Apple Mail Privacy Protection (AMPP) was introduced in September 2021 and since then it is difficult to evaluate the behavior of Apple Mail users accurately because of automatically generated opens. Depending on the industry and campaign, the information on real opens could be lost up to 25% of the total recipients. In order to avoid the distorting of your KPIs and incorrect sending, the automatically generated openings by the Apple system are filtered out in Optimizely Campaign since the AMPP release and no longer influence your opening statistics.
As of today, Optimizely Campaign provides a new feature in the target groups, which allows you to clearly identify and manage users of AMPP. You can individually set up the “automated open was detected” filter by time, frequency and mailing reference, what gives you completely new possibilities for targeting, segmenting and analyzing your email campaigns.
In this blog post, we’ll give you five practical examples how to use the new target group filter:
How to identify recipients with automatic openings
The new target group filter “automated open was detected” helps identify the recipients who have generated at least one opening by the Apple Mail Privacy Protection System in the past. Without any restrictions, the entire lifecycle of the recipients is taken into account.
Figure 1: Create target group for automated opens
Tip: In order to limit your target group to the users with Apple Mail Privacy Protection in case of a possible expansion of the systems, select a specific automated system, instead of “All”, in the last filter option.
Additional restrictions allow you to further refine the target group to get a more up-to-date picture of AMPP users. Assuming that recipients change their devices and email clients over time and also access their emails using second or third devices, we recommend using the time filter in combination with a frequency based on your sending frequency. By excluding real opens and clicks in the affected period, users activity on second devices is not considered. So that at any given time, you can filter those recipients who have recently received your emails with activated Apple Mail Privacy Protection.
For a client who gets two emails per week, a suitable target group might look as follows:
Figure 2: Example of defining a target group in Optimizely Campaign
Example time periods and frequencies by sending frequency:
Sending frequency per month (number of e-mails)
Reviewed period of the target group (in days)
Received mailings in the reviewed period
Expected frequency of automatic openings in the reviewed period
1
90
3
2+
4
30
4
3+
8
14
4
3+
Since Apple Mail Privacy Protection only generates an automated open when Apple Mail is active on the receiving device, we do not expect an automated open for every received e-mail. In general, however, this can be assumed.
If a recipient changes the device or deactivates the Apple Mail feature, automated opens will no longer be generated. The structure of the above mentioned target group shows that these recipients are automatically recognized as “regular” recipients and are no longer included in the target group.
Identify inactive recipients more accurately
Missing opens are used as an important indicator for future email campaigns, especially when reactivating the campaigns or trying to keep the recipient lists clean. This metric is also popular for follow-up and reminder emails. Unrecognized opens, due to AMPP, make targeted communication to relevant recipients difficult and clean-up processes inaccurate.
With the help of the new targeting functionality, non-openers can now be analyzed more accurately. The filter allows you to target AMPP users separately or exclude them completely from your reactivation activities.
Following the target group setup could be used as a starting condition for a reactivation campaign that is targeting inactive recipients in the last 60 days.
Figure 3: Sample target group definition for inactive recipients in Optimizely Campaign.
This setup is not only checking for missing opens and clicks in the selected period, but also excluding the recipients who have automated opens in the same period. Your campaign will therefore only target trackable contacts with no measured activity. The risk of sending unsuitable mails to unrecognized openers is reduced.
Target out dynamic content
One advantage of dynamic (live) content, such as countdown timers or product recommendations, is the high time relevance due to the generation of content at the time of opening. Automated opens through AMPP reduce this relevance, as the content is no longer generated at the actual opening time, but shortly after the dispatch happens. Countdown timers then no longer show the correct time, and the product recommendations could already be out of stock by the time the recipient clicks. It may therefore be worthwhile to provide recognized AMPP users with separate fallback content.
With the help of the sample target group shown in point 1, mailing content can be targeted specifically at Apple Mail Privacy Protection users. For example, instead of the paragraph with a countdown timer, they would receive a static graphic with the end time of the promotion. You could create separate widgets for product recommendations, that only show products with very high availability.
For separate targeting, simply connect the created group to the appropriate content or outline the paragraph that contains the fallback content.
For recipients without AMPP usage, use a corresponding counter-target group that includes only recipients with no or few automated open during the reviewed period. Important: Make sure that your two target groups are mutually exclusive and that in total all recipients are covered by the target groups. This is the only way to distribute the content accurately.
