Leading companies move beyond conventional field planning and embrace dynamic targeting and predictive next-best actions to forge more meaningful relationships with high-value HCPs. However, their shared goal of better HCP engagement still faces familiar challenges hindering next-generation targeting.
The complexity of data availability, varying levels of digital maturity across organizations, and the ever-present impact of regional nuances are challenges to achieving true HCP and patient centricity. The contrast is evident. The U.S. generally has more accessible and granular data sources, while Europe has restrictive data privacy and fragmented data landscape.
GenAI use cases factor heavily into evolving data-driven segmentation and targeting strategies. Yet, pharma companies need to prioritize building an accurate and harmonized customer data foundation to fully benefit from AI鈥檚 potential. As shared by the head of omnichannel engagement strategy at a leading biopharma, 鈥淎I engines complement customer targeting processes, not replace them. Our solid foundation with the right tools and data is what drives our success.鈥�
Her insight comes from Veeva’s latest research, which highlights a critical shift occurring among biopharma as they unlock the power of data-driven optimization. By incorporating historical HCP activity data and predictive next-best-action models, biopharmas are moving beyond basic sales performance measurement. This enhanced approach is fueling more agile and effective multichannel engagement planning, paving the way for field strategies with far greater impact.
Despite sophisticated AI and machine learning models that enable data-driven dynamic targeting, biopharma shouldn鈥檛 overlook the vital role of field knowledge in achieving successful engagement planning and execution. 鈥淕iving our reps a voice to share HCPs鈥� engagement preferences is key to improving our targeting process. Our reps can bring their field knowledge to the table to choose the most optimal channel mix for every HCP,鈥� the head of omnichannel engagement says.
The accompanying diagram breaks down Veeva鈥檚 findings of the primary approaches across EU and global biopharma companies. The X-axis shows the increasing maturity of engagement planning from flexible to granular, and the Y-axis represents the segments of data analytics from descriptive to prescriptive.
- Legacy approach: 40% of companies rely on rep-driven HCP profiling, collected yearly or semi-annually. This method, prevalent in organizations with less granular data sets, leans heavily on the established knowledge of brand and sales teams. While familiar, it is seen as lagging in today’s data-rich environment.
- Channel-agnostic model: 10% embrace channel-agnostic engagement planning at the HCP level. This data-driven approach sets total HCP touchpoints based on segmentation and history. It empowers reps to choose the best channel mix beyond face-to-face, including virtual interactions, emails, events, and more. This is especially important in regions with restricted access. Reps target an overall engagement score with AI providing execution guidance.
- Face-to-face stalwarts: 30%remain dedicated to in-person-only targeting, basing their plans on rep-driven profiling and sales/market research. This traditional, static approach is less agile but holds sway for a significant industry segment.
- Multichannel emergence: 10%are moving toward more granular targeting, combining sales/market performance data, rep profiling, and HCP historical data. This strategy leverages multichannel cycle planning with specific goals by HCP per channel. It is gaining traction among larger pharmaceutical companies.
- Data-driven frontier: 10% of companies integrate comprehensive data sets 鈥� including HCP profiling, sales performance, and historical data 鈥� to drive agile, multichannel engagement planning. AI-generated next-best actions help guide execution and even granular activities like HCP interaction sequencing.
The data reveals a transition. While legacy methods persist, the industry is increasingly adopting data-driven, agile approaches. With its flexibility and responsiveness to regional challenges, the channel-agnostic model is gaining momentum. However, the most advanced companies are pioneering a future where data and AI drive highly personalized and optimized engagement. The following steps offer a starting point for achieving next-generation HCP engagement.
- Conduct a comprehensive assessment: Rigorously evaluate current field deployment and HCP targeting strategies, capabilities, and systems. Identify gaps and opportunities to build agile sales teams that can move rapidly in response to business and market changes.
- Empower reps with local intelligence: Leverage field force intelligence and local knowledge to transition to customer-centric field deployments. Foster collaborative relationships with field reps, enabling them to adapt strategies to nuanced local market dynamics.
- Implement agile, integrated systems: Replace static cycle planning with dynamic, multichannel engagement that leverages GenAI. Deploy integrated systems that deliver real-time insights and high-value actions beyond the traditional call plan, allowing reps to respond proactively to customer needs.
- Prioritize continuous learning and adaptation: Create a culture of continuous learning and adaptation. Regularly review and refine deployment and engagement strategies based on performance data and evolving customer needs.
These strategic investments help biopharma move beyond transactional international and maximize the power of data to forge meaningful HCP engagement and ultimately drive better patient outcomes.
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Written by Bilyana Hristova, Director of Commercial Strategy, Align and Align+ in Europe at Veeva Systems.
