The first mention of Performance Max dates back to 2020, but it is still considered the new kid on the block for businesses and marketers alike.
For many business owners, and especially eCommerce store owners, there has always been that search for the Holy Grail to simplify online advertising. With many options available, it was difficult for many to choose where to start. For those unfamiliar with the Google Ads ecosystem, it became a very expensive lesson, with many chalking it up as an expensive lesson in futility.
Then came a shift in the landscape, with the release of their automated behemoth, Smart Shopping. This new campaign option offered the likes of many amateur shop owners a simplistic way to take their first steps into the online advertising universe. This made for a simplified process for users to easily showcase all their products, putting most of the decision-making in the hands of Google.
Whilst this provided some relief for many, there were still boundaries. For one, the ability to extract pertinent data to review and assess was one of them, as was providing the opportunity to the inexperienced to expand into the other Google advertising ecosystem (YouTube, Display, etc.) where their products may flourish. This provided a void for advertisers to expand their reach and required something to fill the gap.
That was until now!
With the announcement that Google is sunsetting the Smart Shopping campaign, the talk moved quickly to how this will be handled. There was the mention of a “one-click” solution to transition across to this new kid on the block, which was music to the ears of those still not familiar with the Google advertising network. Whilst this may sound like the perfect solution for most, not having that understanding of what you’re working with, could be the difference between the success and failure of your efforts.
This is why I want to equip you with a full understanding of what Performance Max is, and how you can go about implementing the moving parts to set it up for success.
Introducing Performance Max
Performance Max is the latest installment from Google’s war chest of advertising tools. Unlike other automated options of its predecessors, Performance Max harnesses the power of its advertising ecosystem and enables advertisers to serve their ads across YouTube, Gmail, Discover, Search, Shopping & Display networks from a single campaign.
In their own marketing efforts, Google has made it sound simple to get these new campaign types in place, and in some ways, they have. Simply provide your ad copy, upload inspirational product images, add links from your YouTube account, and connect to your Google Merchant Center and you’re only a button click away from unleashing its power. From there, Google’s all-powerful machine learning systems will seek out and find the perfect customer and serve your ads to whichever platform they may be using at the time.
So now, instead of having to create multiple ads and assets for specific channels, you get to “throw it all together” and let Google work its magic, managing its potential to full effect across their advertising landscape.
Performance Max campaigns leverage their automated bidding and targeting technology, creating tailored ads and putting them in front of customers, no matter where they are on the Google Ads network. From the average person, this sounds too good to be true, especially those that are happy to let Google have complete control over their funds.
To help you get the most out of Performance Max, let’s break it down into the many parts that go into making it work.
Anatomy of a Performance Max campaign
Unlike other previous campaign types, such as Search which focus on text-based queries, from this single campaign, you can now show ads to other platforms that include Shopping, Search, YouTube, Display, Local, Gmail and Discovery.
As an automated campaign type, all you need to do is add your assets, select your goal and let Google proceed to do the job by showing your ad to the right person, on the right network, to give you the best possible chance of success. It sounds like the holy grail of advertising and whilst you will see results, having a better understanding of how to put it all together will go a long way to its success.
So where to begin.?
Whilst you’ve read this far, let’s presume that you have a good understanding of the basic campaign settings for creating a Google Ads campaign, including your budget, location, language, etc. As these are generally pre-determined when you plan your campaign and the goals you want to achieve, there are some areas to take into consideration when doing so.
With Performance Max campaigns, you have 2 options with the bidding strategy. Maximize Conversion or Maximize Conversion Value. While there are only these options to choose from, your success is based on choosing the right one. Whichever goal aligns with the outcome you are wanting to achieve, we suggest not putting in any limitations such as a target ROAS or CPA when starting out, and allowing Google to “spread its wings” to jump-start the campaign.
There is one caveat within the settings and that is the Final URL Expansion section. If there is a page on your site that Google believes is more relevant than the landing page you want to direct them to, it will send them there. This does take some control out of your hands, but it is based on your historical conversion data combined with the characteristic profile data it has on users. If there are pages that you specifically do not want to be included, you have that option through the Add the URLs you want to exclude option.
Asset groups can be similarly described as the “new ad groups” of these Google Ad campaigns. Within these asset groups, you have the infrastructure to create themed assets, including imagery, video, shopping products, and text ad copy, that will provide an inventory for Google to showcase across its advertising platform. Keep in mind that if you are not utilizing your own video or YouTube channel, Google will create one as part of the asset group. If this is not an option, you can contact your Google rep to remove the Performance Max campaign from the video network.
