Delivering Brand Relevancy through Connected Data and Analytics

Mari, a 45-year-old woman who has just begun her treatment for diabetes, receives an invitation to a patient support group as well as meal planning tools. Ralph, who has been on his medication for nearly a year, gets information about a program that could lower his out-of-pocket costs. And Aarav, who is concerned that his therapies may no longer be working effectively, is offered a symptom tracker and compliance tips.

These are examples of empathetic and meaningful brand engagement that pharmaceutical leaders strive to deliver to customers throughout their patient journey. But what customers often receive instead are disconnected, one-off interactions that don’t meet their specific needs, and don’t promote long-term relationships or ongoing dialogues with their pharmaceutical providers.

In this article, we’ll explore how a large, global biopharma company is leveraging a data-linking strategy to power insight-generation tools and techniques—and supporting customers through their journey with dynamic personalization and modular content. We’ll also show how this approach to data enables deeper marketing effectiveness measurement and optimization, all while promoting transparency and preserving customer trust.

Customer dialogue depends on data

Pharmaceutical brand leaders are driven to save and improve lives. But to do that, they need to ensure that the right information gets to the right people, on the right channel, at the right time. And that requires being able to answer a series of critical questions about how and where to spend their marketing budgets, including:

Answering these questions can prove thorny because the omni-channel ecosystem is often disconnected and episodic, giving marketing leaders limited visibility into what’s working, what’s not, and how to adjust. Key limitations include:

These process limitations can create an inconsistent or irrelevant customer experience for patients and health care providers alike, leading to a low return on marketing spend.

Data linking powers insight and personalization

To overcome these challenges and better support customers, a large, global biopharma company is working with Deloitte Consulting LLP to implement a data strategy that enables the company’s team to work across customer types in four key areas: insight generation, measurement, optimization, and content personalization.

With this strategy, the company can pinpoint the tactics that motivate patients to engage in their health care at different points in the customer journey. The company’s data strategy is:

Built on linked data: The company is connecting previously siloed data sets and reporting efforts to harmonize the data and extract the maximum value.

Powered by analytics and AI: The strategy features an integrated suite of marketing modules built off campaign, behavioral, and medical data—all connected in a privacy-safe manner. By applying AI-driven data segmentation and messaging, and by connecting insights and actions across channel teams and business units, the company can model and optimize marketing tactics in real time. This enables greater flexibility and connection through the full customer journey.

Based on digital and offline tactics: Advanced data and feature engineering provides a holistic view of the customer journey. This allows for the accurate assignment of attribution, where attribution is due.

Adapted to a highly emotional and complex environment: The strategy is tailor-made for the pharmaceutical customer journey, which is marked by numerous decision points and guided by multiple influencers.

Using this strategy, the company can see how marketing budgets are performing and gain a deeper understanding of patient- and HCP-level impact, driven by media campaigns. Marketing teams can identify new opportunities, personalize content to each customer’s journey, and develop new insights and modeling to improve customer targeting and experiences. Most importantly, the company can better understand the latent drivers of customer behavior to deliver the information customers need to manage their health—all while preserving transparency and trust.

How It Works

Customer data is the foundation upon which personalized brand experiences are built. As customer experience becomes the new battleground for customer loyalty and competitive advantage, the company recognizes that first-party customer data is a critical business asset—one that must be owned and protected in-house.

With this data strategy, the company can integrate clinical and campaign data to optimize brand spend and support the customer journey—from risk identification and diagnosis through treatment and disease management.

Here’s how it works (Figure 1):

Data inputs: As patients and HCPs interact with ads and other forms of marketing across their customer journey, discrete data points are combined with other information, and stored in a central analytics sandbox.

Identity resolution: A patient’s clinical and socioeconomic data from their claims is married to their interaction data, through a HIPPA- complaint de-identified service, to create a holistic customer profile.

AI processing: The de-identified and consolidated data is analyzed using a variety of AI tools to uncover new insights.

Outputs: Insights and recommendations across three categories—marketing mix, patient engagement, and HCP engagement—are generated to inform messaging, content, and channel recommendations.

(Click on figure to enlarge).

Preserving privacy, promoting trust

As first-party data proliferates, customer journeys must be founded on trust, privacy, and the ethical management of this data. Using a customer-first approach, the company’s data strategy was built with key privacy principles and consent-driven processing at its core, including:

Consent and preference management: Obtaining customer consent and preferences, maintained centrally and provisioned to downstream systems.

Individual rights: Enabling customer rights to data access, erasure, restriction and portability.

Identity-based tracking: Tagging customer-based choices and requests to their identity and honoring these choices in marketing campaigns.

Data cataloguing: Maintaining a real-time data catalogue to facilitate holistic management of individual rights, consent, preferences, and data processing.

By embedding privacy—and providing the control and transparency that customers expect and deserve—the company’s data strategy is designed to promote a trust-based customer journey while inspiring brand confidence.

Sophisticated solution, real results

The company is in the process of integrating the new data strategy with its MarTech stack, and the early results are extremely promising. With the solution, the company plans to:

With new insights in hand, the company can re-allocate budget to the best performing tactics and placements—and explore messaging and content optimization to enhance the customer experience. And that will boost the company’s ability to support customers like Mari, Ralph, and Aarav, the people mentioned at the outset of this article, with the information they need to manage their health and live long, productive lives.