Overview
Next Best Action is an AI-powered B2B and B2C automated omnichannel orchestration engine that delivers personalized recommendations catered to pharma clients.The solution integrates with data platforms like Cassandra and CRMs like Salesforce and Veeva to generate weekly recommendations automatically, creating a holistic view of customers’ journeys.
An Omnichannel Orchestration Engine that brings together fully automated data integration along with advanced algorithms to customize the experience of every customer with each interaction by identifying
- Who to engage (high priority Healthcare Professionals / Segments/ targets)
- What to share (Messaging/ Detailing, Sequencing of interactions)
- How to share (right channel, frequency, sequence of channels),
- When to share (Day/ time of outreach)
Next Best Action brings in AI, Engineering and Design together to deliver customer decisioning at speed and scale by:
- Leveraging every data signal to create a single customer view
- Building an always-on automated and self-learning recommendation engine for next best experience and other personalization use cases
- Updated the system with every new signal and the AI engine with every customer response
- Gen AI enabled Conversational query engine to answer healthcare professional's profiling or persona related questions for brand teams and field agents.
Next Best Action is build using AWS Glue, Amazon Athena, Amazon Quicksight, Amazon EMR and Amazon RedShift.
Highlights
- Highly customizable: Deep learning-based solution capable of powering the next best experience for each customer with speed @scale. Python/ PySpark codes are completely compatible with on-prem and cloud infrastructures. Complete white-box codes are shared at the end of the implementation.
- Next-Gen Omnichannel Orchestration engine: Integration of real-time experiences across all channels, including F2F and digital, along with a user feedback loop to optimize recommendations in a near real-time fashion.
- HCP360 with persona view and insights: It can complete one NBA use case in 6 weeks, depending on data readiness. No overhead of product implementation.
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