Within each asset group, you can manually select which products you want to be served up across the Google Shopping network. These listing groups can be segmented by Category, Brand, Item ID, Condition, Product Type, Channel, and Custom Labels. While there is no right or wrong way to set these up, I suggest breaking them down so they align with your themed Asset Group. For example, you may have an Asset Group for Nike and it would make the most logical sense to only include the range of Nike products, especially if you’re using keywords as an audience signal to find your customers.
For those a little more advanced, you can take advantage of using custom labels to get granular with the products that you want to include, such as top sellers, on-sale items or even by a price point. Aligning your products is a key element here, so ensure you spend time looking at how you want to segment these out in comparison to the audience that you will be targeting.
Creating these signals will guide Google’s machine learning models on the way to better optimize your campaign. One caveat with this is that these campaigns may show ads to audiences outside of these signals if Google’s machine learning indicates that there is a likelihood of attaining a conversion that falls within your goals.
When starting out, it’s always good to have a solid foundation of audience signals in place to get things going. This initial information is going to help your campaign ramp up and optimize performance faster. Whilst having all your products and signals in one group is the simplest way to start, ideally, every audience should get its own asset group and intended audience. These audiences should include:
- All website visitors
- Competitor terms and website
- In-Market with a combination of relevant and “outside-the-box”
- Customer match list or All converters
- Converting keywords
These are not the specific audiences that you’ll be targeting but the characteristics of those audiences Google will use to find the right customer.
*Top tip – If you’re looking to create a large number of asset groups by combining categories and audience signals, Google Ads Editor is going to be your best friend. Whenever you duplicate an asset group from within the Google interface, the Listing Group defaults back to all products and you’ll need to segment it each time. If it is duplicated in the Google Ads editor, it will retain the original segmentation of the products.
All Done, What’s Next?
Not quite but you do need to understand that these new campaigns take time to work through the learning process, gathering all the data from your assets and signals, to achieve the goals you have in place. While this doesn’t mean you won’t see some early wins, and you should, it just means you’ll have to be a little more patient. Generally speaking, this can take up to 5-6 weeks from the time you hit the GO button for new campaigns, which for some can be a nervous period.
Now, this doesn’t necessarily mean you can walk away and let it do “its thing” for the next few weeks. As they say, a champion team will always beat a team of champions, and this is no different when talking about your Google Ads account. Relying on a single campaign, as many did with Smart Shopping, can be fraught with danger. Whilst Performance Max campaigns utilize all of the advertising networks that Google has to offer, you want to ensure that you’re not missing any opportunities.
For starters, a Brand campaign.
I suggest running a branded search campaign alongside to ensure that Performance Max is not taking all the glory in sales and converting the low-hanging fruit of those people looking for your business. Although there is hope that it will eventually become available, you’ll still need to speak to your Google rep about adding your brand name, and its derivations, as negative search terms to Performance Max.
Running a standard shopping campaign can also be beneficial, especially if you have core products that need to be front and center with your audience. There is a lot more control, and data to analyze, which can help with improving the overall account, too. The Performance Max campaign will help with “filling in the gaps”, especially with the additional channels it has to market to.
You should also look to run a Dynamic Remarketing campaign. Unlike the previous Smart Shopping that so many were used to running, the remarketing component was far superior, and a dedicated remarketing campaign will give you far more information to review and make decisions.
We live in a media-rich world, where platforms such as Instagram and TikTok rule. The reason they are the kings, or queens, of the social media world is the use of visual creatives. This is no different when it comes to Performance Max campaigns. Make sure you keep a stock of fresh visual images and videos and implement them into newly created themed asset groups for further testing.
But won’t this reset the learning cycle?
Thankfully, it won’t reset the learning phase for the entire campaign, just the newly created asset group.
Will Performance Max campaigns take traffic/sales from my other campaigns?
The short: it depends. Whilst they are known to “steal” impressions and clicks from other campaigns, there are reasons why. Part of the reason comes down to your ad ranking across all your campaigns. For Search based campaigns, if there is no exact match term in other Search campaigns, then it will be based on the highest ad ranking in your account. When it comes to competing against other YouTube and Discovery campaigns, it’s different again.
