Part 2: Personalization: The Role of Omnichannel Marketing

Continuation from Part 1...


Building upon the foundation in the first part of this article series, we explored the evolution of personalization and its impact within multi-channel marketing; we now shift our focus to omnichannel personalization within Life Sciences, Healthcare, and Health Insurance. I will add other industries for clarity and examples as they tend to be more mature with these approaches. Within Life Sciences and Healthcare, where privacy, precision, and relevance are paramount, the power of tailored experiences is a strategic imperative that fuels patient enrollment, engagement, provider relationships, member loyalty, and business success. As we transition from multi-channel to omnichannel marketing, we uncover how the Life Sciences can potentially harness personalized strategies across diverse touchpoints.

The Role of Personalization in Omnichannel Marketing for Life Sciences, Healthcare, and Health Insurance

In Life Sciences, Healthcare, and Health Insurance, omnichannel personalization takes on new dimensions. Imagine a patient discovering a pharmaceutical product through a digital ad, scheduling a virtual consultation with their healthcare provider, receiving personalized health information via their insurance app, and seamlessly picking up their prescribed medication from a local pharmacy—all orchestrated to cater to their unique needs and preferences. This customer experience journey is the essence of omnichannel personalization in health. Adobe has many use cases for Life and Health Sciences, and its teams specialize in discussing the various approaches. When I worked at Adobe, we worked intensely with MD Anderson, Kaiser Permanente, Aetna, United Health, and InterMountain Healthcare on many of these topics.

At its core, omnichannel personalization is about understanding the distinct roles of payors, providers, patients, and pharmacies and creating a synchronized experience that supports their interconnected journeys. It's about delivering information, support, and services when and where they are most relevant, enhancing patient enrollment, adherence, driving proactive healthcare decisions, and fostering stronger provider-patient relationships.

Navigating the Complexities of Omnichannel Personalization in Healthcare

However, achieving omnichannel personalization in healthcare is a multifaceted endeavor. Each stakeholder—pharmaceutical companies, healthcare providers, health insurance companies, and pharmacies—has unique objectives, regulations, and challenges. Integrating their efforts into a cohesive omnichannel strategy requires a delicate balance of data integration, compliance considerations, and patient privacy protection.

Marketing agencies of record(AOR) and specialized niche management consulting companies, like Axtria or, become pivotal in this intricate landscape. These agencies and management consultants understand the nuances of each Life Sciences stakeholder and possess the expertise to navigate the complex regulatory environment. They bridge the gap between pharmaceutical companies and healthcare providers, ensuring that personalized messages, educational content, and service offerings align seamlessly. It is a never-ending journey of complexity and coordination - not unlike a symphony.

With advanced technologies like AI-driven profile personalization, ML insights, and predictive analytics, marketing agencies and specialized consultants empower these industries to deliver tailored experiences that enhance patient outcomes, streamline operations, and foster collaboration. The goal is to create a good user profile for the marketing initiatives and use them within personalized driven strategies for a broad-based entire customer universe campaign to 1:1 single-profile conversion optimization. I created an illustration here on the right side of the first diagram. The image is a generic example - the Life/Health Sciences company would need to undergo a rigorous persona development process to build a suitable data model for their situation and transformation.

Non-vendor specific - Generic single profile view in a CDP - No pseudonymization

Luckily, Adobe, Microsoft, and Salesforce have already done much of the groundwork for the data model for the Life Science and Healthcare industry - and the cool thing is that they are Open Source for the most part. The Adobe data model is a set of pre-configured attributes to define the Member profile - the primary entity in the case of the organization. They have also pre-configured a set of defined time-series attributes to hold the historical event behavior. You will see another diagram below in the article that illustrates your profile parts. This data drives the personalization efforts described in the Part 1 article and above in this article. Besides the examples illustrated below, there are many other examples of a common data model for Healthcare, Life Sciences, and many other industries.

Name Schema details
Healthcare industry data model ERD
Healthcare Member Details schema field group
Healthcare Plan Details schema field group
Healthcare Provider schema field group
Github - Various Industry verticals
Microsoft Cloud for Healthcare entities
Salesforce Health Cloud Data Model

The Complexity of Omnichannel Personalization in Life Sciences and Healthcare

Navigating Diverse Channels with Precision

Omnichannel marketing within life sciences and healthcare involve a strategic dance across diverse channels—digital ads, social media, healthcare provider portals, patient apps, and more. Each channel serves as a unique touchpoint, a potential avenue to engage and inform. However, the challenge lies in orchestrating these touchpoints into a harmonious symphony that resonates with patients, providers, and other stakeholders.

Unlike multi-channel marketing, where each channel can operate relatively independently, the omnichannel approach seeks to deliver consistent and contextual experiences. The updated method requires understanding not only the preferences of patients but also the behaviors and objectives of healthcare providers, pharmacists, and insurance members and the content delivered to them. For instance, a pharmaceutical company may want to communicate the benefits of a new drug to healthcare providers through medical journals while also providing concise and informative summaries to patients through their apps. To provide the content, the organization needs content standardization. This new standardization means a type of content factory and storage of content fragments that personalization delivery mechanisms can access and assemble in real-time.

