Review Final Survey Results with Statistical Insights
Overview
The Scorecard page in Insights becomes available once your surveys are closed, showing final results in a customizable table. You can create your own scorecard by selecting specific questions and metrics, then reorder them by importance. Enriched with statistical significance, Scorecard helps you compare products and segments with confidence on metrics that matter most to your research.
Creating Your Custom Scorecard
When you first visit the Scorecard page after surveys close, you'll see a welcome screen titled "Jump into your Scorecard" with two options to get started:
- Let's Go!: Uses Highlight AI to intelligently analyze your survey questions and automatically create a scorecard with the most important metrics. The AI prioritizes overall liking questions, purchase intent, and key attributes, presenting them in order of importance with recommended metrics (Top 2 Box, Mean, etc.). This gives you an optimized foundation that you can customize further.
- Start from Scratch: Opens the scorecard editor so you can manually select specific questions and metrics that align with your research objectives.
Note: Scorecard creation requires your surveys to contain scale questions (1-3, 1-5, 1-7, 1-9, 1-11 point scales). If no scale questions are available, you'll see an alert explaining that scorecards cannot be created.
How AI Selection Works
When you click Let's Go!, Highlight AI analyzes all your survey's scale questions to select the most important ones:
- Orders by Importance: Questions appear in order from most to least impactful, not survey order
- Recommends Metrics: Each question gets appropriate metrics (Top 2 Box for satisfaction, Middle Box for JAR, etc.)
You'll see a brief loading screen while Highlight AI analyzes your questions and builds your scorecard. Once complete, you can customize the results by adding, removing, or reordering any metrics.
Customizing Your Scorecard
Click Edit Scorecard to modify your scorecard using the drag-and-drop interface:
Adding New Metrics
- Click Add Metric to open the selection modal
- Choose from the Select Question dropdown (searchable, shows occurrence counts)
- Review the question details including scale type and full question text
- View Suggested Metrics based on the question type (e.g., Top 2 Box for 5-point scales)
- Pick your preferred metric from Select a metric dropdown
- Click Add Metric to save
Managing Your Metrics
- Reorder entries: Drag the move handle (+) on any row to rearrange questions by importance
- Edit metrics: Click the edit icon to change the question or metric type
- Delete entries: Click the trash icon and confirm deletion in the popup dialog
Your changes save automatically as you work.
Accessing Final Results
Your customized scorecard displays as a table organized by:
- Rows: Your selected survey questions in your chosen order. Labels match those from Explore.
- Columns: Combination of Products and Segments.
This setup lets you focus on the specific metrics that matter most for your research objectives.
Filtering with Selectors
Customize your Scorecard with selectors at the top:
- Survey Selector: Choose which survey's data you want to analyze. By default, you view the Trial Survey, which allows for product comparisons. You can also select other available surveys such as Screener survey, Pre-trial surveys, or Post-trial surveys, if your project includes them.
- Product Selector: Pick from Products and Product Groups (same as Explore). Note: The Product Selector is not used when you select a Screener, Pre-trial, or Post-trial survey, as these surveys are not product-specific.
- Segment Selector: Choose Segments like demographics or survey questions (same as Explore). You can use the Segment Selector to analyze responses for all survey types, including Screener, Pre-trial, and Post-trial surveys.
- Confidence Level Selector: Set the statistical confidence level. Options are 99%, 95% (default), 90%, 85%, or 80%. You can only select one at a time.
Adjust these to focus on the data that matters most.
