Reinforcement Learning-based Approach for Click-Through Rate Optimization in Real-Time


Authors : Dr. Sk. Mahaboob Basha; T. Sai Kiran; Ch. Hemanth Sai; K. Lavanya

Volume/Issue : Volume 8 - 2023, Issue 4 - April

Google Scholar : https://bit.ly/3TmGbDi

Scribd : https://bit.ly/3HMlCvE

DOI : https://doi.org/10.5281/zenodo.7902000

A popular metric for assessing the success of online advertising campaigns is click-through rate (CTR), particularly in the context of pay-per-click (PPC) marketing. Ad tracking is a crucial piece of technology for monitoring click-through rates (CTRs) in online advertising campaigns. With the aid of ad monitoring solutions, marketers can monitor the effectiveness of their advertising across various platforms and gadgets, including click-through rates. An advertising campaign's efficacy is assessed using this data, and it is subsequently improved over time to increase click-through rates and total return on investment(ROI). Advertisers can test many iterations of their ads and links using A/B testing tools like Optimizely, and they can track the clickthrough rates of each version to determine which one performs best CTR is frequently employed in the context of email marketing, where it is used to assess the success of a campaign by counting how many recipients click on links in the email. When used in this context, CTR is sometimes reported as a percentage of all email recipients who opened the message.

Keywords : Web Analytics, Ad Tracking, Email Marketing Software, A/B Testing Tools, Artificial Intelligence, MultiArmed Bandit, Generative Adversarial Networks (GANs).

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30 - April - 2024

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