Record AMPP usage in the recipient list
In some cases, it is useful or preferred to record Apple Mail Privacy Protection usage by updating a recipient list field in the recipient’s record. This allows to run a data analysis based on the distribution list. In addition, the information can be transferred to CRM or other customer systems as part of synchronization processes.
The requirements for this is a corresponding recipient list field (e.g. of type “Boolean” or “String”) and the use of the “Advanced” or “Ultimate” version of Marketing Automation in Optimizely Campaign, which allows you to use the “Change Recipient” action node.
As a starting node, we set an “Advanced” node that checks daily, for example, the target group shown in point 1 under “Start only for”. Connected to the “Change recipient” node, the new recipient list field can now be set to true/yes as soon as a recipient meets the conditions of the starting node. From that point onward, the recipient will have the information about the AMPP usage as a flag in the data record.
Figure 4: Starting node with target group
Figure 5: Change recipient
If a recipient no longer generates regular automated opens because his/her receiving device or e-mail program were changed, the status of the recipient can be again set to false/no. For this we need another starting and “change recipient” nodes and an additional target group that work on the contrary to the first condition. For example:
Figure 6: Target group definition – change recipient (if it no longer generates automated opens).
The nodes can be used in the same Marketing Automation. If the recipient meets the criteria and fires the trigger, the relevant recipient list field can be set to false.
Figure 7: Overview of the two use cases in marketing automation
To ensure that the Marketing Automation also takes effect in the event of regular changes in user behavior, it should be possible to run the automation multiple times. To do this, set the selection in the first dropdown of the Advanced node to “always” or “when the recipient is not currently going through the marketing automation”.
Determine the proportion of automated opens and adjusted open rate
The main function of the new target group filter is the segmentation of recipients based on automated AMPP opens. Mailing-specific evaluations can also be carried out in combination with our Analytics feature “Deep Analytics”. That can be the starting point for calculating the proportion of automated opens per campaign. It is also possible to display open, click, and click-through rates adjusted to AMPP users.
In the first step, you need a mailing-specific target group that filters recipients with recognized automatedopens for selected mailing.
Figure 8: Create target group for campaign evaluation.
In order to exclude recognized active recipients (e.g. through openings on secondary devices), you can add this as an additional condition.
In the second step, create a new deep analytics report. Limit the analysis to the determined mailing, select the desired measurement values and activate the groupings for “Mailing Name” and just created “Target Group”. In order to calculate the share of automated opens, you need the “Recipients minus bounces” in the measured values.
Figure 9: Configuration of the campaign report in Deep Analytics.
Run the report and download the result as an Excel file. In the data sheet with summary rows, you will get three rows for the selected mailing.
Figure 10: Excel performance report on AMPP users.
The first row shows the recipients of your target group and their measured performance. If you have excluded recognized clickers and opens, the measured values should be 0. Without this exclusion, you get information about how many of your AMPP users are generating clicks and/or are active on secondary devices (opens & clicks).
The second row shows the “rest”, i.e., all measured values for email recipients that do not match your target group and accordingly did not generate automated opens. The open rate number in this row can also be understood as an adjusted open rate, since only recipients that are actually trackable are included.
Line three is the sum line. It allows us to put the absolute number of detected AMPP users (recipients minus bounces, C2) in relation to the total recipients (C4) and thus determine the proportion of automated opens. In the shown example, the proportion is 14.95% of identified AMPP users (32,739 of 218,926 recipients). According to our own analyses, depending on the industry, distributor and campaign, the value is usually between 13% – 20%, in some cases even higher.
We have already summarized the impact of the iOS15 update for iPhone and iPad in this blog post 2021.
For more information on creating target groups, see our documentation. If you have any technical questions or issues, feel free to contact our support team or your customer success manager. If you need more comprehensive support in implementing your AMPP-specific projects in Optimizely Campaign, feel free to contact our colleagues from Business Consulting.
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Cynthia Ramsaran is director of custom content at Third Door Media, publishers of Search Engine Land and MarTech. A multi-channel storyteller with over two decades of editorial/content marketing experience, Cynthia’s expertise spans the marketing, technology, finance, manufacturing and gaming industries. She was a writer/producer for CNBC.com and produced thought leadership for KPMG. Cynthia hails from Queens, NY and earned her Bachelor’s and MBA from St. John’s University.
