Top 5 strategies fof managing Google shopping campaigns

Expected Result: This allows you to scale the results of efficient product groups immediately and bring the performance of underperforming groups closer to the target. If we simply turn off the underperforming groups, we will lose sales.

Example: In this account, we divided low-performing products into two groups:

Products that haven’t reached the target profitability but generate many sales (Top TRs Low ROAS).
Products with both low profitability and low sales performance (Low performance).
The target ROAS for this account is 500%. The performance of the campaigns is shown in the screenshot below.
WEBSITE STRUCTURE ANALOGUE
Description: This is probably the simplest and most obvious account structure. However, it is increasingly common to come across accounts with just one campaign, one ad group, and one product group for “All Products.” Therefore, I decided to include this point here. In this article, you can find a detailed guide on setting up Google Shopping. It explains how to create such a structure.
Expected Result: You gain more control over campaigns and their performance. If you’re manually managing bids, you can increase them for specific products instead of applying changes to the entire catalog. Additionally, you can fine-tune your budgets more precisely. If you’re using smart shopping, you can exclude products that drain your budget without generating sales, without having to modify the entire strategy.

Example: The screenshot below shows the changes in smart shopping and overall account statistics after implementing segmentation and excluding underperforming products.

BREAKDOWN GOOGLE SHOPPING BY PRICE RANGES
Description: Online stores often sell products with different markups, resulting in varying levels of profitability. It is more convenient to manage advertising for the entire online store if you break down your campaigns by price ranges.
The easiest way to do this is through rules applied to custom labels. The screenshots below illustrate a step-by-step change of the attribute using transformation rules. Alternatively, you can modify the attribute in the feed file, although it may require assistance from a programmer.

Expected Result: This strategy allows you to regulate sales volume while maintaining the same profitability. It is common for inexpensive products to generate higher profits due to the quantity of sales, but the profitability remains low because the cost per click is too high.

If you are unable to separate these products individually (due to changes in the product itself, seasonality, etc.), this structure will be optimal. Conversely, there may be cases where a single sale of certain products consumes the entire advertising budget, with the majority of impressions going to “smaller” products.

I should note that this structure is specific and should only be applied after obtaining and analyzing product.

COMBINING SMART + MANUAL (STANDARD) GOOGLE SHOPPING
Description: Some products are placed in manual campaigns, while others are placed in smart campaigns. There are different options available. For example, when using smart campaigns, you can move products with low impressions to manual campaigns. Alternatively, you can move low-performing products to smart campaigns to optimize their performance based on key goals.

Expected Result: This approach is often used for performance breakdown. Well-performing products without machine learning are kept in standard shopping campaigns to ensure consistent traffic. Poor-performing products are moved to smart campaigns to maintain existing sales while making them more cost-effective and profitable.

Example: The screenshot below demonstrates the dynamics of moving products with high CPA to smart campaigns. The key objective here is cost per conversion, rather than profitability. Pay attention to the dynamics of the manual campaign.

HOW TO COMBINE SMART AND MANUAL CAMPAIGNS
IS-OPTIMIZATION
Description: Two reports need to be created:

From the advertising account, generate a user report for products with the addition of the percentage of lost impressions (rating).
Download impression and click statistics for products from Google Merchant Center.
Check products with zero or very few impressions. It is advisable to move such products to separate campaigns to track their dynamics. Update them approximately once a month based on the traffic.

Expected Result: This helps generate more impressions for products that rarely appear in search results and identify the reasons for low impressions. Start by checking the feed. If possible, make adjustments to the feed for these products, as it should be a priority task.

Sometimes products with good click statistics dominate the impressions for new products. By using IS optimization, you can reduce this competition and generate impressions for new products.

Example: Screenshot 1 shows products with 0 impressions in the Google Merchant Center report. The second screenshot illustrates campaigns segmented by the percentage of lost impressions, with a profitability filter applied.

CONCLUSION FROM THE ABOVE
It is important to note that there are more popular approaches available, such as using “all products” in smart shopping for accelerated search engine learning or breaking campaigns into branded/non-branded categories. I decided to focus on approaches that are more suitable for further optimization to showcase the dynamics of metrics before and after implementing the strategy.

Also, keep in mind that this is a description of general approaches and strategies. We have a separate article on improving shopping efficiency that I recommend reading before starting your work.

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