A generic campaign treats every potential customer alike. Audience targeting instead selects defined groups and matches messages or offers to what is known about their interests and behavior. First-party data can make those choices more precise: purchase history, website activity, and engagement signals help identify whom to reach and why. section 1.6.1 section 7.2
Choose the audience according to the business goal:
- Acquisition: model high-intent audiences, then refine the model as data improves. Paid search can use purchase and website behavior to inform keywords and ad copy; social ads can build custom audiences. section 1.6.1 section 7.2
- Cross-sell and upsell: use behavior and engagement to identify customers likely to value a recommendation, upgrade, or bundle. section 1.6.1
- Retention and winback: use engagement signals to spot churn risk, or reconnect with people who have disengaged. In paid media, retargeting can address visitors who viewed products or abandoned carts. section 1.6.1 section 7.2
From customer insight to campaign
An outdoor retailer seeking to win back formerly high-value customers can identify its top spenders and each customer’s best-selling product, then use those findings to suggest an audience and tailor the message. In the illustrative workflow, a natural-language request produces a calculated product field that could support an email recommendation; the campaign then moves toward audience suggestions and audience-specific ad creative. section 9.2.2
Targeting is a choice to test, not a guarantee of relevance. Track website conversions and post-click behavior to refine paid campaigns. For acquisition, return on ad spend and acquisition cost help assess whether a more precise audience is worthwhile; for retention, churn reduction and engagement uplift help assess interventions. section 1.6.1 section 7.2
