Updated on May 10, 2022 | 3 minute read
It can be difficult to predict the outcome of changes you make to your Google Merchant Centre feed. With lots of options for customisation, it’s important to know the impact of changes you make, especially if you’re getting assistance from a third party.
We’ve come across instances where a client has made a change to their feed which has had a negative impact. We’ve collected some of these examples here, so you don’t have to make the same mistakes.
When we start optimising our clients’ Google Shopping campaigns, we rely on performance data that’s linked to product IDs. When these IDs are changed, we lose any of the associated data.
When it comes to PPC campaign optimisation, data is an invaluable resource. Making sure you keep hold of performance data can be a crucial part of maximising your Shopping channel. Keeping your product IDs as they are and not making sudden changes is recommended to enable you to best improve your campaigns.
Google has a list of attributes, known as product data specifications, which are used to format your product information in the Merchant Center. You can take a look at some of these attributes here.
Some attributes are required by Google and will lead to disapprovals if they’re not included. This is the case for specifications like price and shipping.
For attributes that aren’t compulsory, their removal could lead to a decrease in relevancy for Shopping ads. This could be the case if you removed the ‘brand’ attribute, for example, which could be very useful for search terms.
The [adult] attribution tag can be used to indicate that a product is intended for an adult audience. Items with this specification will only show on Google searches for users who are logged into an age-appropriate account.
This should only be used for the specific purpose of highlighting your product as being of an adult nature. Doing otherwise can severely limit traffic for your ads.
It could be tempting to use the [adult] tag to target a specific age group, but there’s a separate specification for this simply called [age_group]. Using this tag would allow you to target things like ‘adult-sized shirt’ and filter out searches for ‘child-sized shirt’, helping your ads show to the most relevant shoppers.
Bidnamic’s machine learning platform lets us automate the bidding process, and helps us to get your ads in front of the most interested shoppers at the right time. If you have questions about Google Shopping or want to know more about how we can help you maximise your Shopping channel’s performance, book a call with one of our specialists.
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Previously a Google Shopping Specialist, Harrie-Anna now coordinates our Customer Success team in helping clients to understand our technology, how their account is performing, and providing advice for client-side optimisations. She also manages Bidnamic’s onboarding process and our employee book club.