AI Audience Planning Intermediate
AI audience planning goes beyond basic demographics to discover high-value audience segments, build predictive lookalike models, and determine the optimal targeting strategy for each campaign. Machine learning enables marketers to find the right people at the right time with the right message.
AI Audience Discovery
Traditional audience planning starts with assumed demographics. AI audience discovery starts with your best customers and works backward to find more people like them:
- Behavioral clustering: Group customers by actions, not demographics, to find meaningful segments
- Propensity modeling: Score prospects by their likelihood to convert based on behavioral and contextual signals
- Interest graph analysis: Map customer interests and content consumption to identify targeting opportunities
- Cross-channel identity: Unify customer signals across devices and platforms for complete audience profiles
Lookalike Modeling
Lookalike audiences use AI to find new prospects who share characteristics with your best existing customers. The process involves:
Define Seed Audience
Start with your highest-value customers: top spenders, most loyal buyers, or best brand advocates. Quality of the seed matters more than quantity.
Feature Extraction
AI identifies the distinguishing characteristics of your seed audience across hundreds of signals including behavior, interests, and contextual factors.
Model Training
ML algorithms learn the patterns that differentiate your best customers from the general population.
Audience Expansion
Apply the model to find new prospects who match the learned patterns. Balance reach and precision by adjusting the similarity threshold.
Audience Sizing and Prioritization
AI helps determine the optimal audience size for each campaign by balancing reach with relevance. Key considerations include the total addressable audience, expected response rates at different targeting widths, budget efficiency at various audience sizes, and campaign objectives.