crealytics' PPC Blog


The place to be for paid search and Google Shopping

3 Best Practices for Dynamic Remarketing Ads

With Audience Targeting dominating the foreseeable future of Search Engine Ads, familiarizing yourself with Retargeting Options may be useful. Dynamic Remarketing Ads can massively improve your performance by allowing you to help build leads and sales by bringing previous visitors back, who may have left at different stages of the transaction. Before we get to some of the best practices for utilizing Dynamic Remarketing Ads, let’s take a step back, and recap what they are.

What are Dynamic Remarketing Ads?

Since the release of Dynamic Remarketing Ads back in 2013, marketers are able to re-engage with former site visitors with highly customized ads displaying the same and/or similar products they previously looked at. The aim, of course, is to convert them into customers.

So, while prospects are still in the early stages of their purchase, you get to continue engaging with them with tailored messages.

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The Key to Good Product Feed Management

So, you have this fantastic e-Commerce website to sell your products on, but you are also want to sell your products to buyers through the PLAs (Product Listing Ads). How do you get started?

Lucky for you, the technology that manages the products on your website, can usually be repurposed to drive buyers to your site through PLAs… and it all starts with a product data feed.

Getting a Data Feed & Managing it

Many e-Commerce platforms have ways to create an export feed of your product data. Some of the most popular platforms can even send product feeds directly to the marketing channel where you want to advertise your products. This isn’t always recommended because your products need additional valuable data that is not automatically included in the feed. Including this additional data will benefit the marketing of your products.

As far as managing your feed is concerned, make sure to send your product feeds regularly, otherwise, you may be paying for traffic for products that are out of stock, or you may miss out on advertising the newest products listed on your site.

This is where feed optimization comes into play.

Importance of Feed Optimization

There is much to be said about feed optimization & channel specific feed optimization, but for sake of time we’ll let you in on a few of the key optimizations ideas to enhance your feed.

Firstly, having unique keyword-rich titles are essential to matching your target audience search queries to your products. Check that your product titles have nouns that accurately and completely represent each product. For example, when navigating on an apparel website to a shirt page, the page data would not necessarily include ‘shirt’ in the title because you navigated to the shirt page through the breadcrumbs. So, including “shirt” in the product feed title will help increase the relevancy of the product to search queries.

Secondly, we’ve seen numerous feeds with either incorrect or missing data. This makes categorization complex and arduous. So, merchant’s will use a more generic categorization instead of the more granular category. The more granular/accurate the categorization, the better.

Lastly, if advertising on Google or Bing, review how you are managing the bid optimization of your campaigns. You can logically group and segment your products in the feed, and then bid based on these groupings. For example, if you group your products in your feed by ‘product_type’, then you can apply different bid amounts to each product type, giving you more control over how much you want to spend on bids, This should positively affect performance. Through the product feed, you can also create custom labels. Custom labels can be used to further segment data to improve performance. Examples of custom labels – by seasonality, margins, pricing buckets, performance groupings, and more.

Common Feed issues

Through the years, we have seen a wide variety of feed related issues. Some are based on data availability, while others may be based on ability to pull the data from the sources  i.e. from the website, business intelligence systems, or merchandising systems.

Here are some examples of issues we run across:

Feed Formatting

Each marketing channel has specific formatting requirements. If the feed doesn’t include all the channel’s requirements, then some of the products may not be displayed.

HTML characters

You may have seen weird characters such as ‘®’ or HTML characters on web pages. These can lead to confusion and just plain look bad.

Missing & Incomplete Data/ Multiple Data Sources

This is one of the most common problems, that we can spend hours talking about. Top reasons for missing & incorrect data: human error;  multiple data systems not talking to one another about a product; unavailable fields in any of the sources. This reinforces that sometimes, it is necessary to compile your product feed from multiple sources.

Missing Nouns

This is another common issue. As discussed above, the product title sometimes misses a noun because of the website structure. It is extremely important in the feed to have robust, keyword-rich titles.

