Why Match Rates Really Matter in Healthcare Marketing
In today's data-driven pharmaceutical and healthcare marketing landscape, the ability to accurately match and manage data across multiple channels is paramount. This capability hinges on a concept known as "match rates," a critical metric in identity resolution and data onboarding. But what exactly are match rates, and why are they so vital for pharmaceutical and healthcare marketing? Here we explore these questions and offer insights into how pharmaceutical and healthcare marketers should evaluate and utilize match rates to optimize their marketing efforts.
What are match rates?
Match rates, simply put, are the percentage of records in one data set that can be accurately linked or matched to records in another data set. In the context of identity resolution and data onboarding, these rates measure the effectiveness of linking disparate data sources to create a unified view of a customer or HCP. There are primarily two types of match rates:
Offline Match Rate: This measures the ability to connect offline data (like purchase histories or prescription information) to online identities or profiles.
Online Match Rate: This evaluates the success of linking various online identifiers (such as emails, social media profiles, or device IDs) to a single individual, helping unify multiple digital footprints into a coherent profile.
There are also additional rates that matter:
Reach Rate: The reach rate measures the percentage of a target audience that can be reached through specific channels or platforms after data has been onboarded and processed. It effectively assesses the breadth of an audience that pharmaceutical and healthcare marketers can communicate with using the onboarded CRM data.
Engagement Rate: This metric tracks how actively individuals interact with a brand's content or campaign after their data has been onboarded. Engagement rate can be calculated through various interactions such as clicks, likes, comments, shares, or page views, relative to the total number of individuals reached. It provides insight into how compelling and relevant the content is to the targeted audience.
Conversion Rate: The conversion rate measures the percentage of individuals who take a desired action (such as making a purchase, signing up for a newsletter, or filling out a form) out of the total number of people reached through specific marketing efforts. This rate indicates the effectiveness of using onboarded data in driving specific consumer actions, reflecting the ultimate success of marketing campaigns in achieving their objectives.
Why Match Rates Matter
Match rates are more than just a metric; they are a reflection of the quality and effectiveness of a company’s data integration strategies. Here's why they are crucial:
Enhanced Customer Insights: Higher match rates enable more accurate and comprehensive profiles, which lead to deeper insights into behavior and preferences.
Accurate Identity Graph: An accurate identity graph enables personalized and relevant healthcare experiences while ensuring compliance with regulations. The accuracy of an identity graph is essential for leveraging the full potential of data-driven healthcare.
Improved Marketing Effectiveness: Accurate matching ensures that marketing messages are personalized and targeted, which increases engagement and conversion rates.
Efficiency and Cost Savings: With better match rates, pharmaceutical and healthcare marketers can reduce waste by minimizing misdirected communications and focusing resources on high-potential interactions.
Compliance and Privacy: Effective matching also helps ensure compliance with data privacy laws by maintaining accurate and up-to-date customer information.
How pharmaceutical and healthcare marketers should approach match rates.
To maximize the benefits of high match rates, pharmaceutical and healthcare marketers should consider the following strategies:
Prioritize data quality: The foundation of high match rates is high-quality data. Ensuring data is accurate, up-to-date, and consistently formatted across sources is crucial.
Use advanced matching technologies: Employing sophisticated matching algorithms and machine learning can help improve match rates by identifying and linking more complex or less obvious relationships between data sets.
Regularly review matching criteria: Pharmaceutical and healthcare marketers should regularly review and adjust their matching criteria to balance between accuracy (avoiding false positives) and breadth (ensuring a comprehensive data match).
Monitor and optimize: Continuously monitor match rates as a part of overall data governance. Use these insights to refine data collection, storage, and management practices.
Consider privacy implications: As match rates improve, so does the depth of data integration, which can raise privacy concerns. Pharmaceutical and healthcare marketers must manage this by ensuring transparency, securing consent, and adhering to regulatory requirements.
Improving match rates involves enhancing data quality, using sophisticated matching algorithms, and integrating advanced technologies like Throtle’s to refine the process of identifying and linking disparate data points.
Healthcare data comes in many shapes and sizes and there is no one magic 'match rate' per brand. When you are matching data, you are looking at a match rate per paired data set. Some match rates are naturally higher due to higher moments of recognition within one or both data sets. But no match rate is ever going to be 100%.