Think of this as a smart ad-placing assistant that studies who actually clicks and buys from your ads on social platforms, then automatically shows future ads to more people who look and behave like those best customers.
Manual audience targeting on social media is inefficient and guess-based, leading to wasted ad spend and low conversion rates. AI improves targeting precision by learning from historical campaign and user behavior data so ads are shown to the right people at the right time.
If implemented by a platform like Koast, the moat would come from proprietary performance data across many advertisers, audience behavior signals, and being embedded directly into advertisers’ campaign setup workflow.
Hybrid
Feature Store
Medium (Integration logic)
Data privacy and access to granular user-level signals from social platforms, as well as model retraining cost on large event streams.
Early Majority
Compared to native ad platform optimizations (e.g., Facebook’s lookalike audiences), a third-party AI audience targeting solution can combine cross-platform data, model full-funnel performance, and provide more transparent, advertiser-controlled segmentation and insights.