Reassess Foundational Assumptions
Goal: Ensure SayPro’s behavioural models reflect current realities.
- Audit existing models for outdated assumptions or generalized personas.
- Align definitions of behaviour drivers (e.g., emotional, social, cultural) with SayPro’s segmentation research (e.g., SCRR-1).
- Validate against new insights from SayPro’s monthly and segmentation projects.
🧠 2. Integrate Latent Needs & Motivational Layers
Goal: Add depth to understand why users behave a certain way.
Enhance SayPro’s model layers with:
- Latent motivations: e.g., autonomy, purpose, recognition, mental wellness.
- Micro-moments: Map real-time decision triggers, especially for SayPro mobile and training platforms.
- Value-based personas: Segment based on values and beliefs (e.g., sustainability, equity), not just demographics.
🔄 3. Behavioral Feedback Loops
Goal: Introduce adaptive modelling.
- Use SayPro platform analytics to dynamically update behavioural profiles.
- Build feedback mechanisms that capture motivations at point-of-interaction (e.g., why did a user abandon a course? Why did they donate?).
- Leverage machine learning clustering on behavioral patterns over time (e.g., seasonal, regional, life-stage-based).
🧭 4. Cross-Channel Experience Mapping
Goal: Track behavioural influence across the SayPro ecosystem.
- Connect user behavior across SayPro Services, SayProApp, SayProCourses, etc.
- Identify key influence pathways (e.g., What content nudges training enrollment? What events lead to NPO registration?).
- Refine the models to account for cross-behavior triggers (e.g., donation after course completion).
📊 5. Behavioral Archetype Expansion
Goal: Evolve SayPro’s user segments beyond broad categories.
Introduce dynamic archetypes like:
- The Impact-Seeker – motivated by social change and purpose.
- The Growth-Oriented Learner – driven by upskilling and career mobility.
- The Community Champion – loyal user, highly active in SayPro forums/events.
- The Silent Observer – visits often but rarely acts; needs nudges and trust-building.
⚙️ 6. Embed Behavioural Science Principles
Goal: Improve the model’s predictive and prescriptive power.
Incorporate:
- Nudging & choice architecture – e.g., highlight “most impactful” action in UI.
- Loss aversion & social proof – e.g., “Join 4,000 others who completed this.”
- Temporal discounting – build urgency through limited-time programs or incentives.
🧪 7. Test, Iterate, Validate
Goal: Ensure continual improvement.
- Run A/B tests on SayPro’s platforms using different nudges or personalization strategies.
- Monitor engagement metrics and conversion rates tied to model assumptions.
- Use SayPro Research Office to conduct qualitative validation (interviews, shadowing).
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