Smarter Spending, Stronger Results: The Power of Dynamic Impression Pacing

Static impression pacing, which uses fixed time intervals between ads, limits efficiency by treating all users equally. Liftoff's Dynamic Impression Pacing employs machine learning to assess each impression opportunity in real-time, considering the user's predicted conversion rate, recency of previous impressions, and expected revenue impact. This dynamic approach adjusts bid prices—increasing bids for high-value users and pacing lower-value ones over longer periods—reducing wasted spend and improving conversion rates.

In a four-week A/B experiment, Dynamic Impression Pacing decreased impression volume by 10%, increased install rates, and maintained ROAS. The system is particularly beneficial for high-volume campaigns with short pacing intervals (under one hour), where it optimizes budget distribution across different user segments. Advertisers gain optimized spend efficiency, more high-value conversions, and reduced manual adjustments.

Liftoff plans to further refine ML models and predictive capabilities. Key takeaway: ML-driven pacing balances control and automation for better results, allowing advertisers to maintain minimum thresholds while leveraging real-time optimization.