Architecting a Result-Oriented, Future Ready Customer Journey Orchestration Engine
With these legacy organizational issues identified and acknowledged, life sciences organizations can set themselves on a path to overcome them. To ease the transition, life sciences organizations can start by integrating a proven, industry-leading Customer Data Platform (CDP) in their MarTech ecosystem.
A logical representation of how a CDP works in life sciences organizations
A CDP helps life sciences organizations in boosting the effectiveness of their marketing efforts and ensuring attributable return on investment (ROI) with their ability to:
1. Improve Personalization with Unified Customer Profiles
A CDP is inherently customer-centric. By integrating fragmented customer data across siloes, it is able to create a single, unified view of each customer. This single customer view enables marketing teams to craft context-driven and personalized customer journeys, boosting both engagement and retention in a competitive market environment.
2. Enable an Automated Customer Experience Ecosystem
A CDP lets you think, design, build, and implement a comprehensive customer experience ecosystem around it that integrates various life sciences use cases, content, communication channels, customer journeys, and marketing campaigns to deliver a seamless and personalized experience for end customers.
3. Act as a Rules and Orchestration Engine
A CDP allows marketers to code the business rules needed to implement personalized journeys across customer segments. It also allows marketers to modify these business rules easily to reflect the evolving preferences of customer segments over a period of time.
Moreover, a CDP can send relevant customer data and trigger downstream systems of engagement to run personalized journeys for that specific channel, thus effectively playing the role of an orchestration engine.
4. Enable a First-party Data Strategy
With the marketing world grappling with stricter regulation of third-party cookies, life sciences organizations must work faster to ensure that their marketing efforts are not disrupted. A CDP is built with first-party data in mind and can help in reducing your external dependency. This tool enables life sciences organizations to pursue their first-party data strategy while still providing opportunities to integrate with third-party industry sources. This comprehensive view can then be analyzed to generate insights and utilized in advanced analytics use cases such as next best action (NBA).
5. Provide Customer-Level Insights
A CDP helps marketers understand the performance of their campaigns in near real time. For example, data from a CDP can help marketers accurately ascertain the following for any given point in time:
The number of customers within each segment of the marketing funnel
The identities and characteristics of these customers within each segment of the marketing funnel
The intricate digital behaviors exhibited by these customers, offering deeper understanding and actionable intelligence
These insights can be generated in near real time as compared with legacy campaign performance dashboards. These granular insights help organizations make more informed decisions, adapt to changing trends, and drive customer loyalty and retention.
6. Generate Accurate Predictions
A CDP’s unified customer view can act as an input in decisioning engines and help in analyzing customer behavior and preferences and anticipating their future actions to recommend the NBAs that are relevant and personalized to individual customers.
These NBAs can be used to increase customer engagement, drive revenue growth, and improve overall customer satisfaction. Implementing these predictive models can also help in streamlining operations and reducing costs.