Amazon PPC Automation: Bid vs Acos analysis
As a part of ongoing initiative at AiHello to make PPC Ads optimization more efficient, we are working to upgrade all our algorithms from our current ARIMA model to a CNN or a LSTM model. We will be running a series of tests and comparing the results between simple regression, machine learning by CNN, machine learning by LSTM and finally using Deep Learning by other Neural Networks. Our initial observation and hypothesis is that bids are affected by seasonal variations. We will be running a non-time series machine learning via CNN and a time-series based LSTM network and comparing their differences. The below post outlines the initial data, observation and analysis of data. Data Scale/size 1.1) There are around 40k distinct keyword IDs in the dataset, with an average of 7 days records for each keyword ID. Most keywords have a one-week record rather than a long-term record. 1.2) Removing the Sales = 0 Records: Over 83% of the data having Sales = 0, which indicates that most keywords