To clear up the confusion, here’s a table to give you an idea of which campaign will show:
|Campaign #1||Campaign #2||Campaign entered in the auction|
|Search campaign that matches user query exactly||Performance Max||Search Campaign|
|Search campaign that does not match user query exactly||Performance Max||Campaign w/ higher ad rank|
|Standard Shopping campaigns||Performance Max||Shopping Ads on Search/Shopping: Performance MaxShopping Ads on search partners: Performance MaxShopping Ads on Gmail & YouTube: Campaign with higher ad rank|
|Display campaigns (with no feed)||Performance Max||Campaign w/ higher ad rank|
|Display campaigns (with feed)||Performance Max||Dynamic remarketing: Performance MaxAll other display ads: Campaign w/ higher ad rank|
|Video campaigns||Performance Max||Campaign w/ higher ad rank|
|Discovery campaigns||Performance Max||Campaign w/ higher ad rank|
|Local campaigns||Performance Max||Campaign w/ higher ad rank|
|ACE campaigns||Performance Max||Campaign w/ higher ad rank|
As you can see, getting started with a Performance Max campaign isn’t as difficult as it may seem, and for those that are either new to Google Ads or crossing over from Smart Shopping, that journey has been made simpler.
Whilst the above will get you up and running, there is still much that can be done through review and testing, as well as working on accompanying campaigns to complement the performance of your account.
If you’d like to find out how to get the most out of Google Ads for E-commerce, you can contact me at Digital Darts.
The post Your Guide to Winning with Performance Max Campaigns first appeared on PPC Hero.
The pandemic and resulting consumer behavior changes have led to a new era of eCommerce, with people around the world increasing their reliance on online shopping and brands investing far more money and attention in direct-to-consumer activity. It’s thought that 78% of D2C brands have increased their marketing budget over the past few years compared to only 60% of traditional retailers.
With so many businesses turning to eCommerce to drive overall business growth, there is far more focus on the end-to-end customer experience, CRM, and broader data usage to help maximize the value of paid traffic. Here are a few of the key areas you can focus on to help drive success;
Building a Unique and Engaging Brand Experience
With so many new brands and so much competition, traditional brands are now looking to build better experiences, with incoming paid traffic being a big consideration for net new customers. Key aspects for new users coming from paid channels include more considered landing pages (with more story-telling and engaging branded content – there are some good examples here) and initial user journeys (curating products better and allowing for more engaged users, etc,).
Often there’s a need to educate users, leading with content, particularly if traffic has been driven through upper funnel paid channels. Experiences should be built around audiences with a focus on engaging content and unique user experiences. Think about how you’re telling a story and selling the brand to users from different campaigns and try to make your site unique, interactive, and deliver engaging content. A great example of this is Asket, which sends paid traffic to more curated landing pages (as per this example) and also does a great job of telling the product and brand story on their product detail pages.
This is just one example, but brands like AllBirds and On-Running are also really good at this. More traditional brands need to catch up to the DTC brands here. Lots of our clients are now investing in this area.
Better Post Purchase Experiences
With new DTC brands emerging every day, driving repeat purchases is key to allowing for higher CAC and scalability. Key considerations here include up-sells through a strong check-out experience, post-purchase considerations, and creating a strong loyalty offering to drive second and third purchases. It’s essential to think about all the touchpoints, and how to use customer data wisely once it is acquired.
- Tiering customers based on spend and enabling different rewards
- Providing loyal customers with exclusive content and offers
- Creating very considered CRM flows to nurture the customer
- Creating a space that allows your customers to become brand advocates
Optimizing the Initial Landing Experience for New Users
It’s important to have different landing pages for different groups of users and campaigns which reflect different objectives and brand positionings. Consider things such as data capture prompts for paid users (based on new users), quick links for easy navigation (to considered pages that will aid the journey), and capitalize upon the opportunity to personalize the user experience.
For example, for a user who was driven to the site via Google Shopping, showing more prominent cross-sells or highlighting a price match CTA is likely to hold more weight than a user who came direct (these users are often more price sensitive so it’s important to try and maximize these kinds of things).
The importance of A/B testing really comes into play here to better understand how to maximize the traffic
Utilizing and Obtaining More First-Party Data
One of the bigger shifts in the market is changes with regard to privacy and stricter regulations coming into play. Last year’s changes around iOS 14 and Google moving to a cookie-less world pose new and continued challenges to advertisers.
Across paid channels, adopting your 1st party data will help drive greater success. Creating segmentation such as VIP or At Risk will allow you to target more relevant content. Capturing that data is also increasingly more difficult, in addition to pop-ups on site as mentioned above, it’s good to consider value exchange and rewarding data sharing, particularly on social channels, enticing new customers to share details or encourage re-engagement.
We are increasingly seeing brands become more creative with the way in which they do this, with things such as engaging quizzes to aid product fit, etc. The data from this can be fed into a customer property within your CRM.
