Smart Shopping campaigns can no longer be ignored. Campaign management is greatly simplified as machine learning takes over the coordination of campaigns. Conversion value goes up, visibility within the search network improves and range is extended as a result of an increase in the number of views within the Google Display Network, Youtube and Gmail. For Kees Smit's growth strategy, smart shopping campaigns were the obvious option to go with as oppose to standard shopping campaigns.
Smart shopping does have some disadvantages. Search query and audience data are not available and control over product visiblity is being limited to a minimum.
Google recommends targeting all products in a single campaign in order to generate as much data as possible for smart bidding. This is quite a short-sighted approach because both low-value and high-value products get equal visibility in this situation.
An innovative solution to this problem is combining the power of machine learning within smart shopping with control over product visibility. With the use of data modeling, we connect our own unique product data to Google's data in order to coordinate the smart shopping campaigns.