About Feedonomics

Feedonomics is a software solution that can correct the above common issues and enhance a merchant’s data feeds with speed and at scale. Whether you have a handful of products or millions of SKU’s, we can help you. We have a team of analysts ready to manage and optimize your feeds and significantly enhance your online marketing efforts.

Feedonomics is committed to simplifying eCommerce with expedited and optimized feed management and delivery. Born in the cloud, tested and tweaked in the trenches, Feedonomics solves the technical, usability, and pricing problems of existing alternatives. It supports all major search engines, shopping platforms, and marketplaces in the industry. Feedonomics services a variety of verticals such as eCommerce, hospitality, travel, and job boards.

Learn more about Feedonomics


Go Beyond Standard RLSA lists

Remarketing Lists for Search Ads have always had an important role in the optimization process ever since their release in 2012. Every PPC manager worth his salt, has spent many an hour playing around with list definitions and using them as a bid modifiers.

As marketers, those lists make our lives a whole lot easier. Not only are they a powerful opportunity for segmenting, they also provide a rare optimization element whose borders we can define and refine to our heart’s content. We can add, exclude or create combinations of lists focused on specific behaviors and use them for our ads as long as the number of the users in the lists reach 1000 for 30 days (with a few policy limits).

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Benchmark your Google Shopping Remarketing Performance with this simple script

Remarketing Lists for Search Ads (RLSA) and Customer Match have been proven to drive incremental revenues of 18% or more.

At Crealytics, we’ve seen many accounts and we developed a few rule-of-thumb benchmarks that give us an idea of how much potential we can unleash by fine-tuning the Remarketing strategy – be it via RLSA or Customer Match.

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How to check your RLSA configuration

It is crucial for every PPC manager to properly set up audience lists and their bids. Unfortunately, since there are various targeting criteria with infinite possibilities, it’s easy to make mistakes during the audience creation process.

Our tests suggest that used correctly, bid modifiers on audiences can increase revenue by 16% while keeping ROAS stable. So it’s definitely worth taking the time to get your audience lists setup right.

In this blog post, we’ll share some tips and common mistakes to avoid when creating audience lists.

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A printable cheat sheet to essential RLSA and Customer Match audiences

Remarketing Lists for Search Ads (RLSA) and Customer Match have proven to drive incremental revenues of +18% and more, all while keeping ROAS stable.

One important key to making Audience Remarketing for Google Shopping work is to know which essential audience lists you should define and use.

At Crealytics, we’ve analyzed and optimized many Google Shopping accounts. As a result, we’ve developed a checklist that contains the most important RLSA and Customer Match audiences we typically create and optimize.

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Understanding audience targeting tools and when to use them

The world of paid search is shifting. Advertisers are slowly moving away from targeting search queries to targeting audiences.

It’s not about just showing the right ad anymore. You need to show the right ad to the right user.

In order to take full advantage of this shift, you need to know

  1. Where is the user in the conversion funnel?
  2. What audience tool targets the right kind of user?

This article will walk you through the different audience tools available and how you can use them to reach the right customer at the right time.

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How to make most of Audience Remarketing using RLSA and Customer Match on Google Shopping

The customer journey has become more and more complex. People tend to navigate between Google and a retailer’s website multiple times before they convert. According to our analysis, 46% of Shopping ad conversions have three or more clicks through to the retailer’s website from Google Shopping. Which makes it essential that you keep your brand front and center in the customer’s mind each time they search.

The good news is, Performance Marketers can act on this customer journey using Remarketing List for Search Ads (RLSA) and Customer Match. These tools make it possible to bid differently on shoppers who have interacted with your website and are searching for something relevant on Google again.

Crealytics A/B tests on the incrementality of Audience Remarketing have shown that bidding higher on people deeper in the conversion funnel drives incremental revenues of around 18% or more.

Done right, you’re not just making the sales you would have made anyway with a higher price bid, you’re actually increasing the number of sales generated by targeting highly relevant shoppers.

Take Audience Remarketing to the next level

Google Shopping is ideal for running Audience Remarketing at scale. This two-minute video provides you with an overview of how we bottled up the combined experience of our PPC experts at Crealytics into an automated solution that lets you leverage the full potential of Remarketing.