Continue to Add Value in a World of Automation
It seems over the past 18 months, Google Ads has had a complete overhaul. Now with Performance Max adoption soon to become mandatory, focus on continuing to add additional value. Consider how you can maintain a level of control over the catalog and display ads within campaigns, and how the users will experience the brand once they land on site. Supply the campaigns with a strong set of assets, and build out and test relative asset groups to better understand what resonates best with the user. There may be some key learnings you can take here, with regard to site merchandising. Finally, think about how you can incorporate business data, best sellers’ insights, or margins for greater efficiency.
Enhancing your Activity
One of the biggest trends we’ve seen across our clients of late is the diversification of channel mix and reaching further upper funnel audiences. The likes of TikTok, Snap, and Pinterest have been of particular focus. However, one of the bigger challenges is justifying the role these channels have to play to key stakeholders when typically ROAS is lower here. CoS has been a key metric that has allowed us to do so.
Using CoS allows us to understand the wider impact of paid marketing on-site revenue. Scaling spending whilst keeping CoS flat is the overall goal – but when spending more and assessing your CoS and overall revenue you can begin to understand the impact of additional or less spend on-site revenue.
We’d still recommend measuring and optimizing towards platform ROAS to ensure campaign activity is as effective as possible. However, this allows you to understand the diminishing returns of paid activity and to forecast more accurately how your paid activity can contribute to eCommerce results as you invest more.
Another key factor is that a lot of brands will monitor platform ROAS on a small lookback window (7 days on Facebook for example). Whereas a number of brands will have a much longer path to purchase and using CoS allows you to account for media spend and revenue over a much longer period
Consumers expect online experiences to be smooth and friction-free, and with an ever-competitive marketplace, it’s important brands put the time in to ensure they stand out and speak to their audience.
Creating quality content both on-site and across paid channels is a great way to drive traffic. It’s also critical to identify the ways in which you can keep your audience engaged, driving greater data capture and increasing brand loyalty. And finally, ensure you are always testing across your site and media mix, helping drive insight into actionable next steps for greater success.
The post Maximizing eCommerce and Performance Marketing Activity first appeared on PPC Hero.
As AI begins to shape the landscape of digital marketing, content managers, copywriters, and digital marketers are starting to explore its potential applications for copywriting.
It’s been predicted that AI would take over a lot of the grunt work associated with creating and managing content – from doing basic research to developing detailed editorial calendars.
Others believe that machine learning can complement human skills and help writers produce better content. So far, artificial intelligence hasn’t quite taken over copywriting as a whole, but it is nonetheless having a huge impact on it in significant ways.
It’s not just copywriting that has seen the beneficial effects of AI. From AI-powered robo advisors that help improve return rates on different investments to impressive video filters that make social media more fun, pretty much all industries are finding ways to use this evolving technology.
Considering this trend is showing no sign of stopping, digital marketers need to understand how AI is impacting copywriting and what kind of opportunities this technology creates for their businesses.
Let’s explore four ways AI is changing the field of copywriting and discuss how marketers can take advantage of these changes to improve PPC performance.
A Short Introduction to AI
AI is short for artificial intelligence, a field of computer science and engineering focused on creating intelligent machines that work and react like humans. In other words, AI involves making computers smarter – something they’re already very good at, thanks to their huge data processing power and ability to learn from experience rapidly.
Put simply, AI works by using algorithms to analyze data so that computers can understand it better. This data might be in the form of text, images, or videos. Once the computer has understood the data, it can then use this information to carry out certain tasks – such as recognizing objects in pictures or understanding natural language.
Most AI algorithms work much in the same way. They start by learning from a data set we humans provide (a process known as “training”). The computer runs a series of calculations during training to develop an equation that relates all the data it was trained on. Then the AI uses this knowledge to make predictions about new data (known as “inference”).
In other words, an “AI” is no more than a piece of software that basically wrote itself to perform a particular task (like copywriting) after training on a given data set and following certain guidelines given by the programmer. Since no two data sets (collections of pictures, videos, or text) are likely the same, no two AI software are ever the same either, even if both were developed by the same publisher.
Companies with large volumes of data on their users can leverage AI for different purposes, from generating sales to improving customer satisfaction. For example, credit card companies and other banking and fintech businesses have been using AI to provide users with insight into their own spending habits, helping them budget more effectively.
Other industries use AI to detect possible scams and frauds based on behavioral patterns.
AI in Copywriting
Copywriting is one of the fields where AI has made a big impact. A copywriting AI is a writing assistant that can help you with the task of creating content. Copywriting AIs are usually powered by natural language processing (NLP), a branch of AI that deals with understanding and generating human language.
There are different types of copywriting AIs trained for different purposes. In general terms, they can be broadly classified into two groups: content generation and editing software.
