SayPro Final Comparative Summary Report

Final Comparative Summary Report

Title: Impact of Revised Segmentation Strategies on SayPro Service Outcomes
Date: April 2025
Prepared by: Echinia Mataban

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1. Executive Summary

This report compares SayPro’s service performance before and after implementing the revised segmentation strategy launched in January 2025. The improvements demonstrate the effectiveness of a data-driven, community-informed, and behaviorally adaptive segmentation model. Gains are especially visible in learner engagement, program completion, and targeted outreach effectiveness.

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2. Key Performance Comparison: At a Glance

Metric	Before (2024 Q4)	After (2025 Q1)	% Change
Overall Course Completion Rate	62%	78%	+25.8%
Average Learner Satisfaction	3.6/5	4.3/5	+19.4%
Dropout Rate	28%	14%	−50.0%
Mobile Access Uptake (Youth Segment)	55%	82%	+49.1%
Re-engagement Campaign ROI	R2.4 per user	R1.1 per user	−54.2%
Community Event Attendance (Cultural Programmes)	1,450	2,290	+57.9%

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3. Strategic Changes Made

Area	Old Approach	Revised Approach
Demographics	Broad age/gender splits	Micro-segments (e.g., unemployed urban youth, single-parent households)
Platforms	Generic SMS & email	Personalized mobile-first campaigns (via WhatsApp, USSD)
Content Delivery	Uniform digital modules	Localized, language-sensitive, device-adaptive content
Feedback Loop	Periodic post-program surveys	Ongoing pulse surveys + AI sentiment analysis
Cultural Programming	One-size-fits-all invitations	Targeted event themes by age/culture/region

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4. Segment-Level Impact Highlights

A. Urban Youth (Age 18–24)

• Completion increased from 61% → 81%
• Average platform engagement up 42%
• WhatsApp chatbot reduced dropout inquiries by 60%

B. Rural Women (Age 30–50)

• Cultural participation doubled after radio-targeted campaigns
• Content in isiZulu and Sepedi raised satisfaction from 3.3 to 4.4 stars

C. Informal Traders (Peri-urban areas)

• Enrollment in financial literacy courses rose by 48%
• 3x increase in self-reported application of skills

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5. Lessons Learned

• Behavioral + demographic targeting outperforms static segmentation.
• Language, access method, and motivational profiling are essential to reaching marginalized segments.
• Continuous feedback loops drive relevance and retention.

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6. Recommendations for Scaling

• Roll out revised segmentation across all provinces and new programmes.
• Expand integration of GPT-based personalization tools for low-literacy and multilingual users.
• Institutionalize quarterly segment impact reviews with automated dashboards.
• Train field teams to collect segment-specific qualitative insights during service delivery.