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Create Industry-Leading Customer Experiences in Life Sciences with a Customer Data Platform

To provide outstanding customer experiences, life sciences organizations must personalize content delivery and customer journeys. This requires an in-depth understanding of customers and their preferences, as well as the ability to effectively use this information to deliver tailored omnichannel campaigns across touchpoints in near real time.
Tailoring marketing campaigns and designing cohesive customer journeys across channels can help organizations improve the overall customer experience and drive better business results.
To achieve an advanced level of personalization in both content and customer touchpoints, life sciences organizations must pivot to more intelligent and effective marketing technologies, implement future-proof data strategies, and design cohesive customer journeys.
However, most organizations struggle with these foundational pillars for the 3 major reasons mentioned below.

1. Incomplete and Fragmented Customer Data

A typical life sciences organization has both owned and third-party data from digital and offline engagements across a variety of platforms and channels.
However, these data are usually non-standardized and siloed. The fragmented nature of data does not lend well to integration with other data sources. Often, the data sources are only built to capture data for brand-specific, campaign-specific, or channelspecific objectives and do not capture customercentric data across the journey. This makes it difficult for the life sciences organization to get a single, comprehensive view of the customer, which is essential to personalize their experience.
Organizations need to implement future-proof data strategies such as capturing data in a consistent way, investing in data integration and management technologies, and creating a unified data architecture. By doing so, organizations can ensure that their data are accurate, reliable, and can be effectively used across different marketing channels.

2. Unplanned and Unintegrated Marketing Technology (MarTech) Stack

A poorly planned MarTech stack made up of siloed tools can lead to ineffectiveness in marketing campaigns. The lack of coordination between marketing channels makes it challenging to obtain a complete view of the customer, orchestrate systems of engagement, and provide an engaging omnichannel experience.
To overcome these challenges, life sciences organizations need to adopt more intelligent and effective marketing technologies that allow them to take a customer-centric approach to marketing and enable persona-specific customer journey orchestration.

3. Poor Expertise in Managing Segmentation, Business Rules, and Automation

Your customers are constantly exposed to educational and promotional content. However, they prefer different formats of content at different times through different channels, and these preferences evolve. Similarly, customers have different digital behavior, and this behavior evolves.
Hence, life sciences marketers need to be nimble in creating dynamic segmentations and business rules to personalize customer journeys across these segments. Since all of this needs to happen in near real time, some degree of automation is required to pull this off. This is another area where life sciences organizations are finding it challenging due to the legacy way of targeting different customer segments.
Owing to these factors, life sciences marketers are yet to fully embrace the concept of cohesive and integrated customer journeys, where relevant content is seamlessly delivered across various channels. Consequently, the current level of personalization provided by life sciences organizations is considerably below its optimal potential.

Architecting a Result-Oriented, Future Ready Customer Journey Orchestration Engine

A Customer Data Platform (CDP) serves as a comprehensive tool for marketers, facilitating the collection, management, and activation of customer data. It enables the consolidation of information from diverse sources to construct a 360-degree customer view, which can be leveraged across multiple channels for effective engagement.
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 customer data platform architecture works in life sciences organizations

An enterprise customer data platform 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.

Key Features of a customer data platform

System Integration and Data Collection : Simplify data ingestion across touchpoints
Visitor Profile Stitching : Map and match profiles across channels and data sources
Profile Enrichment and Segment Building : Create rich customer profiles and segment them
Downstream Orchestration : Activate omnichannel personalisation in real time

1. System Integration and Data Collection

A CDP consumes data seamlessly from multiple platforms by leveraging a wide range of inbuilt integrations and capabilities. Data from these sources and platforms could include the following:
Demographic data: Customer designations, specializations, and locations
Channel engagement data: Opened and clicked emails, web visits, browsed pages, etc.
Transactional data: Prescription data or online purchases in case of e-commerce websites
Device and platform usage data: Frequently used devices, operating systems, etc.
Content preferences data: Affinity toward specific content (drug safety and efficacy, customer support, mechanism of action, etc.)
Privacy, consent, and data security preferences data: Holistic data compliance and consent preferences per the customer record
These data are also typically available across different engagement channels and systems of record, including the following:
Internal systems of record: Customer Relationship Management (CRM) systems, Data Warehouses, and Master Data Management (MDM) systems
Existing marketing automation platforms: Campaign management tools for email, social media, and other channels
External data streaming tools: Tag management systems, campaign tracking, etc.
A CDP collects data from across these channels by using either native connectors or additional provisions to ingest data for integration (such as through file uploads).

