Are you using all available data to manage your Google Ads shopping campaigns? And what about cart data?

What are cart data?

In a highly competitive environment, it’s essential to know the entire customer journey leading to the purchase of your product. Standard conversion measurement in Google Ads can show you if a click on a product led to a purchase, but isn’t it just as important to know exactly what products were purchased? This is all made possible by implementing cart data.

Conversion measurement with cart data allows you to better understand the relationship between ad performance and the customer’s buying process. It also helps you to identify the profitability of your products and campaigns.

How to work with cart data in Google Ads?

After implementation, we start collecting data into metrics that we can add to the product-level report by editing columns. These metrics are not displayed for products without implementing cart data measurement.

Key metrics that are important to know for working with cart data:

• Orders = Total number of purchases attributed to an ad. 
• Revenue = Total revenue from all transactions attributable to a click on an ad.
• Units sold = Total number of all sales from all orders assigned to your ads.
• Average basket size = The average number of products in an order attributed to your ads.
• Cross-sell revenue = Revenue from products sold as a result of advertising another product.
• Product advertising revenue (lead revenue) = Revenue from products sold as a result of advertising the same product.

A particularly interesting metric for us is the “cross-sell revenue”, which shows us revenue from products other than the one we advertised. This metric can then be tracked in reports where we can choose Basket - Items cross-sold. Here we can see exactly which products have been cross-sold.

How to implement?

The first step is to connect your Merchant Center account to Google Ads. Then, choose one of several technical solution options that you use to set your conversion goals. 

1. Implementation via Global Site Tag (gTag)
2. Implementation through Google Tag Manager

The implementation consists of adding the relevant parameters to the source code. We also recommend including a “cost_​of_​goods” attribute to use margin data. 

Well – what kind of recommendation would this be if we couldn’t back it up with real results?

Sanitino

Sanitino is one of the biggest players in the field of sanitary equipment, not only in the Czech Republic but also abroad. We decided to test cart data in one of the biggest markets.

We have a number of performance campaigns running in the account, but the main segmentation, whether Performance MAX campaigns or even DSA campaigns, is into stock products and on-demand products. Our hypothesis was – does it make sense to push stock products in the campaigns as well? This would have been hard to judge, but with cart data we had the answer in no time.

We’ve even found the exact ratio - that is, what % of people who click through to the on-demand product will buy the stock product. And to make it even better, thanks to the cart data, we were also able to find out which products people actually bought. Basically, we confirmed the hypothesis that it makes sense to advertise and promote on-demand products.

In addition to this hypothesis, we discovered some other great findings thanks to cart data. One of them was the average order size in the cart. Thanks to this data, we were able to do particular UX steps to make the e-shop even more customer-friendly.

Now we are going to implement cart data in other countries where Sanitino operates. 

Top-obaly 

For our client Top-obaly, one of the leading players in the packaging and office supplies market in the Czech Republic, we implemented cart data in three countries - the Czech Republic, Slovakia and Poland.

Here, the product feeds give us a lot of space for categorizing shopping campaigns due to their significant size. In our testing, we found the following structure of Performance Max campaigns to be the most profitable in the long term: the first campaign contains products that maintain the best performance, more precisely the return on investment, and we maintain a high target (ROAS) here. The second campaign contains all the remaining products that do not perform so well and therefore we can afford a lower target here.

Cart data helps us better define high and low performers in this Performance Max campaign structure.

In a campaign targeting the best performing products, we can have those products that don’t collect a high number of conversions at first glance, but for example bring in high cross-sell revenue and therefore show a potentially high return.

Higher returns? With cart data? No problem

When selling packaging and office supplies, we primarily target profitability, where we want to reduce costs and in turn increase sales. And that’s exactly what optimizing shopping campaigns with cart data in Google Ads has helped us do. 

Month-over-month, we were able to reduce the resulting PNO by a total of 19% for Performance Max campaigns. 

Abacus

The client Abacus sells electronic devices such as mobile phones, photo traps and cameras, as well as electronic household appliances such as robotic vacuum cleaners, multifunctional pots and kitchen robots under its two brands, Evolveo and Salente. 

In the context of Google Ads shopping campaigns, we are forced to constantly monitor the performance of individual products and adjust the structure of our campaigns accordingly due to the smaller number of products. Because of this, we sort our products into a total of two campaigns, using one Performance Max campaign to promote the best performing products with the best return. The other one, a classic shopping campaign, we use for the remaining/​lowest performing products that do not bring high returns in the long term but we still want to advertise them. 

So, after implementing cart data in this case, we were much better able to identify the products that are worth promoting in the first campaign mentioned above, because customers are buying other, often more expensive, products through them. However, if we had made decisions without all the cart data, we could have manually excluded these products for the second campaign, where they would not have received as much space and we would have unknowingly missed out on potential purchases.

More conversions for Evolveo.cz thanks to cart data

The results after implementing cart data were immediate. In the main Google Ads account, which is the account for the Evolveo brand targeting the Czech market, we optimized shopping campaigns immediately after collecting the data. Using the cart data, we defined the high and low performing products more precisely and adjusted the targeting of the campaigns. 

We obtained a 19% increase in conversion rate and a 5% increase in conversions within the main Performance Max campaign, along with a 6% decrease in average cost per conversion. 

So what does the implementation of cart data bring?

Don’t just rely on basic conversion metrics to evaluate the performance of your products in Google Ads. Using cart data provides a more accurate optimization of your performance campaigns, so you are able to evaluate your products’ performance not only by the number of conversions and their final value, but also by other data such as the number of orders or the average number of items in the cart. 

To conclude we must add that Google’s algorithm does not work with this data in the context of automatic optimization when using automated strategies (conversion maximization or conversion value maximization). Therefore, this is still only extra data that can help the specialists in optimization. 

We can optimize your campaigns too!

Would you like to start using cart data to optimize your performance campaigns, but you don’t know how to implement it? Get in touch and we’ll be happy to help! 

Have a look at our work