Deep Learning Boosts Click Prediction Accuracy by 15% in Mobile AdTech

The mobile advertising industry has seen a significant shift towards using deep learning for click prediction, a move that predates the rise of Large Language Models. This transition is driven by the need to enhance user acquisition strategies in mobile gaming, where companies like Applovin boast market caps over $100B. Traditional machine learning methods like logistic regression, while effective, have limitations, particularly with high cardinality features. Deep learning, with its ability to handle sparse data through embedding layers, offers a solution. A practical example using a Kaggle dataset showed that deep learning models could improve the precision-recall AUC metric by 15% compared to logistic regression. However, deep learning models require more tuning for calibration. The industry’s shift to deep learning is evident as most large tech companies in AdTech now employ these techniques to predict user behavior more accurately.

Source: towardsdatascience.com

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