Skip to content

Meta's AI Ad Targeting Process Boosts Performance Amid Data Collection Changes

Meta's evolving AI ad targeting process is improving ad performance despite changes to online data collection and restrictions on user data usage.

As online data collection faces various changes and restrictions, Meta has been developing new machine learning-based ad targeting models that deliver more relevant ads to users without requiring the same level of personal usage insight.

Apple's iOS 14 update has significantly impacted Meta's ability to gather usage data in its apps. However, Meta's ad business has recently recovered, and marketers report improved performance using tools like Advantage+, Meta's automated ad targeting process.

Meta's latest systematic update, Meta Lattice, is an ad delivery process that uses multiple data points to predict likely ad responses through AI and other predictive technology. The Lattice system can infer more probable user responses without needing as much direct data insight from each person.

By utilizing knowledge-sharing across Meta's different surfaces (News Feed, Stories, Reels), the Lattice system can expand its mapping of potential user interest and activity. Advanced predictive models allow Meta to take in a wider array of data points, better understanding likely individual behaviors.

Meta Lattice is designed to drive advertiser performance in a digital advertising environment with less granular data access. The system can generalize learnings across domains and objectives, which is crucial when the model has limited data to train on. This approach enables the Lattice system to proactively and efficiently update models and adapt to the fast-evolving market landscape.

Meta Lattice also better contextualizes longer-term ad exposure and its impact on response. By capturing real-time intent from fresh signals and long-term interest from slow, sparse, and delayed signals, the system improves ad exposure quality.

Meta's new approach has already improved ad exposure quality by 8%, leading to better results through its automated targeting tools. As AI-based systems evolve and use a broader range of inputs, they are likely to become more significant drivers of response, helping advertisers target the right audience without manually setting campaign parameters.