Knowing Your Audience: Predicting HCP Digital Behavior to Drive Sophisticated Identification and Targeting

2 Dec 2021
Knowing Your Audience: Predicting HCP Digital Behavior to Drive Sophisticated Identification and Targeting

For a company to be resilient and drive growth, it needs to be more innovative than simply providing a product or a service. The journey starts with identifying the right customer base and providing a seamless experience based on customer preferences. Thus, understanding your audience is key to enable impactful customer experiences. McKinsey research shows that companies that leverage behavioral insights outperform their peers in sales growth by 85%.

Netflix, a well-known innovator in creating customer-centric experiences has leveraged technology to capture and analyze data at an unprecedented scale. A customer-centric data strategy has enabled Netflix to create user personas that help them target and engage like-minded or similar audiences. Once a user is on the platform, based on their interests and interactions, Netflix dynamically recommends relevant, personalized content. Users get to view unique, personalized homepages and content with relevant artwork that best match the user’s interests to maximize their time on the platform. Netflix then uses the user-generated insights captured on the platform to further strengthen segmentation and targeting to drive similar audiences or even uncover new audiences to the platform. Companies such as Airbnb and Uber compile data by combining both online and offline initiatives that help to deliver an emotional connection between their brands and customers and have kept their customers asking for more suggestions.

Pharma and customer data: Beginnings 

The pharmaceutical industry is no stranger to data or analytics; the industry has long used data (mostly offline) to target the right customers. The number of prescriptions written by a healthcare practitioner (HCP) was the foundation for targeting and segmentation. For more prescriptions the HCP wrote, the sales representative would prioritize them based on the volume of prescriptions the HCPs write. Pharmaceutical companies then deployed advanced algorithms to allocate optimum sales representatives to cover territories with doctors driving high prescription volumes. But face-to-face (F2F) interactions lacked the mechanisms and depth of data capturing that, in contrast, digital can offer. Even though HCPs used digital to a certain extent to get relevant information, the adoption rates were very low.

COVID accelerates much needed digital adoption in pharma 

Fast track to 2021, 70%1 of HCPs are digital natives, while restrictions imposed during COVID-19 led to a sharp decline in F2F interactions between pharma field representatives and HCPs. The pharmaceutical industry, like all other businesses, were forced to rely on digital and virtual channels for their promotions.

The creation of digital content increased by four times in 2020 as compared with 2019. Representative-sent emails saw a 7-fold increase and the number of virtual meetings showed more than 8-fold increase. The average call duration increased to 18 minutes as compared with 3 minutes during in-person interactions2. With delivery models changing rapidly, practitioners seem to have adopted digital interactions. Thus, the effectiveness of hybrid digital and virtual interactions is high for these digital natives. This trend is expected to continue after the crisis as both pharmaceutical companies and HCPs have now experienced the true potential (and limitations) of digital technologies.

What can pharma do with customer data? 

With digital channel adoption rates growing rapidly, pharmaceutical companies have access to data that is growing at an exponential rate. With data, they can identify what type of content works well for each of the personas, including preferred channels, time and day they are most likely to be engaged, key interest areas, social media activity, and so on, which is similar to other industries. Marketers now can measure how likely they would respond positively to digital and virtual promotions, also known as Digital Affinity, and Promotional Sensitivity, which is the likelihood that those interactions drive prescriptions. Both metrics consider multiple factors and narrow it down to a single number that becomes easier to implement. Marketers now can identify digital-savvy HCPs vs. HCPs who prefer more personal interactions, or a mix of both. In addition, conventional attributes such as market potential (Rx potential) can further enhance the selection and prioritization of the target universe.

The table below shows different personas created by Indegene that identify various behavioral traits, preferences, and the best digital channels that can be implemented to drive maximum conversions.

The predictive scoring approaches leverage machine learning techniques to predict key HCP behavioral characteristics, like their content and channel preferences, as well as their probability of prescribing a certain type of treatment. One can also score on the probability of early adoption for a new type of treatment or preference for branded versus generic drugs. They provide a powerful mechanism to profile HCPs across multiple behavioral dimensions and understand the key drivers of their preferences. These algorithms rely on feature-rich, streaming big data sets, for example, closed-loop marketing activity, sales data, anonymized patient-level data and demographics information to provide analytically robust insights and recommendations.

Figure: Indegene’s Smart HCP: 1.8 million persona data captured at an HCP level

The predictive scoring models thus help create derived variables, which can be used for defining multidimensional customer personas used for smarter targeting and prioritization of your brand’s sales and marketing efforts. These multidimensional personas also help personalize the sales and marketing strategy to your customers, resulting in better customer experience and overall engagement levels.

 

Investments in data-driven predictive models play a crucial role in driving these attributes. Research showed advanced analytics deployed across the life cycle could improve EBITDA for pharmaceutical companies by 45%–75%3. Building a comprehensive predictive scoring strategy for your HCP target universe will require a well-thought-out measurement strategy, including data sourcing, data ingestion and transformation, and advanced analytics to support your company’s sales and marketing strategy. Executed the right way, this strategy can be scaled across all your brands and therapy areas and become a long-term competitive advantage for your sales and marketing teams.

References: 

Using advanced digital capabilities to unlock hard-to-see HCPs access | Pharmafile 

The New Era of HCP Engagement: What’s Next on the Path to Digital Excellence | Pharmexec 

How pharma can accelerate business impact from advanced analytics | McKinsey 

4  Veeva Pulse Trends, Global Market, October 2020