AdWords Ad Scheduling is a powerful tool, but can be dangerous if you analyse the data incorrectly.
In this T-Time Show, Mark explains the difference in attribution models between the data your website and Google Analytics provides and the conversion data Google AdWords provides, proving that AdWords ad scheduling isn’t always such a great idea.
Takeaways from this video:
Ashley, who has an eCommerce store, finds that between 5 pm and 7 pm people don’t buy on the website, so should I schedule my ads to pause during that period because I have a high cost per conversion?
Using the dimensions tab
1:42 Mark explains how to look at that data using the dimensions tab in AdWords, and warns that you must have lots of data to make decisions. The figure we are interested in is the one that shows you your return on investment; conversion value divided by cost.
Remember that users may click once, or twice, or even three times before they buy and if we turn off the scheduling that triggered the first click at the top of the funnel before they bought you may miss the sale completely. Be careful about breaking the funnel.
4:30 When considering the time between 5pm and 7pm, people have just finished work, they are travelling or just simply not in a buying mood. So should you turn these ads off?
5:05 Rather than turning ads off, you can make a bid adjustment within the campaign tools. Instead of saying you don’t want the ads running you could lower the bids by a percentage, but exercise caution.
6:06 What is also important to know that the data in the back end of your eCommerce store, on your website and also in Google Analytics the conversion data is more real time. You will see data about when the conversion happened. Google Ads attributes the conversion to the day and time of the click and not when it actually happened.
This can cause confusion and anomalies as the data doesn’t quite match up. Review all data before making a decision that could lose you sales. Mark explains in depth with the use of demonstration slides in the video.
Ask questions in the comments and we’ll do our best to help. If you have particular anomalies with your data, perhaps you would like us to take a look at it and help you out, if so please contact us.
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