A content generation AI is an AI that writes original content based on input from the user. These AIs are usually trained on a large data set of human-written text, such as news articles or blog posts. And when I say a large data set, I mean large. For example, Jasper (previously known as Jarvis) is one of the best AI copywriting tools trained on a data set of roughly ten percent of the internet’s written content.
Content generation AIs work by understanding the user’s input (usually in the form of keywords, although the more sophisticated software clearly understands instructions) and then generating new text relevant to the input. The generated text is usually not perfect, but it gives the user a good starting point that can be edited and improved upon.
Editing software, on the other hand, is designed to help users improve their writing by checking for grammatical errors and offering suggestions on how to rephrase certain sentences. These AIs are usually trained on a data set of well-written text, such as books or articles from high-quality websites. Some popular editing software includes Grammarly and ProWritingAid.
How AI is Used in Copywriting and Digital Marketing
Automated content generation tools have taken the digital marketing landscape by storm. In particular, they have been a godsend for content marketers and SEOs who are always on the lookout for new and original content at the lowest cost possible.
The rise of AI has also led to new tools and strategies for copywriting and digital marketing. Here are some of the ways AI is being used in these fields:
#1.) To Enhance Copywriting Productivity
Copywriting AIs can help content marketers and copywriters be more productive by taking on some of the grunt work involved in creating content. For example, content managers can use a copywriting AI to generate ideas for new articles or blog posts based on a set of keywords provided by the user.
The AI can then produce a list of potential topics that the user can choose from. Similarly, once a copywriter chooses a topic to write about, they can then use the same AI to generate an outline for the blog post if that’s what they plan to write.
You could keep breaking each section into subsections to go as deep into a topic as possible. Finally, once you’re satisfied with the outline, you can ask the AI to write out the content under each subheading.
By fact-checking here and there and ensuring that everything ties into a seamless narrative, you could have a high-quality, 2,000-word blog post fully written and proofread in under two hours.
Talk about productivity!
#2.) Editing for Spelling, Grammar, and Style
Editing AIs can help copywriters improve the quality of their writing by checking for spelling and grammar errors, as well as offering suggestions on how to rephrase certain sentences.
For example, suppose you’re writing an ebook about the benefits of nano-influencer marketing, and you want to make sure that it’s error-free. You can run your document through an AI editing software such as Grammarly or ProWritingAid, and it will highlight any errors in your text. The software will also offer suggestions on fixing the errors, making your message clearer, and adapting it to a particular writing style.
In addition to correcting errors, you might also find that your text sounds more polished after running it through AI editing software. This is because this software is often tuned to identify style issues such as overuse of certain words or phrases, sentence length variation, and so on.
Making these style corrections lets you ensure that your writing sounds natural and easy to read, which is essential.
#3.) To Improve Conversions
Copywriting AIs go far beyond writing blog posts and correcting your grammar. Since they’re trained on massive amounts of online written data, and much of that data is marketing copy, they’ve become increasingly efficient at producing highly-converting copy based on different frameworks.
This means it will only take you minutes to craft an ad copy based on the Problem-Agitate-Solution (PAS) framework or the classic Attention, Interest, Desire, Action (AIDA) framework. Or you could go for the Before-After-Bridge framework and see which one works best for your audience.
This is particularly appealing to PPC marketers who need to write the most eye-catching and compelling copy to attract the attention of short-attention-spanned internet users.
But, how do you know which framework works best for your audience and leads to more conversions?
The answer is A/B testing, an experimental technique to compare two versions of a web page to see which one performs better. A/B testing has long been the gold standard for optimizing conversion rates, but it can be time-consuming and expensive, especially for small businesses and startups. However, copywriting AIs make this extremely easy since writing out entire ads in different frameworks, styles, and tones only takes a couple of minutes.
Also, there are now AIs that specialize in conversion rate optimization (CRO). These work by constantly testing different versions of website copy and design elements to see which ones result in the highest conversion rates.
These tools essentially automate A/B testing to make it cheaper, faster, and more effective. A good example of this is Unbounce Smart Traffic, which was the first AI-powered CRO tool to hit the market. Many more followed suit.
#4.) Generating Targeted Content
Digital marketing is all about creating content that resonates with your target audience. You can use copywriting AIs to generate targeted content for your specific niche if you know your audience well. You can do this simply by instructing the AI to write a copy for that particular audience.
But that’s not even half of it. Other variations of these software tools, such as evolv.ai, tweak and adapt the ad and landing page content dynamically for every user based on a set of predefined criteria such as location, keyword use, and other factors. This is micro-segmentation marketing on steroids, and it’s only possible thanks to the way AI understands where each internet user is coming from.
