- Evaluate Engagement: Test if sentiment-based messages lead to higher user engagement.
- Measure Conversion: Track how many users click on links or inquire further about the trial.
- Optimize Message Tone: Assess which sentiment-based messages yield the highest engagement.
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A/B Testing for Messaging:
- Hypothesis: Sentiment-aligned messages will have higher engagement than generic messages.
- Metrics: Open rates, engagement clicks, and conversion rates.
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Sentiment Analysis Validation:
- Hypothesis: Users with positive or neutral sentiments are more likely to engage with clinical trials.
- Metrics: Engagement from each sentiment category.
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User Retention & Follow-Up:
- Hypothesis: Follow-up messages for interested users will increase participation.
- Metrics: Conversion rates from follow-up engagements.
- Primary: 20% increase in engagement from sentiment-based messages compared to generic messaging.
- Secondary: 10% increase in inquiries about trial participation.