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If you’re an eCommerce marketer running Google Shopping campaigns, you’re probably focused on optimizing your Google Shopping feeds and Google Ads.
Despite everything these platforms can do, there is one fatal flaw with relying only on these two platforms to inform your online advertising strategies: reported conversions only include sales that resulted from a Google ad click. This often results in an incomplete picture of which products are selling across all platforms.

So, one question: Have you tried to optimize your shopping campaigns with data from your Analytics?
Google Analytics data product feeds are the ultimate secret weapon for eCommerce stores. Optimized shopping campaigns can help you run specific strategies. They enable you to meet your business goals by integrating valuable Analytics Data with Google Shopping Campaigns,  forming a comprehensive picture of all the important data generated by your online stores.

Considering 43% of all eCommerce traffic comes from Google searches, leveraging Google Ads to secure prime real estate on search pages is well worth the investment.
Many consumers do view Ads positively, with approximately 54% of consumers exposed to ads that reminded them of something they already wanted, resulting in  20% of purchasers reporting that they considered the Ad helpful.

To fully benefit from the torrent of purchase-ready Google users, you must fully integrate your Google Analytics Data with Google Shopping to truly understand your customer journey, their behavior, and the overall data narrative.

This practice is useful for eCommerce platforms of all sizes, and it’s especially valuable for mid to large-size companies as they can benefit from automated processes that add dynamic data to product feeds, and enable very targeted Shopping Campaigns.

In this post, we’re going to break down how you can extract metrics to create an in-depth view of the data generated by your online store.
This will allow you to formulate specific Shopping Strategies that empower you to reach specific goals.

Google Analytics Data for Campaign Optimization

Your first step begins with a single question: What are your campaign goals?
This will determine how you apply custom labels to your product feeds before uploading them to Google Shopping. Custom labels are blank attribute slots within the product feed (a .txt or .csv file) that can be used however you desire.

An example: if you want to run ads to boost products that have sold the most in the past 30 days, Google Analytics can help you apply a custom label to these products that can be used within Google Shopping.
Here are some common campaign goals

  • Promote all-time top-selling products
  • Promote less popular products
  • Promote higher-margin products

It’s wise to consider the overall revenue and quantities sold to ensure that you are promoting products with a strong chance of being sold. This data can also be found within Google Analytics.

We’ve mentioned custom labels for Google Shopping a few times. You can create them using any criteria you like. Check out the following common criteria leveraged to create these labels:

  • Channel exclusivity
  • Channel
  • Condition
  • Item ID
  • Category
  • Product type
  • Brand

Custom labels are an essential aspect of creating product segments that can be used to run specific Shopping campaigns. These labels can also be named anything, such as High Margin, and are put to use once your product feed is uploaded.

Setting Up Your Strategy in Google Analytics

Your next step is to go into Google Analytics Query Explorer and identify the products that apply to your specific goal.
For example, if you want to isolate your most popular products or how much money a product earned in a given time frame, there’s a query that will help you identify them.

You may need to combine data from Google Analytics with data from your eCommerce platform, such as determining the highest margin products. Google doesn’t know your margins,
To help you determine the highest-selling products, compare the top-selling report with your platform’s margin report.

Google Analytics updates its interface constantly. Here is a handy guide of general locations to run useful reports:

  • Top selling products: Head to the Product Performance tab under Conversions
  • Google Shopping revenue: Find out how much revenue Shopping campaigns are earning by navigating to the Source/Medium tab under All Traffic
  • Multi-channel conversions: Locate the Multi-Channel Tab under Conversions to identify all of your conversion sources across all channels
  • Site diagnostics: Site speed is vitally important, and a slow site will typically have a high bounce rate and decreased time on site. Determine this information by navigating to the Behavior tab.

Generate all reports that are relevant to your specific goals before moving on to the next step. After you’ve manually experimented with a few campaigns, you can automate your data to automatically add dynamic content to your product feeds used in Google Shopping campaigns. We’ll cover this in more detail in the following section.

Executing Your Strategy in Google Shopping

All of the data that you pull from Google Analytics can be used in the product feeds imported into your Shopping campaigns. If you’re new to creating product feeds and importing them into Google Shopping, review Google’s documentation on the process.

Some data attributes are required, but others are optional. As much as we highly recommend using custom labels, they are not a requirement. However, Custom labels are the backbone of how you can truly optimize your campaigns to best execute your strategy for success.

Your product feed should include:

Once a feed is uploaded and processed, you can then use the data to execute specific Ads using data within the feed.
For example, every product with a custom label of “high margin” can be exclusively promoted in a specific campaign. Set up your Google Ad campaigns to make use of the custom labels that are relevant to your stated goal.

How to Generate Automated Data and Add it to Your Product Feed

Up until now, we’ve only briefly mentioned how to automate this process.
First, you need to understand the entire process before taking an additional step to add dynamic data to your product feeds.

Setting up the automation process begins with Google Analytics Query Explorer. You can simulate queries from your Google Analytics account and use the same queries on API calls to generate the same results.

Define your query based on your customers’ account IDs, analytics results, start date, end date, metrics, and dimensions. You can also sort, use filters, add max results, and more. Metrics such as Item Quantity and Item Revenue are popular queries for eCommerce merchants to add to their product feed.

Product Feed Optimization for your Google Shopping Campaigns

During this whole process, talking to a product feed optimization expert can help you leverage the opportunities given fromGoogle Analytics Data.

Highstreet.io’s product feed platform mixes and matches your performance data from Google Analytics (GA) automatically with your catalog content. The technical elements of integrating your GA data with your Google Shopping feed are taken care of so you can focus on using your new feed to improve your campaign results.

We know that it can be challenging and we’re here to help.
Our highly-trained specialists helps you integrate all of your data from your Google Analytics with your Google Shopping feed, creating an entirely automated product feed optimization process that allows highly segmented Ad campaigns.

Start making the most of your data. Contact one of our product feed optimization experts today to get started.