#5.) AI for SEO
We already discussed the power of AI for improving copywriting productivity by helping writers come up with new topic ideas based on given keywords. But how do you know which keywords to target?
This is where AI comes in handy again. You can use AI tools for contextual targeting purposes: they work perfectly with keyword research and help to develop a list of relevant keywords that you can then target with your content.
In addition, copywriting AIs are also getting better at understanding SEO best practices and can help you tweak your copy accordingly to make it more search engine friendly. Surfer is one of the most popular SEO optimization tools out there, and, guess what? It’s also an AI.
The Bottom Line
As digital marketing evolves, copywriters and content managers must embrace new technologies like AI to stay ahead of the curve. In particular, AI can help content managers and digital marketers in every stage of content production and delivery.
From coming up with relevant keywords to target and using them to come up with topic ideas and relevant subtopics, to actually crafting the content itself.
Additionally, You can use AI for several other important tasks, such as SEO optimization and improving conversions.
By understanding how AI works and using its capabilities to your advantage, you can create more effective PPC campaigns that connect with your target audience and improve your PPC performance. If you’re not using AI for your digital marketing efforts right now, you’re already falling way behind.
The post Five Ways AI Can Improve Copywriting and PPC Performance first appeared on PPC Hero.
It’s important for businesses to have the insights they need to drive more conversions on their websites. But rising expectations and regulations around user privacy can make it hard to meet both performance and privacy needs. We’re continuing to invest in solutions to help you find that balance.
Server-Side Tagging in Google Tag Manager allows you to move measurement and advertising tags off your website and into a secure server container. This helps protect your customers by restricting access to their information, and helps increase conversion rates on your site by reducing page load times.
To ensure all businesses can use this feature, Server-Side Tagging now works with any cloud or server provider that supports Docker — an open source platform for developing and running applications. We’ve also integrated Server-Side Tagging into more Google products and services to help you move more tags off your website and achieve better site performance. With these improvements, we’re moving Server-Side Tagging out of beta and making it generally available to all customers in Tag Manager and Tag Manager 360.
Support for more Google advertising products
Now, when customers interact with your site, a single client-side tag can activate multiple tags for these products directly in your server container. This means you’ll have fewer tags on your site, which can help improve your site’s page load time.
Integration with other privacy solutions
Marketers often ask us how to use Server-Side Tagging with other privacy solutions like Consent Mode and enhanced conversions. Consent Mode helps you customize how Google tags behave before and after users make their consent decisions; and enhanced conversions help you use consented, first-party, user-provided data to better understand how users convert after engaging with your ads.
We’re now making it simpler to use these products together. Advertisers with Google Analytics 4 on their sites will soon be able to use enhanced conversions in Google Ads without needing to add additional tags to their site. And once you’ve set up Consent Mode, any Google tags implemented in your server container will automatically respect consent choices that users have made on your website.
We’re also making it easier for you to ensure that user data is handled according to your security preferences. Server-Side Tagging automatically anonymizes your users’ IP addresses before the information is shared with Google’s reporting tools. And in cases where you need more control, you have the option to eliminate users’ IP addresses from your data completely before they’re shared.
Success with Server-Side Tagging
Since launching Server-Side Tagging last year, we’ve seen businesses around the world use this feature to uphold higher expectations around user privacy and drive better marketing performance.
Nemlig, Denmark’s leading online grocer, saw a large rise in visitors to its site as people turned to online shopping and home delivery for their daily essentials last year. This resulted in longer page load times, which negatively impacted conversion rates on Nemlig’s site. After adopting Server-Side Tagging, the company was able to move tags from the browser into its secure server container, improving its page load time by 7%. Read the full story here.
Square has also found success with Server-Side Tagging. The San Francisco-based company helps businesses of all sizes reach buyers online and in person, manage their business and access financing. Since implementing Server-Side Tagging, Square has seen a 46% increase in reported conversions.
Server-Side Tagging is our preferred method for sending measurement data to our marketing partners. It allows us to collect data from the website in a secure manner while improving data collection and enabling event enrichment.Doug Logue
Sr Product Manager of Marketing Technology, Square
With Server-Side Tagging, you can improve both user trust and website performance. As we continue to work on new features and updates, our goal is to help you achieve your privacy and performance goals across all of your measurement needs.
Once you’ve created content in the form of Web Stories, you’re probably wondering who your Web Stories are reaching and whether they’re resonating with your audience. Google Analytics and Data Studio are easy-to-use tools that help you understand how your Web Stories are performing on your website — or anywhere else on the web.
