Marketing AnalystBrand and Market AnalyticsIntermediateSingle prompt

Brand Sentiment Analysis AI Prompt

Analyze brand sentiment from customer reviews, social mentions, and survey data. Data sources: {{data_sources}} (reviews, social listening, NPS survey, support tickets) Time per... Copy this prompt template, run it in your AI tool, and use related prompts to continue the workflow.

Prompt text
Analyze brand sentiment from customer reviews, social mentions, and survey data.

Data sources: {{data_sources}} (reviews, social listening, NPS survey, support tickets)
Time period: {{period}}
Competitors to compare: {{competitors}}

1. Sentiment scoring:
   For each text data source:
   - Classify each item as: Positive, Neutral, Negative
   - Sentiment score: (Positive - Negative) / Total
   - Track sentiment score over time
   - Volume by sentiment category per period

2. Theme extraction:
   - Use topic modeling or keyword clustering to identify the main themes in reviews/mentions
   - For each theme: count of mentions, sentiment split, trend over time
   - Positive themes: what do customers love most? (Product quality, service, value, ease of use)
   - Negative themes: what are the biggest complaints? (Price, reliability, support, missing features)

3. NPS driver analysis:
   - Promoters (9-10): what do they consistently praise?
   - Passives (7-8): what would convert them to promoters?
   - Detractors (0-6): what are the primary complaint themes?
   - For each NPS segment: top 3 verbatim themes

4. Competitive sentiment comparison:
   - Overall sentiment score vs competitors
   - Which themes does our brand win on vs competitors?
   - Which themes do competitors win on? (Areas to improve)

5. Sentiment anomalies:
   - Any spikes in negative sentiment? What triggered them? (Product issue, PR event, policy change)
   - Any unexpected positive spikes? What can we replicate?

6. Marketing implications:
   - Which proven positive themes should be amplified in marketing messages?
   - Which negative themes represent reputation risks that marketing must address?

Return: sentiment score trends, theme analysis, NPS driver breakdown, competitive comparison, and marketing implications.

When to use this prompt

Use case 01

Use it when you want to begin brand and market analytics work without writing the first draft from scratch.

Use case 02

Use it when you want a more consistent structure for AI output across projects or datasets.

Use case 03

Use it when you want prompt-driven work to turn into a reusable notebook or repeatable workflow later.

Use case 04

Use it when you want a clear next step into adjacent prompts in Brand and Market Analytics or the wider Marketing Analyst library.

What the AI should return

The AI should return a structured result that covers the main requested outputs, such as Sentiment scoring:, Classify each item as: Positive, Neutral, Negative, Sentiment score: (Positive - Negative) / Total. The final answer should stay clear, actionable, and easy to review inside a brand and market analytics workflow for marketing analyst work.

How to use this prompt

1

Open your data context

Load your dataset, notebook, or working environment so the AI can operate on the actual project context.

2

Copy the prompt text

Use the copy button above and paste the prompt into the AI assistant or prompt input area.

3

Review the output critically

Check whether the result matches your data, assumptions, and desired format before moving on.

4

Chain into the next prompt

Once you have the first result, continue deeper with related prompts in Brand and Market Analytics.

Frequently asked questions

What does the Brand Sentiment Analysis prompt do?+

It gives you a structured brand and market analytics starting point for marketing analyst work and helps you move faster without starting from a blank page.

Who is this prompt for?+

It is designed for marketing analyst workflows and marked as intermediate, so it works well as a guided starting point for that level of experience.

What type of prompt is this?+

Brand Sentiment Analysis is a single prompt. You can copy it as-is, adapt it, or use it as one step inside a larger workflow.

Can I use this outside MLJAR Studio?+

Yes. The prompt text works in other AI tools too, but MLJAR Studio is the best fit when you want local execution, visible Python code, and reusable notebooks.

What should I open next?+

Natural next steps from here are Competitor Analysis Framework, Market Sizing Analysis, Survey Analysis for Marketing Insights.