How AI is transforming personalization in mobile marketing | Adjust

Summary

The article emphasizes that AI personalization has moved from optional to essential in mobile marketing, citing McKinsey data that 71% of consumers expect tailored experiences and 76% feel frustrated without them. It breaks down the AI personalization stack into four areas: audience intelligence (predicting LTV, churn, purchase intent), creative personalization (dynamic creative optimization and GenAI for ad copy, voiceovers, localization), engagement timing (AI-driven scheduling and channel optimization), and measurement/feedback loops (A/B testing, cohort analysis, predictive models). Real-world examples include Starbucks using AI for product recommendations, SparkLabs generating GenAI ad creatives for Project Makeover, and Zalando localizing onboarding with GenAI.

The article also addresses critical challenges: privacy and data consent under tightening regulations, overpersonalization leading to algorithm fatigue, and risks of model bias and hallucinations. It advises starting small with focused experiments, focusing on user value, and fostering cross-functional collaboration. Looking ahead, it identifies trends such as emotionally intelligent AI, omnichannel personalization including CTV and AR, and branded foundation models.

For ad ops decision-makers, the actionable takeaway is to test AI tools incrementally, ensure human oversight, and align teams around shared data and goals.