Understanding Metrics
Each question in your scorecard uses a specific metric based on its answer scale. The available metrics depend on your question's scale size:
Available Metrics by Scale Type
3-point scale questions:
- Top Box, Middle Box, Bottom Box, Mean
5-point scale questions:
- Top Box, Top 2 Box, Top 3 Box, Middle Box, Bottom 3 Box, Bottom 2 Box, Bottom Box, Mean
7-point scale questions:
- Top Box, Top 2 Box, Top 3 Box, Middle Box, Bottom 3 Box, Bottom 2 Box, Bottom Box, Mean
9-point scale questions:
- Top Box, Top 2 Box, Top 3 Box, Middle 3 Box, Bottom 3 Box, Bottom 2 Box, Bottom Box, Mean
11-point scale questions:
- Mean
How Metrics Work
Metrics help you understand survey responses by grouping ratings into meaningful categories. Here's what each type means:
Top Box Metrics (Positive Responses)
These show the percentage of people who gave high ratings, indicating satisfaction or agreement:
- Top Box: Only the highest possible rating
- Example: On a 5-point scale (1-5), only responses of "5"
- Useful for measuring excellence or "definitely yes" responses
- Top 2 Box: The two highest ratings combined
- Example: On a 5-point scale, responses of "4" and "5" combined
- Most commonly used - shows general satisfaction or likelihood
- Top 3 Box: The three highest ratings combined
- Example: On a 7-point scale, responses of "5", "6", and "7"
- Shows broader positive sentiment
Middle Box Metrics (Neutral/Optimal Responses)
These focus on middle ratings, particularly useful for "Just About Right" questions:
- Middle Box: The exact center rating(s)
- Example: On a 5-point scale, only responses of "3"
- Perfect for "Just About Right" questions where middle = ideal
- Middle 3 Box: Three middle ratings (only available for 9-point scales)
- Example: On a 9-point scale, responses of "4", "5", and "6"
- Shows the neutral/acceptable range
Bottom Box Metrics (Negative Responses)
These show the percentage of people who gave low ratings, indicating dissatisfaction:
- Bottom Box: Only the lowest possible rating
- Example: On a 5-point scale, only responses of "1"
- Highlights serious problems or strong disagreement
- Bottom 2 Box: The two lowest ratings combined
- Example: On a 5-point scale, responses of "1" and "2" combined
- Shows general dissatisfaction or negative sentiment
- Bottom 3 Box: The three lowest ratings combined
- Example: On a 7-point scale, responses of "1", "2", and "3"
- Captures broader negative sentiment
Mean (Average Rating)
- Mean: The mathematical average of all responses
- Example: If 100 people rate something and the total adds up to 720, the mean is 7.2
- Shows overall performance as a single number
- Useful for tracking trends over time
Reading Your Results
- Box metrics display as percentages: "68%" means 68% of respondents gave ratings in that range
- Mean displays as a decimal: "7.2" is the average rating on your scale
- Higher percentages in Top Box = better performance
- Higher percentages in Bottom Box = areas needing improvement
Interpreting Statistical Significance
Scorecard uses common market research notation to highlight statistically significant results. Here's how it works:
- Each column gets a letter (A, B, C, etc.).
- A green cell means the value is statistically higher than another column at your chosen confidence level.
- The cell includes the letter of the column it's higher than (e.g., "A" means higher than column A).
- We use pair-wise, two-tailed tests: t-tests for Mean, z-tests for proportions. Columns with fewer than 15 responses aren't tested.
Example: Imagine a "Satisfaction" question (5-point scale, Top 2 Box):
- Column A (Product X): 70%.
- Column B (Product Y): 85% (green, with "A").
At 95% confidence, Column B's 85% is statistically higher than Column A's 70%, so it's green with an "A" to show the comparison. Only higher values are highlighted, lower ones stay plain.
Tip: Adjust the Confidence Level to see how significance changes.
Exporting Your Scorecard
Save your custom scorecard as a CSV file:
- Click Download CSV to export your current scorecard configuration
- The file includes all your selected metrics with current Product and Segment filter settings
- Your custom metric selection and ordering are preserved in the export
Tip: Export after making Product and Segment selections to share specific views with your team. The exported file reflects your personalized scorecard setup, making it easy to share tailored insights.
Making the Most of AI-Generated Scorecards
When using Let's Go! to create your scorecard, keep these tips in mind:
- Review the AI's choices: The AI selects questions based on importance, but you know your research goals best. Add or remove questions to match your specific needs.
- Check question order: Reorder them if your stakeholders prefer a different sequence.
- Customize metrics: The AI recommends appropriate metrics for each question type, but you can change them. For example, switch from Top 2 Box to Mean if your team prefers average scores.
- Works with all project sizes: Whether you have 15 questions or 150, the AI focuses on the most impactful metrics to keep your scorecard focused and actionable.
Tip: Start with the AI-generated scorecard, then refine it for your audience. This approach combines intelligent automation with your research expertise for the best results.
← Back to Insights Overview