farrellwahyudi/Predicting-Ad-Clicks-Classification-by-Using-Machine-Learning

In this project I used ML modeling and data analysis to predict ad clicks and significantly improve ad campaign performance, resulting in a 43.3% increase in profits. The selected model was Logistic Regression. The insights provided recommendations for personalized content, age-targeted ads, and income-level targeting, enhancing marketing strategy.

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This project helps marketing and management teams improve ad campaign performance by predicting which users are most likely to click on an ad. It takes historical customer data, including demographics, site usage, and past ad interactions, to identify target customer segments. The output is a set of insights and recommendations for personalized, age-targeted, and income-level ad strategies.

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Use this if you are a marketing manager or business owner looking to optimize your online ad spend by targeting the right customers and increasing your ad click-through rates.

Not ideal if you lack historical data on customer demographics, site activity, and ad click behavior, or if your advertising strategy doesn't involve online ads.

ad-targeting marketing-analytics customer-segmentation campaign-optimization digital-marketing
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 8 / 25
Community 6 / 25

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Last pushed

Nov 06, 2023

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