Structuring shopping campaigns in a Google Ads account is extremely important for improving your results. But there is a lot of confusion there, and Google does not provide any recommendations in that area. In today’s post, I’ll explain in an easy and practical way why and how to structure shopping campaigns.
Why split shopping campaigns
While the ultimate reason of splitting shopping campaigns is performance, sometimes logistics plays role as well.
Some of the Logistical reasons are:
- Different countries That’s an obvious choice when you advertise in different countries, especially with different currency or language, or both.
- Seasonality If you sell swim ware and winter jackets, you probably want to treat those products differently. Put them in separate campaigns.
- Large Inventories If you feed has 20K of more SKUs, managing one shopping campaign becomes difficult and prone to errors. Dividing the products by some convenient method, for example, by mirroring the website categories, is a good solution here.
Now let’s look at the Performance reasons.
- New vs existing products If you regularly add new products to a smart campaign, learning period is triggered. This may hurt performance of existing products. To minimize this negative effect, place new products to a separate campaign. Once enough traffic and conversion data is collected, move them over to the main campaign. Learning period will be shorter because product data already exists in the acount.
- Bestsellers and Promotions strategies will allow you to focus on a small subset of products that you want to promote.
- Different ROAS strategy helps you to split products based on historical ROAS, and treat them differently.
- Search Query filtering strategy will bid higher to the visitor google searches that are closer to the purchasing decision.
- Catch-All strategy addresses the tendency of Smart bidding to “optimizing away” - or stop serving - some products. It “catches” product searches that fell through the cracks of smart bidding campaigns.
Campaign priority levels
Campaign priority level is the setting on standard shopping campaigns. It does not exist on smart shopping campaigns.
The setting becomes useful when you’re advertising the same product in multiple campaigns.
Campaign priority allows you to determine which campaign should participate in the auction for that product.
There are three priorities: Low, Medium, and High. All shopping campaigns have Low default priority, but you can change at any time. These priorities determine the bid for any products that the campaigns share.
Use campaign priority when you want your product bids to come from a specific campaign.
You have a campaign Tapes that includes tapes from all manufacturers.
The 3M tapes are your bestsellers, so you add a campaign 3M Tapes with higher bids. Now 3m tapes are listed in both campaigns.
But whenever 3M tape is searched, you want the product bid to come from 3M Tapes campaign - not from Tapes campaign.
To make sure that this happens, set High campaign priority on the 3M Tapes, and set Low or Medium priority on the Tapes.
This approach works better if you prioritize only a subset of the products that you want to promote.
Smart Shopping Turbo strategy
This strategy will help you grow sales of your smart shopping campaign.
Next to your smart shopping campaign, start a standard campaign Shopping - catch-all for the same products, with low bids and low budget.
This campaign will “catch” product searches missed by the main campaign and serve ads.
Catch-all campaigns spend very little and generate some revenue with good ROAS.
Consider following this set up process for the new campaigns, or when your smart chopping campaign is not bringing results.
Stop your underperforming smart shopping campaign (optional.
- Launch Shopping - all - manual campaign with full budget and Manual CPC or Max Clicks bidding. Run the campaign long enough to generate 10-15 conversions.
- Run the product report and note high-spending, low-performing products.
- Start Shopping - all - smart campaign with 90% of total budget . Exclude high spenders found earlier. At the same time, start Shopping - catch-all campaign for all products with manual CPC bidding, low bids and 10% budget. For this campaign, you can reuse Shopping - all - manual campaign used in the 1st step.
This Strategy is relatively easy to work with, On the scale 1 to five, i’ll give 4 to ease of set up and ease of management. I’ll give it 3 out of 5 for performance.
This is my most popular shopping account structure. It can deliver great performance, but not for every account.
To set it up:
- Place a subset of your products in a campaign with aggressive bidding. Those products can be bestsellers, or promotional products, or a new apparel collection that you know will sell well.
- Place the remaining, regular products in another campaign with conservative bidding.
- Finally, add a catch-all campaign.
To simplify setting up and managing shopping campaigns, use custom labels. After tagging selected products with a custom label in the feed, use it as a product group selector during the campaign setup.
This strategy is a bit more complex, I’ll give it 3 our of 5 for both ease of setup and ease of management. For performance, I’ll give it 4 out of 5.
Search Query Filtering
This popular and somewhat complicated bidding strategy has been around since 2015.
The strategy allows you to bid separately depending upon a search term, also called search query.
It has became less effective in recent years when Google, in 2020, started hiding some of search terms.
The strategy allows you to:
- Bid low on a general search term
- Bid higher on the more specific search term (for example, that includes brand)
- Bid highest on the most specific search term (for example that includes a product name or SKU)
The logic is that more specific searches are more likely to convert, and therefore should get more aggressively priced ads.
You have three campaigns with low, medium, and high bidding levels.
