As we approach Q4, retailers start to gear up for the busiest period and begin increasing their investment in Google Ads, and in particular Google Shopping Ads. In Q4 of 2022 Google Shopping Ads took the largest portion of spend and resulted in 65% of overall Google Ads Spend. (Data from Shoptimised)
Although Shopping Ads are growing every year and as they evolve from Standard Shopping to Smart Shopping and now Performance Max, retailers still have a lot of questions about how to get their Shopping Ads more visibility. This isn’t just a question clients put to their agencies, it's a question that is commonly asked when we have discussions with agencies that subscribe to Shoptimised.
The Google Academy gives insight into the Shopping Ads Algorithm and Auction Dynamics and what goes into serving an ad.
Data Quality - Takes into the key components of Shopping and looks at unique identifiers such as GTIN, Title, Brand, MPN, Description while also looking at the quality of images in the feed and also takes into account Price.
Product Relevance - Combined together with Data Quality as the quality of the data also needs to be relevant to the product being advertised.
Predicted Click Through Rate - Expected Click Through Rate has been a factor in Quality Score on search for a long time, now we have confirmation that this is a factor in the Shopping Auction. Google looks at the historical data of your account, the product feed and predicts a click through rate. The more relevant your product, the better your predicted click through rate will be. More relevant data within your Product Feed will then increase your predicted click through rate over time. This leads to a better position in the shopping results, which inturn leads to a better click through rate and the cycle repeats itself.
Bid - The bid is often thought of as the key component of being shown in a shopping auction, but it is just one of four key parts. The better optimised your product feed is, the higher your Predicted Click Through Rate will become which results in you having to make a modest bid. However, if you find yourself having to increase your bid it could mean you have neglected the other key areas. When it comes to Performance Max, you’re not in control of the bid, but you can influence it via your campaigns settings with bidding strategies such as Target ROAS. However, the higher you set your Target ROAS, Google will restrict traffic and products if it doesn’t predict you will achieve your Target ROAS in each auction. This is why it is imperative to get your Data Quality and Product Relevance right as it has a direct impact on the Cost per Click you will potentially have. The lower your Cost per Click will result in more Google serving more products as your Target ROAS will become easier to achieve.
Titles - Google listing Title as the one of the key attributes with a high impact on the auction is no surprise as this along with the image and price is what is shown in the Shopping results. Google is looking for rich keywords that have high search volume, but adding the brand, gender, age group to the titles gives more long tail visibility, higher click through rates and conversion rates.
GTIN - Google uses GTINs as a unique product identifier, products without a GTIN, in particular from well known brands can have a significant decrease in impressions or potentially disapproval. If the GTIN isn’t in the correct format, this will also lead to a disapproval.
Product Type - This has no impact on your website, this is how you categorise your products and displays as a breadcrumb trail in your Shopping feed. It has a high impact on the relevance of your product, and is often neglected in non optimised feeds.
Descriptions - These have a strong impact on onsite performance and product relevance, descriptions should be unique and contain rich keywords in a structure that informs the user.
Google Product Category - These attributes have a strong impact on the relevance, selecting the wrong Google Product Category can lead to low visibility for products, or to show for the incorrect search terms, leading to a poor click through rate which goes on to impact both your Predicted Click through Rate and Historical Click through Rate.
Other Attributes - Size, colour, gender don’t have as much of an impact as the other attributes within Search Terms. However depending on the Google Product Category some attributes are key. For Clothing & Accessories, size, gender, age group and colour are required, and will give warnings in the merchant centre if they are not in the feed. Also, these attributes do factor a lot more into the filtering of the Google Shopping page and if a potential customer filters by a color that you’re not passing in the color attribute, you will vanish from the results.
To help improve the data quality and product relevance, these quick wins we commonly apply and can potentially benefit all retailers.
1 - Duplication of titles - The first check we complete in a feed is looking for duplicate titles, clients who sell variants commonly have duplicated titles that is generally the name of the parent product. Adding in sizes, quantity and colour where available removes title duplication from the product feed and gives focus on more long-tail size, color, material and/or pattern specific searches, which are more likely to convert and improves bounce rate.
2 - Building out Product Types - We often see just one product type added to a product, but expanding this to 4-5 levels of Product Type allows for better filtering of products within Google Shopping Ads campaigns and can double down on search terms. We can take a basic ‘Trainers’ product type and change that to ‘Mens > Trainers > Nike > Black > Size: 10’ using simple rules in the Shoptimised platform.
3 - Make sure your Google Product Categories are correct - Google are very good at predicting the correct Google Product Category when missing for common products like clothing, homeware and baby and toddler products, but for more niche products, or products with titles that contain a common term for another product Google can incorrectly categorise products.
Taking a look how this all comes together in an auction, with three products Product A, an optimised product with a below benchmark price. Product B which is well optimised with a benchmark price and Product C, poorly optimised but with below benchmark price.
We can see how this would be displayed in a Google search for the term ‘Mens size 9 blue nike running trainers’. This is a long tail term with a high chance of conversion if the auction is won, the customer knows exactly what they want, not the exact style but they are looking for a specific type and colour of trainer.