Crealytics customers have been able to benefit from the Audience Remarketing optimization since April 2016. If you have any questions, thoughts, comments or just want to chat about RLSA, feel free to reach out to your Crealytics account manager to discover more.

Not a Crealytics customer yet? To learn more about how our Smart Shopping Automation tool can help you get the most from your campaigns, get in touch with us on hello@crealytics.com and we’ll be more than happy to tell you all about it!

How are your RLSAs doing right now?

To make it easy to evaluate the current state of your Audience Remarketing Google Shopping campaigns, we’ve put together these resources designed to help you check this task off your list.

More on RLSAs

For more on how to make the most of your audience lists, check out these other great resources.


How to find the mistake in your Google Shopping account

Has the performance of your Shopping campaigns ever changed suddenly with no obvious cause?

If it has, don’t worry. You’re not alone. As a campaign manager, you probably do multiple adjustments a day, many of which won’t show their whole impact for several days. So when something goes wrong, you might need to do a little digging into your performance to spot the mistake and solve the issue.

Here’s how to systematically check your account and find the problem:

Do you have a disapproved Shopping feed or products?

The first step when you see a big performance change in your Shopping campaigns is to log into your MerChant center and use the diagnostics tab. Check to see if there are any disapproved accounts, feeds or items and make sure that all your products are included in the feed and ready to serve.

Are there wrong negatives attached?

If there is a massive change in the overall amount of impressions your account is receiving or if you see search terms in product groups where they shouldn’t be, you may have the wrong negatives in place.

In any case, it’s good practice to review your negatives regularly to ensure you don’t have seasonal negatives place or have excluded profitable search terms.

Do you have the right priorities in place?

If you use our query-level campaign segmentation method to filter your traffic into the right campaign for the right bid, you should check that your traffic split is working. Google always serves the highest priority first, so getting this right is essential.

Check change history for major changes

If your performance change is based on settings and not linked to disapprovals, check the change history for the timeframe when the performance change occurred. Using this information, you can investigate which change might have caused your issue.

You also can compare the performance on an hourly basis to pinpoint exactly where things may have gone awry. Go into the dimension tab and chose the view “Hour of the day” compared to the day before. You’re looking for bids that have been decreased or increased heavily or some other setting change like an added/removed RLSA bid modifier, Device modifier, etc.

Is there an external factor?

Performance changes aren’t always due to something going wrong within your AdWords account. External factors can also have a big impact.

  • A competitor starts offering the same product at a cheaper price or is running a special sale that includes this product.
  • A top selling product runs out of stock and you can’t serve your performance driver.
  • Something in the market changes and there was a decrease in requests for the corresponding product.
  • Google releases an update or changed the format.

This illustration demonstrates the internal and external effects that can influence your account`s performance.

Avoiding problems before they happen

To avoid poor performance, you should check your Merchant Center at least once a day to check for disapproved ads. We also recommend you setup email alerts within the AdWords interface to be instantly informed about big performance changes.

To preserve your sanity, don’t do any intense bid management tasks on Friday or before you go on vacation – you don’t want to be tracking the impact of your changes at the weekend!

Last but not least, in order to accurately attribute performance changes to the right factor, it’s important that you don’t make too many changes at once.

What other factors do you think contribute to campaign performance problems? Let us know in the comments below!


Image testing in Google Shopping: the next frontier

Any digital marketer worth their salt knows that testing, measuring and iterating are the three pillars of a successful strategy.

Google Shopping, however, has proved somewhat resistant to this strategy. Unlike other methods of PPC, it’s technically not possible to properly split test alternative titles by showing two different versions of the same ad simultaneously to different people.

The obvious workaround is to compare two different time periods, and while that does come with some challenges, it’s still possible to draw significant conclusions. To help ensure the different time periods aren’t the reason for any uplift/downswing, we also analyze the total performance of all the products over the whole time period.

In their simplest form, Shopping ads are made up of a Product title, description, category, and image. We’ve had significant success in testing the first three over the years – you can read about those findings here – but image true testing has remained somewhat elusive.

