[Case Study] Increasing Google Shopping Performance with DataFeedWatch

  • 4 min read

Google has gone from being a manual work-focused platform to a more automated platform, which means that everyone can create and maintain a simple campaign setup. This means that you (as a marketeer) have to figure out a way to stand out, and do better than the competitors in your market. DataFeedWatch has helped us do that. With an interface that’s better and more capable than Google Merchant Center, we have managed to successfully optimize our customers' product feeds to their best possible version.

KompetenceKanalen is a digital marketing agency with more than 15 years of experience based in the heart of Aarhus, Denmark. We work with businesses of all sizes within every thinkable market.

In this case study, we’ll explain how we optimized our feeds, and how we created our go-to strategy, which is profit margin focused.

Problem I: Raw product feeds bringing mediocre results

We often get new clients that have untouched product feeds, meaning the titles, descriptions, product type etc. are all unedited. Because of that, the copy we receive is not optimized well enough to drive satisfactory campaign performance.

You might ask yourself: “Why optimize my product feed? My product ads are being shown anyway.”

Well, a properly optimized feed helps Google prioritize your products due to attributes such as:

  • A descriptive title
  • A description oriented on the products’ features
  • Product type
  • Product identifiers like GTIN/SKU
  • Color
  • Size
  • Gender 

Feeding all possible information into Google about what your product is, how it's used, what it looks like (color, size etc.), will all come down to determining why it's a better fit for the given search query.

As mentioned before, a well-optimized feed will most likely lead to a shopping campaign performing better than it would with a non-optimized feed. But how do we actually use it at KompetenceKanalen?

We usually use it as a substitute for Google Merchant Center's own feed rules, since DataFeedWatch offers a variety of ways to optimize attributes, and include or exclude products in a very customizable way. We’ve decided to give you, the reader, a look into one of our DataFeedWatch accounts, and how we organize and optimize our title and GTIN attributes.

Solution: Title and GTIN optimization

Title optimization

Our customer had products without the brand and product type in the title, so we created a rule to add them.

We organized the new titles so the brand came first, then the original title, and then the product type at the end. To make sure this only affected the product that was lacking the brand name, we added an [Only If] factor. It excluded all products from this rule which already had the given brand name in the title. As a final touch we made sure to add an [Else] factor, which renamed it back to the original title if none of the above rules had any effects on the product title.

By doing it this way, we made sure that every title which was troublesome and/or lacked the proper information, got what it needed to be able to perform the best it possibly could.

After we uploaded our optimized feed to the customer’s Merchant Center we saw an increase in Google Shopping conversions by a whopping 95,67%.

GTIN optimization    

If the GTIN attribute is populated incorrectly, then your products will be denied. This of course means there is no room for error when the GTIN attributes are filled out.

GTINs can be built of up to 13 characters. To counter the possibility of error, we created a rule for the GTIN attribute that deletes the numbers entered if they were either shorter or longer than 13 characters. By adding this, we made sure that no products would ever be denied by either a GTIN that’s too long or too short. We would rather have a product without a GTIN than a denied product.

Problem II: ROAS doesn’t bring enough insight into profit of conversions

ROAS has been the stable choice of automated bid strategy for Shopping campaigns, and continues to be so. The only problem with ROAS is not having insight into the actual profit of a conversion. A ROAS of 800% might sound and look good, but if the profit margin of that given product isn't matching the ROAS target, then the client won’t profit off of Google Ads.

There is also a POAS strategy, which takes different costs into account, such as delivery cost, salary, fixed costs etc.

At KompetenceKanalen we have created a way to be able to bid for profit with the help of using return on ad spend. How do we do it? We’ll keep that to ourselves for now, but we can show how we set up so you can get the profit margin into your product feed with the help of a custom label and DataFeedWatch.

We used our own bid-for-profit strategy for one of our clients, which led to increased CTR, conversions, conversion value, and ROAS. In no less than two months we managed to increase:

  • CTR with 38,82%
  • Conversions with 95,67%
  • Conversion value with 139,85%
  • ROAS with 29,11%

Solution: Calculating profit margins in product feeds using DataFeedWatch

To be able to calculate the profit margin of a product in DataFeedWatch you have to be able to pull out the product cost and product price from the client’s CMS. It doesn't really matter whether it is with or without VAT, since you’re able to subtract the VAT within DataFeedWatch. In this example we’ve pulled the price without VAT, which it’ll be referred to from now on.

This step might require some manual work from your clients’ side, since the product cost is usually not a standard box to fill out.

After that has been done, we can move to DataFeedWatch and calculate the profit margin.

To get the profit margin into the product feed, you’re going to need to do so in a custom label of your choice. When you’ve chosen a specific custom label to work in, you’ll have to follow the steps in the picture below. 

Rename to the sales price without VAT (which is the “pris uden moms” in the screenshot below), to be able to calculate the profit margin. After that we’ll click on “Edit Values”, which is the blue button on the right hand side.

We’re then going to get into how to get the precise profit margin percentage into the feed.

To be able to change or edit what the ‘price without VAT’ is, you’re going to have to choose the mapping type “Recalculate”. This makes it so we can use the existing field (pris uden moms) as a base for our calculation. We’ll then subtract ‘cost per item’, and divide by ‘price without VAT’ (pris uden moms). This is the standard calculation to get the profit margin of a product.

If you pulled the price with VAT, this is where you’ll have to subtract it. Do this by adding a new rule within the Edit Values, and multiply by 0,20. 

Important: This has to be done before the other calculations, and should be the first rule.

Basic Example

Let's say our ‘price without VAT’ is 100, our cost is 50, then the previous calculation results in 0,5. The next two steps are to get the profit margin in a complete percentage number, such as 50%.

We use the mapping type “Round”, with an input to 2, to only get 0,50, and not 0,501893. We then multiply by 100 to get the percentage.

The two other factors for our rule are [Only IF] cost per item is greater than 0 and an [Else] factor that adds a static value if the rules above fails.

Since DataFeedWatch fetches and uploads your feed everyday, like it would with a regular CMS to GMC setup, all future products will automatically be uploaded and categorized into their respective profit margin group. This means that setting up this profit margin calculation is a one time thing, and won’t have to be done every time new products enter your feed.

About DataFeedWatch

DataFeedWatch by Cart.com is the top-rated global product feed management platform that enables eCommerce brands, retailers, and digital agencies to drive multichannel growth. Merchants on both custom solutions and popular shopping carts, like Shopify, WooCommerce, and Magento (among others), can choose from 2000+ integrated shopping channels, affiliate networks, and marketplaces in 60 countries (such as Google, Facebook, Criteo, Amazon, and more). Major global brands like adidas, Decathlon, and KENZO have used DataFeedWatch to improve product performance across channels and expand to new markets. Sign up for a free trial today and receive guided onboarding to get started.

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