Pharmatic Mindset uses AI to analyse available audience signals. It relates the subject matter of viewed content to categories and medicines, considers signal recency and helps develop advertising segments. The result describes potential interest in a subject. It does not establish a diagnosis, recommend treatment or guarantee a purchase. Sources, segment rules and placement are agreed for the campaign.
How it works
- 01Raw signals
- 02Topic interpretation
- 03Relevance and recency
- 04Interest profile
- 05Segment and activation
From signal meaning to a segment hypothesis
- 01SignalExploration of a topic or category
- 02MeaningInterpretation of thematic relevance
- 03ContextRelevance and recency of interest
- 04SegmentScale check and media activation
Inputs remain distinct
The system can use thematic content, search and interest context, platform signals and permitted partner data. Fiscal and telecom sources retain different meanings.
From signal to segment
A signal receives a thematic interpretation and a recency window. Related signals form an interest profile; the resulting segment is checked for scale and activation.
What the technology does not claim
It cannot infer why someone viewed a medicine leaflet or diagnose a condition. Audience hypotheses need campaign validation and measurement.
What a signal suggests — and cannot prove
- interest in a topic or category
- stage of product exploration
- relevance of a message
- a diagnosis or health status
- why a person viewed a page
- guaranteed purchase intent
Why meaning matters beyond keywords
The same term can appear in news, a product instruction, prevention content or active comparison. Mindset considers topic, context and recency to distinguish broad exploration from a more specific category choice.
A brand workflow
The brand defines its product, category and campaign goal. Relevant topics and signals are selected, recency is checked, and segments are built for different decision stages. Messages, frequency and measurement are agreed before activation.
How to assess segment quality
Checking a segment requires clear topics, inclusion and exclusion rules, signal recency, size and overlap with other groups. Hypothetical example: reading a medicine news item and repeatedly studying product comparisons may call for different messages. This is an interest hypothesis, not a confirmed decision stage for every person. After launch, review response and frequency, then refine signals if the original hypothesis is not supported.
Mindset in the data stack
Mindset helps find audiences before a purchase, when receipt data alone cannot identify new people. Fiscal receipt data and permitted telecom characteristics can complement subject interest. Selection criteria and the campaign objective are recorded for the resulting segment.
From raw signal to relevance
Permitted observations of category content and product exploration are interpreted in pharma context. Relevance and recency are assessed before several consistent signals form an interest profile; one accidental visit should not carry the same weight as sustained research.
From profile to activation
For activation, translate the profile into advertising-segment rules and check available scale. Mindset web segments, partner InApp and CTV require separate capability confirmation: conditions from one channel do not automatically carry over to another. CTV targeting operates at household level. Record the channel, selection rules, message and metric in the media plan so results can be compared with the original hypothesis.
Limitations
Available sources and technical parameters depend on the project and partners. No model accuracy figure is claimed on this page.
Questions
How does Mindset differ from contextual targeting?
Contextual targeting looks at a page or placement. Mindset interprets the meaning and recency of available permitted signals to build audiences for a decision stage and brand objective.
What is needed to configure it for my brand?
Start with the category, product, audience and goal. Relevant topics, exclusions and recency are then defined; available sources are confirmed for the project.
Can a new product use Mindset without sales history?
Yes. Initial audiences can use category and content interest; purchase signals and campaign results can refine them later.
How often are segments refreshed?
That depends on source, category and campaign duration. The key is to set a validity window for each signal and review it as demand changes.
Can Mindset's contribution be tested?
Segments can be compared on agreed media KPIs. A claim about incremental sales requires a separate Sales Lift design and purchase data.