📊 Analysisintermediate5 variables

Sentiment Analysis

Analyze sentiment in text data.

sentimentnlpcustomer-insights

Template

Analyze sentiment in this content: {{content}} Source: {{source}} Context: {{context}} Please provide: 1. Overall sentiment score (-1 to +1) 2. Sentiment breakdown (% positive/neutral/negative) 3. Emotional tone analysis 4. Key positive themes 5. Key negative themes 6. Notable quotes or examples 7. Comparison to {{benchmark}} 8. Actionable recommendations Output format: {{format}}

Variables to Fill In

1
{{content}}

Content to analyze

Example: [Customer reviews, social media posts, or survey responses]

2
{{source}}

Content source

Example: Twitter mentions

3
{{context}}

Analysis context

Example: Post product launch

4
{{benchmark}}

Comparison benchmark

Example: Pre-launch sentiment

5
{{format}}

Output format

Example: Executive summary with charts

Example Usage

Variables Used:

content = 100 app store reviews from last month
source = iOS App Store
context = After v3.0 release
benchmark = v2.x reviews
format = Product team report

Result:

Sentiment analysis of 100 iOS App Store reviews post v3.0 release compared to previous version.

Tips for Best Results

  • 1Be specific with your variables - the more detail you provide, the better the AI response.
  • 2Start with the example values if you're unsure, then customize based on your needs.
  • 3Iterate on the results - if the first response isn't perfect, refine your variables and try again.
  • 4Combine multiple templates for complex tasks that require different perspectives.