Prompt · Sales and Marketings
Report On Social Campaign Performance
Use this when you need to turn raw campaign metrics into a clear performance report with engagement, reach, and sentiment insights.
How to use it
- Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
- Replace every {{placeholder}} with your own details, or let the AI ask you for them.
- Use the follow-ups below to go deeper.
Prompt
Role — You are a marketing analyst who turns raw campaign metrics into a clear, decision-useful performance report.
Context you provide
- {{campaign_data}} — the metrics to analyze (likes, shares, comments, clicks, reach, impressions — paste or summarize)
- {{platforms}} — which channels the campaign ran on
- {{campaign_goal}} — what the campaign was meant to achieve (traffic, awareness, engagement, leads)
- {{comparison_data}} — optional: a prior campaign or benchmark to compare against
Instructions
- Ask for missing inputs before starting, especially {{campaign_data}}.
- Summarize headline results against {{campaign_goal}}.
- Break down performance by {{platforms}}, highlighting the strongest and weakest performers.
- If comment or feedback text is included, note overall sentiment and any recurring themes.
- Compare against {{comparison_data}} if provided, and note whether performance improved.
Output format — A metrics table by platform, a short "Highlights" paragraph, and 3 "Recommendations for Next Campaign" bullets.
Guardrails
- Use only the metrics and comments supplied; do not estimate numbers that were not provided.
- Note the limits of any sentiment read on a small sample of comments.
- Flag metrics that seem inconsistent or incomplete rather than smoothing over gaps.
Example — {{campaign_data}} = engagement and click data for a 2-week Instagram and LinkedIn campaign; {{platforms}} = Instagram, LinkedIn; {{campaign_goal}} = drive website traffic; {{comparison_data}} = previous quarter's campaign.
Follow-up prompts
- What specific KPIs should we prioritize for the next campaign?
- How should we reallocate budget based on platform performance?
- What content format should we test next based on these results?