Swoop Launches AI-Powered Healthcare Conversation Agent That Revolutionizes brand.com Engagement

New offering enables pharma brands to engage in 24/7, MLR-compliant near-human interaction with ideal customers in the moment of need

Swoop, a leader in developing precise direct to consumer (DTC) and healthcare provider (HCP) audiences for pharmaceutical and life sciences brands, announced the launch of its AI-powered conversational agent. This groundbreaking advancement in healthcare marketing sets a new standard for lower funnel engagement, enabling immediate, MLR-compliant virtual customer interactions via brand.com.

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“Swoop’s AI-powered conversational agent marks the first groundbreaking advancement for brand.com since the introduction of pharmaceutical websites in the 1990s, addressing a pressing need for innovation in how the industry engages with their customers”

“Swoop’s AI-powered conversational agent marks the first groundbreaking advancement for brand.com since the introduction of pharmaceutical websites in the 1990s, addressing a pressing need for innovation in how the industry engages with their customers,” said Scott Rines, underscoring the historic significance of this achievement. “Patients and physicians are looking for real-time information, 24/7/365 during their moment of need, but are often faced with an overwhelming experience on brand.com. They come to the site seeking fast, clear answers to their health-related questions – our agent solves this.”

Market conditions continue to remain a challenge with shortages of healthcare professionals despite an uptick in customer demand for information related to their condition and treatment decisions. Meanwhile, HCPs are also less likely to allow medical reps into their offices, a shift that has continued post-Covid. Instead, these increasingly digital-native, often over-extended, physicians prefer to seek information online when their schedule permits, limiting the impact of personal promotion.

“The ability to parse the data derived from lower funnel conversations with HCPs and patients in real time will prove invaluable, as these signals will become proprietary 1st party data to optimize future marketing spend and messaging,” added Rines.

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Key Features of Swoop’s Conversational Agent:

• Dynamic Patient Conversations: Patients and HCPs can engage with conversational AI in real-time, creating a personalized and responsive user experience to drive more high-value actions on a health brand website.
• MLR-Approved Medical Information: Leveraging advanced algorithms, conversational AI provides MLR-approved answers to both simple and complex medical questions in the moment of need, enhancing the overall user experience for both patients and HCPs.
• Real-Time Patient Insights: Valuable real-time data from conversations accessible via dashboards allows healthcare brands to assess the effectiveness of their messaging and make informed adjustments promptly.
• Scalable to Client Demands: Whether for a single brand, therapeutic area or product portfolio, Swoop conversational AI agents can scale with the needs of healthcare marketers from new product launches to covering open territories and unsupported brands.
• Patient Data Security and Compliance: Swoop prioritizes patient privacy and data security, ensuring that all conversational AI agents operate in compliance with the highest industry standards and regulations.

Typical Client Results Seen by Customers:

• 96% – Average answer success rate of inquiries
• 5.2 minutes – Typical conversation duration
• 4.7/5 – Average user satisfaction rating
• 800% – Increase in high-value activities on brand websites

Swoop’s conversational AI technology is built on more than 1.3 billion conversations with patients and providers and has been trained under the supervision of physicians and medically trained clinicians. Unlike generative AI, which can hallucinate and is not appropriate for direct patient and HCP interaction in the heavily regulated pharmaceutical industry, Swoop conversational AI uses fine-tuned large language models to understand user intent and surface the most relevant MLR-approved answers to ensure compliance, accuracy and, most importantly, safety.

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