By: Kent Groves, PhD, Global Head of Strategy, 兔子先生 health
The pressure to innovate and deliver personalized experiences in healthcare and life sciences is greater than ever. While consumers desire more human interaction in certain aspects of their healthcare journey, they also expect digital convenience in others.
As we've discussed in previous articles, organizing healthcare data and implementing the right customer relationship management (CRM) system are foundational steps toward driving an effective customer experience to meet this demand. But the true measure of success lies in the business impact generated by these efforts. This impact transcends patient or healthcare provider (HCP) engagement and involves achieving measurable outcomes that work toward broader organizational goals, such as market share growth, client retention, therapeutic impact and ROI.
While this accurately describes the destination, the reality is that the path to impactful data-driven strategy is far from straightforward. Healthcare organizations often find themselves entangled in a web of conflicting priorities, competing stakeholder interests, and an overwhelming array of metrics. To cut through the noise and focus on what truly matters, it's essential to anchor your data strategy in business impact. Here’s how to figure out what that “impact” means for you.
Prioritize the KPIs that matter
The first step in driving business impact is identifying the right key performance indicators (KPIs). Focusing on too many metrics can dilute your attention and make it harder to identify what activities are truly driving success, namely, concentration on KPIs that directly align with your organizational goals. This targeted approach will help you track the factors that truly matter. For example, if patient retention is a critical goal, focus on metrics like patient satisfaction scores, patient reported outcomes (PRO), adherence, propensity, and patient lifetime value. For market share growth, you might emphasize lead generation, conversion rates, competitive benchmarking and NBRx, NRx, and TRx metrics (new prescriptions, renewed prescriptions and total prescriptions).
It's also important to consider your KPIs relative to the brand’s product lifecycle position, and to periodically reassess your KPIs to ensure they’re still relevant. The health and life sciences landscape is dynamic and as your strategy evolves, so should the metrics you use to measure success.
Leverage the right tools for measurement
With your KPIs framework established, the next step is to harness the right tools and platforms to track, measure, and optimize these metrics. A sophisticated CRM system, which we've discussed earlier in this series, serves as the backbone for managing data and interactions. When paired with advanced analytics, this CRM can help transform raw data into actionable insights. For example, predictive analytics could help a pharma brand anticipate HCP needs and preferences, leveraging multi-touch attribution to allow for more tailored engagement strategies, and the ability to inform the next best action/experience relative to a specific HCP therapeutic journey. By analyzing trends and historical data, the brand can forecast which new treatments or therapies might be of interest to specific healthcare providers, enabling more targeted and effective outreach.
Additionally, marketing automation platforms further streamline your efforts by automating repetitive tasks and ensuring that your messaging reaches the right audience and builds on past learnings to optimize timing and frequency. These tools can help you manage campaigns more efficiently, from scheduling and sending communications to tracking engagement and adjusting strategies in real time.
By leveraging these platforms, you can boost operational efficiency and continuously refine your strategy with real-time adjustments based on performance data, ensuring that your efforts remain highly impactful.
Define roles and responsibilities
A successful health data strategy relies on clearly defined roles and responsibilities across the team. For example, in a pharmaceutical company, marketing teams should work closely with data analysts to interpret insights from clinical trial data and patient feedback, allowing them to craft relevant messages, and inform creative and content. Meanwhile, healthcare providers need to coordinate with data analysts to identify therapeutic trends and fluctuations in audience/specialist prescribing behavior so they can in turn respond with tailored care solutions.
Leadership must champion these efforts, ensuring that all departments are aligned with the goal of driving business impact. This collaborative approach encourages a culture of accountability and “open silos”, where each team member is empowered to contribute effectively to the organization’s success, not simply their own performance metrics.
Gain buy-in across the organization
Achieving buy-in from all levels of the organization is critical to the success of your data strategy. This requires effectively communicating the value of your approach to both senior leadership and frontline teams. For senior leaders, emphasize how your strategy will drive key business outcomes—whether it’s increasing ROI, expanding market share, improving patient retention, or optimizing spend (earned, owned and purchase media, as an example). Use data and case studies to illustrate the potential impact and return on investment.
At the same time, ensure that frontline teams understand how their work contributes to the higher-level goals. Provide them with the tools and training needed to execute the strategy effectively and show them how their efforts directly influence the organization’s success. This approach creates a unified, purpose-driven organization committed to achieving business impact by supporting collaboration across departments and functionalities.
Build on insights and validate metrics
In healthcare and life sciences, a data strategy must be dynamic and adaptable. This is achieved by continuously building on the insights gained from your KPIs to refine your strategies and inform your next best actions. Regularly assess your metrics to ensure they accurately reflect the impact on your business by tracking campaign performance and revisiting the relevance and effectiveness of each metric in relation to your goals.
If a marketing campaign for a new treatment generates high engagement but fails to generate trial, it might be time to re-examine the target audience, message content/creative, the communication channels, and/or the media mix. Conversely, if PRO scores are high, but retention rates are low, it could signal the need to enhance follow-up care and patient support programs. By consistently validating and adjusting your metrics, you ensure that your data strategy remains aligned with your business objectives, driving ongoing improvement and success in patient impact, physician reach, and categorical performance.
Conclusion
At the end of the day, the ultimate performance metric for any health data strategy is business impact. By carefully selecting KPIs, leveraging the right tools, defining clear roles, and securing organizational buy-in to define what that means for your organization and using insights to inform strategy, you can transform data into a powerful asset that drives meaningful, measurable outcomes. As you refine your strategy and your tactical mix, keep the focus on impact—because in the end, it’s the business results that matter most.