SayPro Sentiment Analysis Template: A template to structure sentiment analysis data and make reporting consistent.

SayPro Sentiment Analysis Report Template

Report Title: Customer Sentiment Analysis Report – [Department/Project Name]
Reporting Period: [Month/Quarter/Year]
Prepared By: [Analyst Name/Team] | Date: [DD/MM/YYYY]

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1. Executive Summary

• Overview: Brief description of the purpose and scope of the analysis.
• Key Findings: Top insights from the sentiment analysis (e.g., “70% positive sentiment on support interactions”).
• Trends: Notable changes compared to previous periods (e.g., “Complaints about response time decreased by 15%”).

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2. Data Sources

Source	Volume (Responses)	Time Frame	Notes
Customer Surveys	500	Jan-Mar 2024	NPS embedded
Social Media	1,200 comments	Jan-Mar 2024	Twitter, Facebook
Support Tickets	800	Jan-Mar 2024	Email/live chat

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3. Sentiment Breakdown

A. Overall Sentiment Distribution

• Positive: 65% (😊)
• Neutral: 25% (😐)
• Negative: 10% (😞)

Visual: Pie chart/bar graph

B. Sentiment by Category

Category	Positive (%)	Neutral (%)	Negative (%)	Key Issues (if negative)
Product Quality	75%	15%	10%	Warranty claims
Customer Service	60%	30%	10%	Slow ticket resolution
Pricing	50%	30%	20%	Discount expectations

Visual: Stacked bar chart

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4. Key Themes & Insights

Positive Highlights

• Top Praise: “Friendly and quick service” (32% of positive feedback).
• Improvements Recognized: Mention of faster checkout process (18%).

Negative Pain Points

• Top Complaints:
  1. “Delivery delays” (40% of negative feedback).
  2. “Website glitches during payment” (30%).
• Urgent Issues: Flag recurring complaints for escalation (e.g., IT for bugs).

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5. Text Analytics (Sample Quotes)

Sentiment	Direct Customer Feedback
Positive	“The support agent resolved my issue in under 10 minutes!”
Negative	“Waited 3 days for a reply to my refund request.”

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6. Actionable Recommendations

Priority	Issue	Proposed Solution	Owner	Timeline
High	Delivery delays	Partner with logistics firm	Ops Team	Q2 2024
Medium	Website bugs	Dev sprint for payment fixes	IT	Apr 2024

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7. Conclusion

• Summary: Restate key trends and next steps.
• Follow-Up: Plan for re-evaluation (e.g., “Next analysis scheduled for June 2024”).

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Template Notes:

• Customizable: Add/remove sections for product, region, or campaign-specific needs.
• Tools Used: [e.g., MonkeyLearn, Lexalytics, Python NLTK]
• Confidentiality: For internal use only.

Attachments:

• Raw data files
• Detailed visualizations
• Previous reports for comparison