In this post, we’ll discuss the current challenges associated with image testing, what testing we’ve done thus far and the insights we’ve derived.

Image testing challenges

An image can tell you far more about a product than a title or a description and a good one is key to catching the attention of would-be customers. Images are widely believed to be the most important factor in shoppers choosing to click on an ad.

Image testing looks to be the next game-changer for click-through and conversion rates, but it’s still a bit of a black box. This is largely due to three factors that make images difficult to test: categorization, image displays, and time lag.

Image categorization

The first issue comes down to how you categorize your images, to begin with. In fashion, for example, a basic image test would be to see whether images with a model perform better than images with just the product in them. However, if you haven’t already categorized your images in this way already, it will be difficult to know which images to change.

Ideally, you’d change all the images in an entire category. But this also means you need to have an image of both types for every product in that category. Which you may not have, especially if you sell products from other brands.

Image categorization is time-consuming and largely manual. However, without accurate categorization, you won’t be able to run a conclusive test.

Conclusion: Spend time categorizing your images along all the lines you think you’d want to test them

Image display

While image categorization is something completely within your control, whether or not your image is even shown by Google is not.

On the main SERP (Search Engine Results Page) each of the (up to 8) products shown has an image. However, in the Shopping tab products get clustered into just one offer list. This usually happens when multiple retailers sell the same product.

Effectively, what this means is that you cannot be sure your image is being shown – making accurate testing very difficult.

Conclusion: Unfortunately there’s no real workaround for this as you don’t have any control over which image is shown and where. For more general tests you could test only exclusive products not sold by anyone else, in which case you can be sure that your image is displayed

Time lag

Another factor out of your control which makes image testing difficult is the time lag. In this instance, time lag refers to the amount of time after you change the image on your website for Google to change the image on your Shopping ad.

It can take up to 72 hours for Google to index a new image when the accompanying URL is changed. If you don’t change the URL and instead do a server-side image swap, re-indexing the image can take up to 6 weeks!

This time lag makes image testing take a while because, in order to accurately measure the effect, you need to wait for all the images to be indexed and then run your test, change them, wait for the re-indexing and run the test again. The whole process could potentially take months.

Conclusion: Make sure your images have changed before you start collecting data for your test – wait at least 72 hours.

Image testing and insights

Despite the challenges accurate image testing presented, we were able to run a test that gave us an interesting insight into an image’s potential to boost a campaign.

The data we used came from two retailers in the fashion industry. For this first iteration, we looked at the effects of using images that featured a modeled product and a product in isolation.

In total, we changed around 1800 images. Up to 40 million impressions were taken into account, and we overlooked any products that were not consistently available. To help measure the true impact of the new image, we also ran a control stream as a baseline.

Interestingly, we found that while in some cases changing the image had a significant impact on the CTR, in other cases it had very little effect.

When we dug a little deeper we found that whether or not an image change had a significant effect depended on the other images it was displayed beside in Shopping. If the image types in Google Shopping varied regularly (ie there was a roughly equal amount of images with and without a model), there was no significant benefit in having the image feature a model.

On the other hand, if most of the other Shopping images featured products on their own, it was beneficial to have an image that stood out (ie one with a model). We observed a 27% increase in CTR when our image stood out.

This presents another major issue with image optimization: knowing what sort of image will stand out. Figuring out what the most commonly displayed images look like for the top 1,000 products you sell presents plenty of its own challenges.

So close, and yet, so far

As Google gets better and better at figuring out synonyms and directing traffic to the right products, optimizing your product titles will get more and more difficult. Images have the potential to fill that gap.

The potential for image testing goes far beyond whether or not the image contains a model. Perhaps certain product colors stand out more than others. Or image background (white, color, scene) could be important.

For now, it appears that simply having an image that stands out from the competition in some way has the greatest effect. But as we pointed out before, even that isn’t an easy thing to figure out and optimize for.

There’s a long way to go before we get the full picture of what an image does to your campaign. And, honestly, it seems like we may need a few changes from Google before true testing and optimization are possible.

Nevertheless, we’ll keep plugging away at it to see what we can find out. We’ll keep you posted!

What do you think of image testing?