This post was sponsored by Adchieve. The opinions expressed in this article are the sponsor’s own. Smart Shopping campaigns in Google Ads offer a number of benefits that advertisers find attractive – particularly those trying to manage product promotion at scale. It’s a format that puts Google’s machine learning to work for you by automating bidding, testing, and ad placement, using your product feed to display ads across the Google Search Network, Google mobile number list Display Network, YouTube, Gmail, and more. It can be a helpful assist in simplifying and streamlining campaign management – that is for sure. But having machine learning do the heavy lifting has its potential downsides, too. Smart Shopping can be something of a data “black box” for marketers. How can you use the different types of data available to you to better influence the results of this machine-assisted automation?
Once you better understand the inputs and outputs of that black box, you can tinker with the input more effectively. In this article, you’ll learn how to do just that. Read on as we explain how you can use combined insights obtained from different types of data to better match your business objectives, drive the best possible ROI, and really move the needle in product sales. The Unprecedented Importance Of Data Science Before you can uncover insights, you must first understand the distinction between different types of data. Google Data: Data you get mobile number list back from Google Although Google discloses less data than ever, there is still a lot of important information that you can use. Think of conversions, costs, impressions, etc. Company Data: Company-specific data that indicates which KPIs or factors you focus on Company data is data that you have yourself. Think of insights into margins, stock data, and all kinds of customer data. Competition Data: Data about what is happening in your market The third data source is data about the market in which you are active.
Are you ahead or behind your competitors? What are your competitors’ prices and which products do they offer? Which keywords do they rank for and you don’t? Now let’s make the leap to insights. 4 Examples: How Turning Data To Insights Can Give You A Head Start Different types of data are needed to arrive at valuable insights. Sometimes this concerns insights for which you only need one data source, but we think the best insights can be found when you combine Google, company, and competition data. The following are some examples of insights that you mobile number list can now build with Adchieve to optimize your campaigns within Smart Shopping: Understanding campaign profitability (POAS). Insight into cross-sell and upsell patterns. Insight into prices and their importance for your rankings. Insight into keywords in Smart Shopping campaigns. 1. POAS Insights In our journey to understanding Google’s shopping algorithm, we wondered if ROAS is a good objective.