2. Visitor Profile Stitching

Visitor profile stitching is a critical capability of a CDP that enables a unified view and the ability to identify target customers across multiple channels and map all data points related to their profile across various data sources. Integrating duplicate profiles of the same customer across different touchpoints resolves their identity and creates a holistic customer profile. This comprehensive view is essential for personalizing experiences and delivering relevant content to the customer at every touchpoint.
A CDP typically uses 2 types of visitor profile stitching techniques:
Deterministic matching, a technique to find exact matches between customer records relating to a specific and unique attribute
Probabilistic matching, a statistical approach to measure the probability that 2 customer records represent the same individual

3. Profile Enrichment and Segment Building

As customers interact with various channels over time, their preferences may change. A CDP is capable of capturing these changes and updating the relevant customer profile to maintain its accuracy. By persistently recording customer interactions and preferences at each touchpoint, such as at the beginning or end of a visit or when viewing an email or a video, it enriches the customer profile to provide a contemporary view of their preferences.
In addition, a CDP should be able to assign customers to specific segments based on their reactions to the organization’s channels and assets. As preferences change, it should be flexible enough to modify and re-segment customers into relevant cohorts.
Life sciences marketers can apply specific business rules based on the customer profile and engagement with the content and channels. A CDP enables building audience cohorts based on these business rules. As these rules evolve, it facilitates quick updates to ensure that customers remain up-to-date and seamlessly informed and engaged.

4. Real-Time Downstream Orchestration

A CDP has in-built downstream connectors linked to different records and systems of engagement. These connectors trigger actions or push records for cognitive orchestration of customized customer engagement in near real time. Real-time orchestration can include everything from targeted email campaigns to personalized website content and ads, as well as any other type of personalized interactions with customers.
A CDP enables personalized experiences at scale. We have illustrated one such potential approach with a realworld example of healthcare professional (HCP) engagement using a CDP.

A Sample Customer Data Platform Use Case in Life Sciences Organizations

A leading life science organization was looking to promote a newly launched ophthalmology brand through an omnichannel awareness campaign.
The organization sends an email to all the targeted HCPs announcing the launch. Some HCPs open the email and visit the website for information about the brand, while others are yet to do so. The organization’s medical reps get the HCPs’ profiles and an action item via their suggestion tool to engage the HCPs who have not opened the email, which informs reps to send HCPs a rep-triggered email about the brand. A single source of truth between the mass email tool, website analytics, and the rep suggestion tool is necessary to send suggestions to reps about the HCPs who have not visited the website. The role of orchestration between the systems will be handled by the CDP, which will analyze and trigger the interactions between them for specific HCP segments.
If an HCP who is not on the target list but is in the master record visits the website and the organization does not yet know their identity, the CDP assists the organization in identifying the HCP’s identity from the master records based on their login details or website interactions.
Once the HCP lands on the website, they can access a wealth of information about the brand, including its efficacy, dosage, support , and research details. If the organization further wants to know the HCP’s content preferences to create an enriched profile, then the marketers can set up a rule-based Content Affinity system for better segmentation, which is also managed by the CDP. The CDP calculates the content affinity scores based on the HCP’s link clicks, web page scrolls, and form fill-ups. The HCPs are then segmented based on their content scores, following which the CDP triggers personalized communication for the specific customer segments in near real time.

How to Get Started

The most effective way to personalize customer experiences is by offering them exactly what they are looking for, that is, a consistent and relevant experience across channels at a time they prefer. A CDP creates a single customer view or profile, assigns segments based on business rules, and enables near real-time orchestration. It also enables personalized experiences at scale through effective process, technology, and people.
Get started on your marketing transformation journey with these quick tips:
Revamp and improve first-party channels to ensure that they are prepared for personalization and omnichannel storytelling
Enable data collection practices that capture richer data relating to customer information from first-party channels, such as gated content on digital assets
Create nuanced, data-driven customer journeys with standardized and robust metadata collection practices. Ensure that customer IDs tagged to each asset remain consistent across multiple channels
Ensure that brand objectives are geared toward understanding comprehensive customer behavior and not just focused on capturing data for channel-specific or brandspecific goals

Steps for implementation and adoption

Implementing and adopting a Customer Data Platform (CDP) in the life sciences industry requires careful planning and execution. Let’s look at some crucial steps to get started:
Assess current data infrastructure and identify key data sources for integration with the CDP.
Understand data governance policies, compliance regulations, and security protocols to ensure data protection.
Select the appropriate CDP that meets the organization's needs and objectives.
Conduct thorough training and onboarding programs to familiarize stakeholders with the CDP's functionalities.
Implement a phased approach to integration and testing to minimize disruption to ongoing operations.
Monitor and optimize the CDP strategy to align with evolving business goals and market dynamics.
Foster a culture of data-driven decision-making and encourage cross-functional collaboration to maximize the CDP's value across the organization.
While onboarding a customer data platform (CDP) in order to realize its many benefits can seem daunting, engaging an experienced marketing technology and consulting expert with life sciences industry experience, such as Indegene, can add an immense long-term and specialized value.
Indegene’s unique 5-stage city planning approach to consulting and implementation ensures that life sciences organizations effectively implement and benefit from their CDP investment. Indegene’s expert consultants customize and implement your CDP of choice to fit your first-party data strategy by starting with a 360-degree analysis of your existing MarTech stack and data model, integrating new and existing tools to your CDP ecosystem, and creating business rules and defining segments. Indegene also evaluates and optimizes the implementation with industry-leading tracking and analytics expertise, giving life sciences organizations the capabilities needed to manage data better and deliver the best cross-channel experiences in real time.
And there is always help around the corner. Write to us for a strategic consultation today!