Swoop DTC Marketing Solutions
Empower patients to become active participants in their treatment journey.
Exclusive, Privacy-Safe Patient Audiences That Are Higher in Quality and Drive Rx Lift
For too long, life sciences companies have been constrained by the marketplace’s antiquated thinking, processes and systems that produce broad, generic one-size-fits-all target segments that fail to consider a brand’s specific market definition and core therapeutic advantages.
SWOOP IS CHANGING ALL THIS
…as well as enable them to become active participants in their medical journey.
RWD+ML+AI = Rx Lift
Swoop defines and uncovers exclusive audiences based on client-specific market definitions and performance criteria that fuel optimal cross-channel marketing strategies to engage the ideal patient with the ideal message through the ideal channel. The result? Greater performance over conventional targeting approaches.
Privacy-Safe
Industry 1st
First consumer health data company to become a member of the NAI and have our own Privacy Board.
100% NAI
As an engaged member, we assure 100% compliance with the NAI 2020 Code of Conduct Guidelines.All Conditions
Our segment-building methodology is approved for sensitive and non-sensitive conditions.Predictive Power in Action
Predictive Power in Action

Swoop audience quality was 72% higher than the second-best performing partner.

Privacy-Safe Target Segments of Ideal Patients
Uncover Patient Behaviors Through The Precision of AI and Social Determinants of Health Data (SDOH)
Traditional market segmentation starts with a relatively small number of demographic and lifestyle characteristics. Each consumer is then slotted into the best fitting descriptor.
The result is an artificially simplistic view of healthcare consumer groups that creates potential mismatches by forcing a “best fit.”
Incorporating SDOH data and activity-based intelligence increases patient audience granularity.

Incorporating SDOH data and activity-based intelligence increases patient audience granularity.

Psychometric FactorsDetermine how healthcare consumer populations cluster by demographics, attitudes, values and beliefs. |
Decision-Making ApproachesUncover consumer approaches, critical factors and dependencies for healthcare decision making. |
Media Consumption PatternsDiscover healthcare consumer preferences for Programmatic Advertising, Social Media Marketing, Digital Marketing, Addressable TV, Linear TV and On-Demand Audio message deployment. |
Message ReceptivenessUnderstand how brand promises, messaging and "beyond the pill" factors are perceived by healthcare consumers. |
Consumer ExperienceLearn the uptake levels and behavioral effects of differentiated consumer healthcare messaging. |
Marketing MixDetermine the blend of cross-channel activation including Programmatic Advertising, Social Media Marketing, Website Personalization, Search Engine Optimization, Addressable TV, Linear TV and On-Demand Audio. |
Psychometric Factors
Determine how healthcare consumer populations cluster by demographics, attitudes, values and beliefs.
Decision-Making Approaches
Uncover consumer approaches, critical factors and dependencies for healthcare decision making.
Media Consumption Patterns
Discover healthcare consumer preferences for Programmatic Advertising, Social Media Marketing, Digital Marketing, Addressable TV, Linear TV and On-Demand Audio message deployment.
Message Receptiveness
Understand how brand promises, messaging and "beyond the pill" factors are perceived by healthcare consumers.
Consumer Experience
Learn the uptake levels and behavioral effects of differentiated consumer healthcare messaging.
Marketing Mix
Determine the blend of cross-channel activation including Programmatic Advertising, Social Media Marketing, Website Personalization, Search Engine Optimization, Addressable TV, Linear TV and On-Demand Audio.
Our SDOH Data Universe

Economic Stability
Employment, Working Conditions, Income, Expenses, Spending, Debt

Wellness
Nutrition, Hunger, Access to Healthy Options, Activity Level

Environment
Location, Housing, Transportation, Safety, Recreation, Walkability

Community
Integration, Support, Engagement, Discrimination, Stress
Education
Literacy, Education Level, Language, Vocational Training

Health Care
Availability, Accessibility, Coverage, Quality of Care

Demographics
Citizenship, Gender, Ethnicity, Faith, Age, Marriage, Children

Influence
Social Media, Web, Digital, Television, Ratio
Our ML and AI-Based System of Engagement Provides High-Definition Patient Intelligence to Discover Cohorts of Patients Relevant to Your Brand
ML+AI+RWD = 65 billion anonymous consumer transactions and over 300 million unique de-identified patients
Cluster Modeling
Considers all relevant pattern-of-life characteristics rather than a few pre-determined demographic traits.
Dimensional Spatiality
Measures the distance from any point in a multi-dimensional space where population clusters form around an attribute.
Commonality Extraction
By not using pre-determined categories, we uncover natural population clusters and then extract commonalities.