Google Shopping ROI varies greatly depending on your products, search volumes, product data quality and consumer demand. Typically, Google Shopping campaigns are measured by RoAS – return on advertising spend. This is simply the total sales revenue resulting from ad clicks divided by the amount spent on ads.

A successful Google Shopping campaign could have a RoAS of 2 or 10 – it all depends on the factors listed above, as well as the margin on the product. In this piece, we’ll dig into the mechanics of Google Shopping and how to maximise your return on investment in Shopping ads.

Knowing what to advertise (and where, and how much, and when)

Omniscience would make Google Shopping campaigns (and much else besides) a piece of cake. Failing that, you’ll need to figure out how to find the best information and insights available, and incorporate those into your Shopping campaign.

Starting with bestselling products is usually a safe bet – but they might not be the highest value targets for investing in promotion on. Look for high margin, low velocity products and experiment with boosting them through advertising spend for high return.

Typically, retailers and brands will put a low level of spend behind large volumes of products and optimise towards those which work. This approach is fine as far as it goes, and will usually lead you to a positive RoAS. However, on its own it fails to maximise the potential value of your Shopping campaign. It fails to account for seasonality, or the potentially varied quality of product data across your product range.

Getting as much information as possible together in one place is essential for really understanding which levers you should be pulling to improve your ROI – this is true of anything in ecommerce, but particularly with paid promotions like Google Shopping. If you are able to slice your data by product type, margin, sales velocity, etc. then you’re halfway to omniscience (at least in Google Shopping terms).

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How to get the best value from your spend – product data quality

As mentioned above, the quality of your product data is a key determining factor in your performance on Google Shopping. Product data is quite an abstract term, so let’s get specific. Google, like any search engine (including Amazon, for example) attempts to deliver relevant results to search queries.

This is true in paid placements as well as organic results. That means that the most relevant products are more likely to be displayed as ads. This in turn means that the required bid to display the ad is lower than a less relevant product. So, the challenge is to give Google all of the information it needs in order to understand all of the terms your product is relevant for. To do this, you need key attributes like colour, material, size, dimensions, weight, etc. to be included in the data feed that you send to the Google Merchant Centre.

The problem is that many brands don’t do this – Google Shopping pulls a limited amount of information, sometimes directly from the website or ecommerce platform. That means less relevancy, which means less exposure and higher bids, hurting key ecommerce metrics like cost per acquisition and return on advertising spend. Ultimately, poor quality product data means your ROI for your Google Shopping campaigns will always be limited.

It’s not just Google that reads your listings in Shopping though – it’s your customer. You need high quality titles (70 characters before Google cuts them off) and descriptions with relevant keywords (up to 5000 characters). Product images are also vital – high quality here is paramount to conversion.

This sounds like (and is) a lot of work to do to optimise listings for Google Shopping. However, brands are increasingly using technologies with AI and machine learning capabilities to allow them to maintain a single product data set, which then gets automatically pulled out and intelligently optimised for individual channels like Google Shopping by the technology itself.

Seeing the big picture

The theme running through all of this is that without a clear idea of how your Shopping campaign ties into the rest of the business, it’s hard to realistically claim a strong return on investment. eCommerce teams need their actions to be fully informed by relevant data. How many Google Shopping campaigns are optimised to avoid promoting products with low margins and high return rates? To avoid such errors and earn a strong ROI, it is crucial to learn how to optimise Google Shopping campaigns.

Chasing impressive-seeming returns on ad spend is tempting, but being able to prove value to the wider business through increasing the profitability of online sales is probably better in the long run. The key is to constantly focus on bottom-line affecting metrics like return rates, profit margin and to focus your efforts where they will make the most difference.
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