Introduction

By leveraging advanced algorithms and machine learning, pharmaceutical companies can create personalized promotional content designed to resonate with healthcare professionals (HCPs) and patients, ultimately driving better engagement and prescription rates.

According to a recent study, only 35% of HCPs feel that pharmaceutical companies' customer-facing resources effectively meet their needs. Additionally, 80% of life science executives report that their omnichannel efforts have had little to no impact on customer engagement. However, with the implementation of generative AI (genAI), companies may be able to bridge this gap and create more effective promotional strategies.

A key thrust involves customizing the content supply chain.

"By helping our clients understand their customers better,” noted David Laros, Partner, Beghou Consulting, “then together we can take that understanding of the customer to make engagement not just more frequent, but better and more curated."

Laros described how one pharmaceutical client successfully harnessed the power of generative AI to transform its approach to customized promotion. By deploying content tagging and machine learning algorithms, the company increased its tagging by 60-fold and achieved a 94% accuracy rate in its models.

This enabled the manufacturer to better understand customer preferences and create more targeted marketing content, resulting in a three-fold increase in acceptance of alerts and suggestions. As the company continues its journey, it aims to achieve a 60% increase in engagement and a 3%-6% lift in prescription rates, Laros reported.

Cross-functional collaboration—including among the sales, marketing and analytics teams—was key to the drugmaker’s ability to create a cohesive and effective promotional strategy.

"It's incredibly important to keep the end user in mind, to collaborate, bring them up-front," Laros explained. "It's people, process and technology.”

This approach has not only improved content management and personalization but also resulted in significant cost savings, he added. Moreover, genAI has also enabled the company to map its key messages to its collateral, identifying mismatches and areas for improvement. By leveraging large language models (LLMs) and large reasoning models (LRMs), clients can understand the prominence and frequency of their messages, allowing for more targeted and effective communication.

As Laros noted, "We took the data, cleaned it and did prompt-sharing to build confidence through an LLM. That allowed us to understand which of their messages are in each one of the collateral pieces within their content blocks."

This case study demonstrates how prioritizing customer-centricity, collaboration and data-driven decision-making can help companies unlock the full potential of AI and optimize their pharma marketing activities.

Key takeaways:

1. GenAI can enhance pharmaceutical marketing: By leveraging advanced technologies, companies can create personalized promotional content that drives engagement and improved health outcomes.
2. Understanding customer preferences is critical: Companies must prioritize customer-centricity and create targeted content that meets the needs of HCPs and patients.
3. Collaboration is key: Cross-functional teams—including sales, marketing and analytics—must work together to create effective marketing strategies.
4. GenAI can drive significant cost savings: By improving content management and personalization, companies can reduce costs and improve efficiency.
5. Measuring success is essential: Companies must track and measure the effectiveness of their promotional strategies, using data and analytics to inform future decisions.

" By helping our clients understand their customers better,” noted David Laros, Partner, Beghou Consulting, “then together we can take that understanding of the customer to make engagement not just more frequent, but better and more curated."

This approach has not only improved content management and personalization but also resulted in significant cost savings.

The use of generative AI has also enabled the company to map its key messages to its collateral, identifying mismatches and areas for improvement. By leveraging large language models and large reasoning models, they can understand the prominence and frequency of its messages, allowing for more targeted and effective communication. Laros noted, "We took the data, we cleaned it... we did prompt sharing to build confidence through a large language model... and that allowed us to understand which of their messages are in each one of the pieces, the collaterals within their content blocks."

By prioritizing customer-centricity, collaboration, and data-driven decision-making, companies can unlock the full potential of this technology and achieve greater success in the market.

Key takeaways:

1) Generative AI is transforming the pharmaceutical industry: By leveraging advanced technologies, companies can create personalized promotional content that drives engagement and improved health outcomes.

2) Understanding customer preferences is critical: Companies must prioritize customer-centricity and create targeted content that meets the needs of HCPs and patients.

3) Collaboration is key: Cross-functional teams, including sales, marketing, and analytics, must work together to create effective promotional strategies.

4) Generative AI can drive significant cost savings: By improving content management and personalization, companies can reduce costs and improve efficiency.

5) Measuring success is essential: Companies must track and measure the effectiveness of their promotional strategies, using data and analytics to inform future decisions.

"Medical and commercial will always have their separate roles. They will always be distinct in what they need to do. But there is no reason why you cannot have a single objective or single set of objectives what you're trying to accomplish,"

she explains.

The solution isn't about breaking down regulatory boundaries but aligning on common goals: "If you can align on the goal, it's not about the activities, it's not about the details of the road, it's about, are you trying to move in the same direction?"

Fostering Innovation Through the 90/10 Rule

To drive meaningful innovation, Gopal advocates for the "90/10 rule"—dedicating 90% of resources to essential activities while reserving 10% for creative exploration. She cites Google's approach of allowing employees to spend 20% of their time on creative projects, which led to innovations like Gmail and Google News.

However, she cautions that once an innovation shows promise, it requires full commitment: "They cannot be side projects once you choose to do something with them. If you decide you're going to do something coming out of that 10%, you have to be all in."

Implementing Change

Gopal outlines three key principles for implementing change:

1. Establish clear objectives and stay committed: "Pick a lane, get alignment and stay committed. You cannot have a different plan every six months."

2. Involve the right stakeholders early: "Get the right people around the table to say, okay, this is the idea. How are we going to make this happen? Not do I have permission to make it happen."

3. Proceed with determination: "You have to be enthusiastic when you're trying to make change. You have to believe and you have to commit. And you can't back down."

"Agility in pharma is not a contradiction. It is absolutely possible," Gopal concludes. "We are nimble when we need to be. How are we going to be nimble when we want to be?"

Key Takeaways

1) Shift from reactive to proactive change: "Imagine if you could turn that around and make it about, I see a need, I see an opportunity, and I want to change something. That's what creates agility."

2) Align medical and commercial objectives: "If you can align on the goal, it's not about the activities, it's not about the details of the road, it's about, are you trying to move in the same direction?"

3) Implement the 90/10 rule for innovation: "Let's dedicate 90% of our budget to things that need to happen... But let's leave 10% to think about things that we normally wouldn't think about."

4) Prepare concrete action plans, not just scenarios: "Being competitive means preparing for the pivot and having a plan in place that we can use immediately."

5) Learn from cross-industry approaches: "We need to be curious. I learn a lot from other industries. I don't think any industry is better or worse at moving with speed than pharma is."

"That's one of my big missions in my team – that people are getting a flavor and a taste of all of the different components of this ecosystem between the data, the digital and the operations,"

she says. "The more we are thinking of that holistically across this whole area, the better off we're going to be anticipating and seeing around corners."

Key Takeaways

1) Start with the customer experience: "A big part of it is really starting with our customer as the first point. How do we think about that person's experience? The things that are making them frustrated or standing in their way."

2) Embrace difficult change management: "Standing true to the notion that ultimately, on the other side of those tough decisions, there's a better future for the organization and maybe even for those individuals who are impacted."

3) Adapt to the digital-native clinician: "Our clinicians are changing and that inherently means that the way we engage with those clinicians has to evolve with them."

4) Maximize each interaction: "The number of times we get in front of these clinicians nowadays is going to be a lot fewer per time period, so each one of those conversations needs to be that much better and that much more planned out."

5) Foster cross-functional thinking: "I want the entire team to be thinking about data, thinking about digital and thinking about operations, regardless of which place you are in your function."

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