📊 SayPro Sentiment Heat Map Template
1. Overview
Purpose: To present the distribution of sentiment (Positive, Neutral, Negative) across selected categories or geographic regions based on research findings.
2. Data Structure
| Category/Theme/Region | Strongly Negative | Negative | Neutral | Positive | Strongly Positive |
|---|---|---|---|---|---|
| Example: Access to Education | 🔴 25% | 🟠 15% | ⚪ 20% | 🟢 25% | 🟢🟢 15% |
| Example: Digital Literacy | 🔴 10% | 🟠 20% | ⚪ 30% | 🟢 25% | 🟢🟢 15% |
| Example: Skills Development | 🔴 5% | 🟠 10% | ⚪ 30% | 🟢 35% | 🟢🟢 20% |
3. Color Legend
- 🔴 Strongly Negative (0–20%)
- 🟠 Negative (21–40%)
- ⚪ Neutral (41–60%)
- 🟢 Positive (61–80%)
- 🟢🟢 Strongly Positive (81–100%)
4. Sentiment Source
- Source Data: SayPro Monthly Research surveys, interviews, focus groups
- Sample Size: e.g., 500 respondents across 9 provinces
- Timeframe: e.g., May 2025
5. Interpretation Notes
- Look for categories with high polarity (strongly positive or negative).
- Use as input to guide interventions, campaigns, or policy responses.
- Compare over time to identify trends.
6. Visualization Tools (Optional)
Use tools like:
- Excel / Google Sheets (Conditional Formatting)
- Power BI / Tableau (Heat Map Charts)
- SayPro Dashboard Integration
Leave a Reply