The global pandemic has indelibly impacted every area of the lives of each person on this planet. It has also epitomized the profound difference between driving awareness versus driving behavior change.
It is never enough to simply make people acknowledge the existence of a problem. You must make people do something about it. As such, marketing plans will fail when they do not move the needle.
This new reality in which we live has crystallized the importance of adaptability, efficiency, and action-oriented communications. The only way to change clinician behavior is through marketing solutions that are informed by data-driven insights.
Drive Diffusion of Innovation by Leveraging AI-Based Data Analytics
The best way to optimize marketing plans is to minimize the unknowns. The healthcare market is unpredictable, which is why we must embrace that which we can control. Advanced network mapping analytics are critical to meeting this objective, as they can uncover the clinicians who can measurably change the behavior of others in their network.
These insights not only bolster your ability to connect with key targets, but they also inform marketing communications that will actualize desired clinical behavior change and ultimately evolve patient care. In a study quantifying the impact of peer influence in the context of treatment choices by clinicians, it was shown that the recommendation of an influential peer is more than 100 times greater than the impact of sales rep interactions with clinicians.
Once you have modeled a network, you can explore many other factors, such as how easily or quickly information flows through it, or how amenable or resistant to change a specific target may be. For example, we apply our proprietary network mapping analytics that use the following approach:
- Using disease-specific healthcare claims data, you can analyze every interaction the patient has during his or her journey.
- Connections among clinicians are identified, and the relative impact of the most influential clinicians on the behavior of peers within their network is quantified.
- The most influential clinicians within a network are leveraged to achieve the desired clinical behavior change among high-value targets.
The following case studies demonstrate the difference AI-driven analytics can make.
Case Study: Reach Targets More Efficiently to Catalyze Brand Growth
In a time when virtual interaction is essential, adaptability is, too. The pandemic is a testament to the fact that despite our best-laid plans, anything can happen, and there will always be an unforeseen rate-limiting factor that can change the course of a business. How do we mitigate this? The application of data-driven insights can allow us to cut through static noise as efficiently as possible.
A good marketing plan accounts for change, but an exceptional marketing plan engenders change. In this case study, we demonstrate how leveraging regional clinical leaders accelerated growth in a competitive market by addressing the challenge of most efficiently driving behavior change among key targets.
Market: Oncology
Situation:
A marketed oncology product, which requires biomarker testing, is experiencing eroding market share due to strong uptake and noise level of competitors.
Key Questions:
- How do we reach our targets more effectively?
- How should we effectively segment messaging to increase impact?
- What untapped opportunities exist in the market?
Challenge:
The product’s success hinged on the ability to identify what untapped opportunities existed in the market, and—more importantly—how we could quickly deliver messaging to increase market share.
Maximizing impact is a function of being able to use the ever-evolving healthcare landscape to our advantage, rather than seeing it as a hurdle. By using data analytics, we can tease out specific areas in the market that pose the most opportunities for a brand.
Solution:
Analysis of the situation started by applying proprietary machine learning and claims analytics to deconstruct the patient journey and identify potential levers that can be applied to dismantle clinical inertia and facilitate change in existing behavior to support the brand’s marketing strategy. The output of these analytics provided insights that drove the development of customized messaging for each target segment.
In addition to patient-journey mapping, we applied machine learning and network mapping to identify new key customers, including high-priority, high-impact targets with expansive clinical networks. We matched clinicians with clinical leaders in their networks who had demonstrated the ability to change the prescribing habits of others in their network. These clinicians became the messaging communication conduit for the rest of the network, which supported optimization of an omnichannel campaign. By focusing our communications on these clinicians, we were able to leverage market dynamics that could have otherwise stifled product uptake.
In fact, selectively targeting clinicians who influenced the behavior of others in their networks informed message dissemination as well as the development of segment-specific messaging designed to effect a change in behavior.
Results:
The commercial success of this targeted approach led to accelerating annual product sales growth to more than 30%, which was maintained every year since.
Case Study: Dissect the Clinical Journey to Maximize Launch Success
In this industry, it is not about what you know—it is about what you understand. You need to understand how the precise clinical journey defines your brand’s patient-clinician dynamic. And, you need to understand how to reconcile those insights with your resources, especially when preparing for a launch.
Two-thirds of drug launches fail to meet sales expectations, and those that fall short usually continue to underperform over the next two years. With the stakes this high, leave as little to chance as possible. This case study takes a closer look at a successful launch plan that demonstrates how data-driven clinical journey analytics can yield powerful insights, informing market strategies to ultimately change clinician behavior.
Market: Neurology
Situation:
A mid-size biopharmaceutical company was launching a biologic with a novel mechanism of action into a mature market. The company had limited experience and no established footprint in the space, with a lack of understanding of treatment dynamics. Additionally, there was potential for significant payer restrictions.
Key Question:
What are key points along the clinical journey to engage with HCPs to maximize product uptake?
Challenge:
This product faced the challenge of entering a highly competitive, largely genericized market, with established treatment dynamics and payer restrictions. Rapid adoption at launch by the most influential treaters—those who can measurably change the behavior of others in their network—was essential to commercial success.
Solution:
Our approach was guided by the question “How does the clinical journey inform future product uptake?” To address this key business issue, we analyzed anonymous patient-level data to discover the most relevant cohort of patients and assess the diagnostic process and therapeutic intervention over the course of two years. Using analytics, we were able to track patient visits to various specialists during this time period and quantify the rates of treatment retention, switch, and abandonment.
While primary market research provides depth on patient experience, it does not often capture the intricacies and extent of the diagnostic and treatment journey. After individual patient data were aggregated to summarize treatment protocols, claims-based predictive analytics allowed us to recreate the reality of the journey and predict the treatment decision-making points offering the greatest opportunities for our client’s brand.
Analytics further enriched this knowledge through detailed thought leader profiles and mapping, enterprise-wide activity tracking, and industry relationship assessment. The culmination of these insights informed the development of a targeted and effective engagement planning strategy that propelled product uptake.
Results:
Predictive analytics fueled by real-world data revealed previously unknown patient and HCP behaviors. Uncovering these treatment patterns informed the creation of a successful launch strategy that drove rapid product uptake well beyond forecast.
The Ability to Adapt to Any Situation
Today, it is COVID-19 challenging us to adapt, but there will always be rate-limiting factors, mitigating circumstances, and unavoidable obstructions.
The only way to successfully combat the certainty of uncertainty, and the impositions therein, is through applying analytics-driven insights that can ensure nimble adaptability, informed perspectives, and targeted communications. Incorporating these principles into a biopharmaceutical marketing plan is paramount to changing clinical behavior and maximizing the commercial potential of a brand.
The healthcare landscape is variable, but data give us more control. It will never be enough to drive awareness. Results are a function of change. Success is defined by results. And, in these changing times, it is time to drive change.