Understanding the profile unification process and content manufacturing process is essential. While the profile is stored and managed in an EDM/CDP platform, the content needs something similar with the same rules, governance, and privacy applied - and accessible by all the downstream delivery tools, agencies, and solutions used for syndication to the user for their journey. Typically this means deploying a transformation initiative across CMS and DAM systems into a centralized platform tied closely to the downstream personalization tools mentioned above. The below diagram illustrates one approach to this, unifying the profile to the content in a real-time omnichannel process and optimizing the content to the conversion goal based on the point in the journey. The step is a 1:1 real-time late-stage part of the journey and is user-event driven within a mobile app. The same profile and content could be referenced by another personalization engine on a website - the only addition would be the profile events are updated in real-time, so if the next visit is to the website, the personalization engine will have this information to make the right decision of what content to serve up - because it will know what content was served last on the mobile app seen below. The example below is how a tool like Algonomy(AKA RichRelevance) works in this context. While they specialize in specialty retail - the concept is the same across all industries.

Algonomy's Omnichannel Personalization engine for 1:1 conversion optimization. Most Personalization engines work like this illustration or can be configured to do it.

The Conundrum of True Personalization

Achieving true personalization in an omnichannel environment presents a complex puzzle. As you see above in the diagram, we only look at one stage - the later stage in the journey at one point in time. The challenge lies in data fragmentation, each channel's varying contexts, and the inherent silos of the delivery tools not being fully connected. A patient's behavior on a healthcare provider's portal may not seamlessly correlate with interactions on a patient app. Each channel(Website and App) may have two separate personalization engines and CMS systems delivering content for the same profile but never simultaneously. Such disjunctions can lead to disjointed experiences that fall short of true personalization. This aspect is where things start to fall apart and revert to the older, less mature multi-channel approach. The goal is to consolidate and transform systems centrally further back in the process that can integrate better into the downstream disparate systems without entirely disrupting and causing costly delays for go-to-market products and initiatives. Basically, you are centralizing and unifying the profile from many different source systems and their related behavior events and consolidating content fragments used vertically within all channels. The idea, then, is a centralized dual-platform system of profile data unification and Content centralization - governed, regulated, and syndicated downstream on an as-needed initiative basis to the marketing AOR (Agency of Record) or teams of staff and consultants driving the go-to-markets.

Moreover, privacy concerns and regulations add another layer of complexity. In the healthcare and life sciences, safeguarding patient data is not just a priority—it's a legal mandate. Striking a balance between delivering personalized experiences and respecting patient privacy requires a sophisticated approach, often involving pseudonymization techniques, strict data access controls, and robust encryption protocols.

Strategies to Mitigate Profile Fragmentation

While content unification is mentioned often in the discussion above, the article will discuss content only a little. Content as a topic of technology, process, and people is a separate article and, mostly, a separate set of technologies. While part of omnichannel, it does require more depth and explanation. However, the article will discuss the profile; in the intricate landscape of life sciences and healthcare, where patient well-being is at the forefront, strategies that mitigate profile fragmentation and enhance personalization become paramount. One essential approach is the creation of unified patient profiles. Integrating data from disparate channels into a comprehensive profile allows healthcare providers and insurers to understand each patient's journey better. The unified profile enables more personalized interactions and accurate predictive analytics, enabling proactive interventions and tailored recommendations. One vendor we mentioned above and in other articles is Adobe. Their AEP (Adobe Experience Platform) set of tools helps with profile fragmentation through their data management data set/data lake architecture - the AEP is a mini EDM(Enterprise data management platform) that ties together many other tools and capabilities as needed. You can read about how they bring the profile fragments across different data sources together here: Adobe Primary/Profile Entity Record . Other vendors with excellent Identity Resolution and profile unification capabilities are Amperity, Algonomy, Nuestar(now Trans Union), and Liveramp.

Others are on this list, but be careful and wary of vendors claiming this capability. Many claim they can do it well, but in reality, they have not kept pace and, in fact, could undermine nearly the entire approach. I plan to write more about Identity Resolution and Profile Unification details in other articles, so stay tuned. The article touches a bit on Identity resolution attributes for omnichannel purposes.

Adobe AEP Primary/Profile Entity and Dimension (Event) Entity records

Furthermore, leveraging advanced analytics and machine learning becomes essential in this process. Adobe lets other vendors integrate via their API-first architecture, or you can use their set of tools embedded with the Adobe platform. These technologies can sift through vast datasets, identifying patterns and correlations that human analysis might miss. By understanding these insights, Life Sciences companies can tailor their messaging to healthcare providers and craft content that resonates with patients based on their past interactions and preferences.

In collaboration with marketing agencies of record(AORs), or specialized consulting agencies, like Axtria or, industry players can strategize around omnichannel personalization with a keen eye on delivering relevant content at the right time. These agencies and consulting specialists can navigate the intricacies of each stakeholder's needs and objectives, curating messages that align with the journey of patients and providers alike. The art lies in weaving these messages into a cohesive narrative that enhances patient adherence, improves health outcomes, and builds trust in the healthcare ecosystem.

As we mentioned above, the complexities of omnichannel personalization in Life Sciences and Healthcare are complex; like any other industry, it's clear that the fusion of technology, data insights, and human understanding illuminates the path to success. In the forthcoming Part 3 of this article series, we will explore specific lists of personalization strategies, personalization tactics, and best practices that empower you to conquer the challenges of omnichannel personalization, turning the vision of seamless and tailored experiences into a tangible reality.

I hope you got some nuggets of value from this article, and stay tuned for Part 3, where I will give you some actionable lists to use in evaluations and deployments.

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