Viewing Web Stories performance in Google Analytics
The first step to measuring your Web Stories performance with Google Analytics is to set up tracking. Most Web Story editors, including Web Stories for WordPress, MakeStories, Newsroom AI and others, provide a simple way to add tracking in Google Analytics for each story created. You’ll need to provide the UA Tracking ID associated with the Google Analytics property you’re using for Web Stories.
Once your Stories are being tracked, key performance metrics will become available via the Events report in Google Analytics. This report is accessible by navigating to Behavior > Events > Overview in the navigation bar. The metrics available include:
- Story Starts: A measure of how many users started reading your Story. These are reported as pageviews in Google Analytics.
- Time Spent: A measure of how long users spend reading your Story, on average. This metric is helpful when determining how engaging your story is. This is reported as Avg. Time on Page in Google Analytics.
- Story Pages Viewed: A measure of how many users read each page in your Story. This can be a helpful indicator to determine how far users get into your Story and where they might lose interest. These are reported as story_pages_viewed events in Google Analytics, and can be found in the Events Report.
- Story Completions: A measure of how many users completed your Story by reaching the last page. These are reported as story_completion events in Google Analytics.
The Events Overview report in Google Analytics will report the story title under Event Category. You can click into each of your Stories listed to view data for each of the metrics above by selecting Event Action as the primary dimension.
Even simpler access to Web Story performance insights with Data Studio
The Web Stories Insights dashboard template in Data Studio provides an overview of your Web Stories’ performance by pulling data from Google Analytics into a simple and visually engaging report. The dashboard displays several essential metrics to consider when evaluating performance, including:
- Key Metrics: Story Starts, Page Views, Time Spent and Completion Rate
- Audience Metrics: Age, Gender and Device breakdown across all stories published
- Top Stories: Your top 10 stories during the selected time period, sorted by Story Starts
- Traffic Channels: An overview of where users are finding and reading your Web Stories
- Story Level Performance: Key metrics and a breakdown of pageviews for a specific story are available on the ‘Story Level’ page.
Anyone can access the dashboard by visiting goo.gle/web-stories-insights and selecting your Google Analytics account via the Click to Select your Data dropdown. Note you’ll only have access to analytics that your Google account is linked to, so be sure to verify which account you’re using. You can also create a copy of the template and adjust it according to your specific analytics needs.
We hope that Google Analytics and Data Studio will help you improve your Web Stories for your audience.
“Will we ever be able to put search marketing strategy in the driver’s seat?” This is almost every search marketer’s dilemma as the community continues to remain at the mercy of Google’s algorithms and updates.
SEAT S.A, the Barcelona-based multinational automaker part of the Volkswagen group have innovated a testing model that is driving growth for its brands, SEAT and CUPRA in the European market. While SEAT is the young, cool and urban brand that offers cars with striking designs and several mobility solutions – CUPRA is an unconventional brand, which is defined by its progressive design and the performance of its electrified models.
We spoke with Corinne Calcabrina, Global Media Manager at SEAT S.A, Sophie Santallusia, Global Paid Search and Programmatic Director, and Alejandro Sebastian, Global Search Team Lead at PHD Media Spain to discuss the ‘Performance innovation program’ (SEAT S.A’s testing model) and its value add to the businesses.
A fast-paced industry
Digital is a fast-moving sector and search is always reinventing itself with new formats and everchanging ways to create and manage accounts. The teams at SEAT and CUPRA had several pain points:
1. Staying on-top of all innovations and changes in the industry
“We needed to become first movers who actively capitalize on opportunities that appear. To ensure this our teams needed to take advantage of search space dynamics, apply best practices, and gain a technological and intelligence edge over the competition.”
– Corinne Calcabrina, Global Media Manager at SEAT S.A.
2. Improving visibility of the team’s hard work
“While we were putting all these efforts, we wanted to improve our team’s visibility. While we are busy becoming the best performing channel, always reinventing, working towards results and efficiencies, we often miss the glitter of other channels. Adding an official scope and framework means we get to report and showcase our achievements.”
– Corinne Calcabrina, Global Media Manager, SEAT S.A.
3. Maintaining performance and improving efficiency
“As the best performing channel on a last-click attribution model, we were also facing multiple challenges. The pandemic lockdowns and microchip shortages made search performance improvements a constant, ongoing must-have. This meant decreasing the cost per click (CPC) and improving the cost per acquisition (CPA) were always core reasons to develop such a testing model.”
