Training dataset decreasing in quality (Google data science blog)
Here are some things to consider. You may already be doing some of them, but it's hard to tell.


As new data arrive, add them to your database. Randomly sample, with replacement, your database. All other things being equal, take a 2/3 sample and reserve 1/3 for testing. Record the training error and the prediction error. 
At intervals, take past training data sets and measure prediction error on a sample of new data only.
Prepare time series of the training error, contemporary prediction error and post-training prediction error.
Look for trends and temporal autocorrelation.
Consider possible seasonality in demand for the offered product.
Consider market changes (entry of new competitor, substitution goods, price points)


This is just the view from 30,000 feet. It's hard to say more without knowing more about your model.

Good luck.