Three Google searches, related to your products, arrive:
- industrial tapes (we'll call it generic query)
- 3m industrial tapes (we'll call it brand query)
- industrial tapes (we'll call it product SKU query)
You want that the generic query is served by the 1st campaign, the brand query - by the second campaign and the product SKU query - by the third campaign.
You assign high campaign priority to the 1st campaign, medium priority to the second campaign, and low priority to the third campaign.
You add negative keywords to the first two campaigns.
The queries arrive first to the campaign with the highest priority level. This is the Low bid campaign.
- The industrial tapes query is served by the campaign
- Two remaining queries are blocked from this campaign by the negative keyword lists Brand and SKU
- Two queries are passed further down
Two queries arrive to the second campaign.
- The 3m industrial tapes query is served by the campaign
- The remaining query 3m 3550 tape is blocked from this campaign by the SKU negative keyword list
- The 3m 3550 tape query is passed further down
The 3m 3550 tape query arrives to the third campaign, and the ad is served.
Our goal is achieved.
While less effective today, this option can still deliver good performance.
I only use it when smart bidding is not performing, or not appropriate (for example with low monthly conversions).
I also prefer to use a simplified, 2-campaign setup, without the SKU campaign.
I give this option 1 out of 5 for ease of setup and management, and 3 and a half for performance.
Account Structure case study
With this imaginary case study I’ll go show my approach of planning and building a campaign structure.
Frank is marketing manager for Signs Unlimited, an online store that sells signs for home bars and garages.
Two months ago Frank started testing a smart shopping campaign for all products.
The campaign has spent $2K and generated $4K, ROAS of 200%.
Today Frank is given the budget of $6K/mo and the task to increase sales to 15K within two months.
It means, he needs to increase also ROAS to 250%.
The feed is in good shape, Frank feed that opportunity lies in restructuring the account.
What about the Search Query strategy?
Because there’s no history of search queries in smart shopping campaigns, Frank checks the organic Query report in Google Analytics.
There are no strong brand or product search terms.
That’s understandable. Signs Unlimited is a young business without strong brand awareness.
Next, Frank runs a product report and notices that:
- 30% of products delivered 80% of revenue
- Most of bestsellers were Neon signs and Custom signs
- Neon signs had 13 sales, and Custom Signs have 8 sales
Frank starts the Shopping - all - manual CPC campaign with manual bidding and the $6,000 budget.
30 days later, Frank gets these results:
- Spend: $6,000
- Conversions: 86
- Revenue: $13,200
- ROAS: 220%
While the average ROAS is still low, Frank notices that Neon and Custom signs categories have delivered 80% of sales with adequate ROAS.
Frank rebuilds the account to the 3-tiered Bestsellers structure.
A few notes:
- We set tROAS for Bestsellers lower than historical ROAS of both categories in order to give more room to the bidding algorithm to be more aggressive.
- We set the Bestsellers budget to 80% of total to reflect the revenue of those product categories.
- We use manual bidding on the Regulars campaign because smart bidding would struggle with low conversion data on those products.
- The role of the catch-all campaign is to catch the product searches missed by other two campaigns. It has very low bidding and the low campaign priority level.
Another month passes, and ROAS is 253%.
The goal has been achieved.
Going forward, Frank continues to manage the account by:
- Building a negative keyword list after analyzing Search terms
- Testing different tROAS on bestsellers in the search for the ideal performance
- Scaling the bestsellers by increasing budget
- Scaling the bestsellers by identifying new bestsellers candidates inside the regulars campaign
In this imaginary case study, I showed my approach to planning and building the account structure.
In real life, results may not arrive so quickly, or many not arrive at all for some accounts, so be ready to experiment and react accordingly.
Comparison & Recommendations
Here are rankings of the three strategies we've covered.
There's a big variation in the ease of set up and management, and that will probably be the main determining factor for many.
Performance is only indicative. Direct comparison will not be accurate because it is highly dependent on specific account.
How do I decide which category to use? Here is what I think:
- Smart Shopping Turbo is a good choice for new shopping ads practitioners, who want to run a simple, mostly hands-off setup
- Bestsellers method is my main approach to structure accounts that get over 15 shopping conversions a month. It is universal, and flexible
- I use Search Query Filtering when monthly shopping conversions in the account are below 15, or other structures don’t work
A word about Performance Max Campaigns
Google has recently announced the rollout of Performance Max campaigns “after strong beta results”.
What’s more, Performance Max will replace Smart Shopping campaigns in September 2022.
That’s quite a bid shift for Google, considering that for the last two years Google has been pushing Smart Shopping Campaigns.
After testing the pMax campaign, and watching the industry I have three things to say:
- To me they look like are extension of Smart shopping campaigns, so they won’t be too hard to learn.
- I hear some positive feedback from respected PPC peers about pMax.
- I won’t be surprised if the switch date is pushed further in the future.
That means while we still have time, we better start learning Performance Max campaigns.
In this post, I've described my methods of splitting shopping campaigns.
Do you have any questions? What method do you use? Write to me. Thanks.