How to Use It:
Share behavioral data (anonymized): interests, purchase trends, timing patterns
Present WhatsApp engagement metrics (e.g., open/reply rates, conversion from chat)
Highlight persona profiles derived from WhatsApp chat flows
Offer data-informed campaign co-creation: “We know when and how users buy this product category—let’s run a joint drop”
Ideal Partners:
Non-competing brands targeting the same audience
Influencers who want better conversion channels
E-commerce platforms or affiliates
67. Sentiment Analysis on WhatsApp Conversations
Analyze emotion and tone in user messages to uncover hidden opportunities and risks.
Why It Matters:
Identify unhappy customers before they churn
Spot upsell moments when customers are delighted
Track CX team tone vs. customer reaction
Correlate sentiment with revenue or retention outcomes
Tools to Use:
NLP libraries (spaCy, TextBlob, or AWS Comprehend)
Fine-tuned GPT models for deeper emotion detection
Tag chats as “positive,” “neutral,” “negative” with intensity scores