A global pharmaceutical company plans to launch a groundbreaking new product in the respiratory health segment across multiple markets. The client aims to create maximum market impact while ensuring personalized outreach to both healthcare professionals (HCPs) and end consumers.
Using GenAI, Tech4Biz ingested the client’s historical sales data, CRM records, public health data, and third-party market research reports to create dynamic audience segments based on:
Outcome: Created micro-segments of HCPs and consumers for hyper-personalized targeting, enhancing message precision and campaign ROI.
Our GenAI content engine automatically generated:
Outcome: Cut down content production time by 60% while maintaining regulatory compliance and cultural relevance.
GenAI models predicted the best time, channel, and format to engage each segment based on:
Outcome: Increased email open rates by 45%, boosted webinar participation among HCPs by 35%, and improved digital ad click-through rates by 30%.
Tech4Biz integrated the GenAI system with the client’s marketing automation tools (Salesforce, Mailchimp, HubSpot, and social platforms) to auto-schedule and optimize campaigns across:
Outcome: Achieved consistent cross-channel messaging without manual intervention, with dynamic content adjustments based on real-time performance.
AI models analyzed social media sentiment, product review platforms, and post-launch customer feedback to quickly identify:
Outcome: Enabled the client to respond to customer feedback within 24 hours, boosting brand trust and fostering customer advocacy.
Metric | Before GenAI | After GenAI |
---|---|---|
Time-to-market | 6 months | 3 months |
Email Open Rate | 25% | 45% |
HCP Engagement | 30% | 65% |
Content Production Time | 8 weeks | 3 weeks |
Customer Queries Response Time | 48 hours | 24 hours |
Digital Ad CTR | 10% | 30% |
Tech4Biz’s GenAI-driven product launch framework enabled the client to accelerate their go-to-market timeline, improve engagement rates, and optimize customer experiences while reducing operational overhead. This case study highlights how AI-powered personalization, predictive insights, and automation can transform product launches in the pharmaceutical industry.