– Corinne Calcabrina, Global Media Manager, SEAT S.A
Putting testing in the driver seat: The SEAT and CUPRA Performance innovation program
The SEAT S.A testing model, ‘Performance innovation program’ was designed to align with the inherent love for innovation that runs at the core of SEAT and CUPRA brands. The testing model was built centrally to maintain brand focus on the strength of paid search – improving cost efficiencies and accelerating performance.
Corinne and her team at SEAT S.A and their agency, PHD Media reviewed brand strategies for SEAT and CUPRA respectively, their performance, and local needs. They created a framework that provides structure, helps the brands expand their market share, and deliver central visibility on the testing results. They created specific testing roadmaps, based on quarterly goals that align with local markets based on their needs and strategies.
“We then applied our tests, sharing the hypothesis (highlighting results from other markets) of what we hope to achieve and then applying the test into the main strategy.
“We had a clear timeline and roadmap. We always test and learn. This allows us to have a specific position with partners, allowing us to always be part of the alphas and betas, testing new formats, always trying to improve results at the same time”, Corinne shared.
To facilitate consistency the SEAT S.A team organized tests throughout the year pacing one test at a time for an ad group or campaign to maintain efficiency and gain clear observations. The roadmap was created on these factors:
- Priorities for markets based on the impact and workload
- Changes that Google makes to ad formats or different features that it sunsets or iterates
The search marketing grand prix: data, automation, and visual optimization
SEAT S.A and PHD Media started differentiating strategies by keyword type and defined them for each ad group. Keywords were segmented based on brand and non-brand search, their role, and their respective KPIs. This data was then used during the auction bidding. Artificial intelligence (AI) was used to segment audiences and target ads that were top of the funnel. Comparative insights from these tests were later fed into the business to inform the direction of strategy.
To improve the click through rate (CTR) and lower CPCs, the SEAT S.A team focused on adding visuals to ads, improving ad-copies, and testing new extensions. They also decreased CPAs by using bid strategies and the system’s AI to get the best of their budgets.
To master their visual impact on audiences SEAT S.A used image extensions for each ad across all their campaigns. Google displayed these images based on multiple factors like clicks, content, and keyword triggers to optimize the best performing ones.
From a data point of view, in Search SEAT S.A used Google Search Ads (SA360) to manage and monitor their Google Ads and Bing Ads respectively. The data sets tracked all the core essentials of paid search:
- Keyword conversion performance
- Ad copies
- Audience data through all the custom bidding options available in SA360
The ‘Performance innovation program’ model has helped SEAT and CUPRA achieve one of their best tests which catalyzed their search performance in terms of the cost per visit (CPV), one of their main KPIs that signaled top of the funnel conversions. The cost per visit (CPV) improved by 30% and cost per acquisition (CPA) improved by 37%.
SEAT S.A (SEAT and CUPRA) are now equipped with new ways to deduce and analyze conversions on a market-to-market basis.
Sharing intelligence across diverse markets
After completing the testing phase, the SEAT S.A team and their global partner PHD Media reported on results and observations. Sharing their learnings and insights with other markets has empowered other teams to benefit from the knowledge and expertise derived from the successful test prototypes. Focusing on components that drive results has allowed the teams spread across to be challenged and has facilitated constant learning while embracing changes and new features. The SEAT and CUPRA teams are now strongly positioned to outperform the competition.
Gearing up for a cookie less future
Going cookie less will bring challenging times and impact the search channel. SEAT and CUPRA plan to counter this with the use of Google Analytics 4 (GA4) to maintain performance and target the right audience. Opening up to new visual formats like Discovery campaigns and MMA/MSAN from Bing will also take an important place within search in the future, as the core of search might evolve with more automation, less granularity and control.
Greater focus on measurement and a privacy-first future
The team is testing ‘consent mode’ with GA4 and ‘enhanced conversion’ to estimate the attrition due to privacy guidelines. They are also focused on identifying and designing a risk contingency plan for the paid search elements that they won’t be able to test in the near future.
“We are testing all the new solutions and features that Google is bringing to the market in terms of privacy and cookie less capabilities. Particularly, our testing is focused on deploying the full suite of Google Analytics 4 (GA4), site-wide tagging, consent mode, and enhanced conversions.
Additionally, we are also testing new audience segments that GA4 allows within a privacy first ecosystem on our paid search campaigns. We are seeing some positive and promising results.”
– Corinne Calcabrina, Global Media Manager at SEAT S.A
SEAT S.A and PHD Media are actively focused on Google solutions for mapping markets and audiences that are privacy compliant and applicable for targeting segments.
They are also working towards gathering and connecting first party data like CRM audiences and customer match solutions.
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The post How a testing model is driving SEAT and CUPRA’s search marketing performance appeared first on Search Engine Watch.
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