Pharma audiences can draw on contextual content, category and brand interest, permitted anonymised purchase signals and partner attributes. Each source answers a different question. Pharmatic considers relevance and recency to build a segment for an agreed campaign objective. No single signal is a diagnosis or a guarantee of purchase intent.
How it works
- 01Define an audience hypothesis
- 02Select signals and recency
- 03Build and validate a segment
- 04Activate and measure
One segment, several distinct signals
Go beyond broad interests
A generic health audience combines different needs. Separate early exploration, product comparison, brand interest and prior purchase.
Use distinct signal layers
Pharmatic Mindset interprets context; fiscal data can describe category purchases; telecom partner data may add permitted attributes. Overlapping sources must not be added together as unique reach.
Activate and validate
Document inclusion rules, recency, geography and expected scale. Confirm buying availability, frequency and measurement before launch.
Segments for different decision stages
Early category explorers, active comparers and repeat buyers need different messages. Their role in the campaign is set before activation and checked against segment scale and outcomes.
A segment passport
We document inclusion signals, recency, geography, exclusions, expected reach, contact frequency and the metric that will test the hypothesis. The brand team can see why the audience was selected.
What to specify before activation
Manage overlap and fatigue
People can appear in category, brand and competitor groups at the same time. We account for overlap when estimating unique reach and sequencing messages, and adjust rules when a segment is too narrow.
Connect audience to outcome
Each segment has a specific expected action and measurement plan. Audience Portrait clarifies barriers, Demand Intelligence informs time and region, and Sales Lift can test purchase impact when feasible.
Category versus brand interest
Category interest helps reach people still exploring a problem; brand interest reflects familiarity with a specific product. Competitor audiences need a reason to consider an alternative. Each group needs its own message and KPI.
Recency and observed purchase
A recent content visit and a purchase months ago play different roles. Set validity windows by category cycle rather than one universal rule. A purchase confirms an action but not its motive, so test the resulting segment in campaign.
Limitations
Audience profiles indicate relevance, not the health status of an individual. Availability depends on partner data and lawful use.
Questions
How is this different from a broad health-interest target?
A segment is built for the brand objective using topic meaning, recency, decision stage, geography and available purchase signals. Its composition is documented before launch.
Can competitor buyers be identified?
Yes, where permitted anonymised purchase data and sufficient scale exist. Brands, purchase window and matching rules are agreed in the brief.
How long does someone stay in a segment?
It depends on category and objective. A one-off content signal may expire quickly; a purchase history can be useful longer. The window is set and reviewed in the segment passport.
Can Mindset, fiscal and telecom data be combined?
Yes, where permitted matching is available and each layer improves the objective. We check overlap and incremental value rather than adding database sizes.
How do we know the audience works?
Agree on a segment KPI before launch, then review media response and, where the study design allows it, purchase impact through Sales Lift.