Scores: View candidate performance on each question

    2. Overall Averages: See comprehensive campaign performance scores

    3. Comparative Metrics: Compare candidates against each other

    4. Performance Tracking: Monitor score distributions and candidate quality

  • Data Analysis

    1. Question Effectiveness: Identify which questions provide best candidate differentiation

    2. Scoring Patterns: Analyse common response patterns and score distributions

    3. Candidate Insights: Gain deeper understanding of candidate capabilities

    4. Process Optimisation: Use scoring data to improve question design and preferred answers

  • Best Practices for Preferred Answers

    Criteria Development

    • Comprehensive Coverage: Include all important aspects of ideal response

    • Specific Elements: Define clear, specific criteria rather than vague concepts

    • Realistic Expectations: Ensure preferred answer represents achievable excellence

    • Job Relevance: Align preferred answer criteria with actual job requirements

  • Question Design

    • Open-Ended Format: Use questions that allow candidates to demonstrate knowledge depth

    • Clear Intent: Ensure questions clearly communicate what you're looking for

    • Practical Application: Focus on real-world scenarios candidates will encounter

    • Differentiation Potential: Design questions that will reveal candidate differences

  • Scoring Strategy

    • Balanced Weighting: Ensure scorecard criteria are appropriately balanced

    • Clear Standards: Define what constitutes meeting each criterion

    • Consistent Application: Apply scoring standards consistently across all candidates

    • Regular Review: Periodically review and adjust preferred answers based on results

  • Advanced Scoring Applications

    Campaign Optimisation

    1. Question Refinement: Use scoring data to improve question effectiveness

    2. Criteria Adjustment: Modify preferred answers based on candidate response patterns

    3. Threshold Setting: Establish minimum score requirements for progression

    4. Integration with Rules: Use campaign scores in automated decision rules

  • Candidate Development

    1. Feedback Provision: Use scorecard criteria to provide specific candidate feedback

    2. Skill Gap Identification: Identify areas where candidates need development

    3. Training Recommendations: Suggest specific improvements based on scoring results

    4. Performance Benchmarking: Establish performance standards for role requirements

  • Troubleshooting Common Issues

    Scoring Problems

    • Low Overall Scores: May indicate preferred answers are too comprehensive or unrealistic

    • Score Clustering: All candidates scoring similarly may indicate unclear differentiation criteria

    • Missing Elements: Candidates not addressing key points may indicate question clarity issues

    • Inconsistent Scoring: Review preferred answer criteria for ambiguity or overlap

  • Question Effectiveness

    • Poor Response Quality: Questions may need clarification or better context

    • Irrelevant Answers: Candidates may not understand what you're looking for

    • Score Distribution Issues: Adjust preferred answers if scores are too high or low across all candidates

    • Criteria Relevance: Ensure scorecard elements actually predict job success

  • Quick Reference

    Setup Process: Campaign Question → Preferred Answer Input → Define Criteria → System Generates Scorecard

    Scoring Mechanism:

    • Each preferred answer criterion = 1 scoring point

    • Candidate score = (Points earned / Total points) × 100%

    • Multiple questions = Average of all question scores

  • Key Benefits:

    • Objective evaluation of subjective responses

    • Detailed candidate performance insights

    • Consistent scoring across all candidates

    • Data-driven candidate comparison

  • Best Practices:

    • Include comprehensive but realistic criteria

    • Use specific, measurable preferred answer elements

    • Regularly review and optimise based on results

    • Integrate scores with broader evaluation framework