In a groundbreaking alliance, Amazon and Hyundai have joined forces to reshape the automotive landscape, promising a revolutionary shift in how we buy, drive, and experience cars.
Imagine browsing for your dream car on Amazon, with the option to seamlessly purchase, pick up, or have it delivered—all within the familiar confines of the world’s largest online marketplace. Buckle up as we explore the potential impact of this monumental partnership and the transformation it heralds for the future of auto retail.
Driving Change Through Amazon’s Auto Revolution
Consider “Josh”, a tech-savvy professional with an affinity for efficiency. Faced with the tedious process of purchasing a new car, he stumbled upon Amazon’s automotive section. Intrigued by the prospect of a one-stop shopping experience, Josh decided to explore the Amazon-Hyundai collaboration.
The result?
A hassle-free online car purchase, personalized to his preferences, and delivered to his doorstep. Josh’s story is just a glimpse into the real-world impact of this game-changing partnership.
Bridging the Gap Between Convenience and Complexity
Traditional car buying is often marred by complexities, from navigating dealership lots to negotiating prices. The disconnect between the convenience consumers seek and the cumbersome process they endure has long been a pain point in the automotive industry. The need for a streamlined, customer-centric solution has never been more pressing.
Ecommerce Partnership Reshaping Auto Retail Dynamics
Enter Amazon and Hyundai’s new strategic partnership coming in 2024—an innovative solution poised to redefine the car-buying experience. The trio of key developments—Amazon becoming a virtual showroom, Hyundai embracing AWS for a digital makeover, and the integration of Alexa into next-gen vehicles—addresses the pain points with a holistic approach.
In 2024, auto dealers for the first time will be able to sell vehicles in Amazon’s U.S. store, and Hyundai will be the first brand available for customers to purchase.
This collaboration promises not just a transaction but a transformation in the way customers interact with, purchase, and engage with their vehicles.
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Driving into the Future
The Amazon-Hyundai collaboration is not just a partnership; it’s a revolution in motion. As we witness the fusion of e-commerce giant Amazon with automotive prowess of Hyundai, the potential impact on customer behavior is staggering.
The age-old challenges of car buying are met with a forward-thinking, customer-centric solution, paving the way for a new era in auto retail. From the comfort of your home to the driver’s seat, this partnership is set to redefine every step of the journey, promising a future where buying a car is as easy as ordering a package online.
Embrace the change, and witness the evolution of auto retail unfold before your eyes.
It’s no wonder that responsive search ads have steadily grown in popularity in recent years. Through Google’s machine learning capabilities, RSAs provide a powerful way to automate the testing of multiple headlines and descriptions to ensure a closer match to user intent. The benefits are clear: RSAs mean broader reach, better engagement, and improved performance metrics.
However, all these benefits come at a significant (but reasonable) cost – they can be extremely difficult to manage, especially when it comes to updating ad copy to promote limited time offers.
I know this firsthand – I work with several ecommerce clients with promotions that constantly change. Not too long ago, I found myself going through the consistently tedious process of updating a client’s RSA headlines and copy. As I was making the changes, I thought to myself: “There must be a better way to update this ad copy. I shouldn’t have to use find and replace so many times while pausing and enabling my ad campaigns.”
After expressing this to my colleague, Jordan Stambaugh, the two of us agreed there must be a better way. But we’d have to make it happen. A few weeks later, we put that idea into action and created a more efficient process for updating RSA ad copy on a scheduled basis. If you want to try this process for yourself, just keep reading.
Responsive Search Ad Customizers 101: Basic Options & Execution
Before diving into the process of scheduling automatic updates for your RSA customizers, it’s essential to understand some key Responsive Search Ad fundamentals.
First, you can customize three main options within RSAs: the Attribute Name, the Data Type, and the Account Value. Each of these plays a vital role in personalizing your ads:
Attribute Name: This is essentially the identifier for the customizer. It is how you’ll reference the specific piece of information you’re customizing within the ad. For instance, if you’re running a promotion, you might name an attribute “Promotion.”
Data Type: This indicates the kind of data the attribute represents and it determines how the information can be formatted and used within the ad. Common data types include Text (for plain, non-numeric text), Percent (to represent percentage discounts), Price (to denote monetary values), and Number (for any numerical value).
Account Value: This is the default value for the attribute that you set at the account level. It acts as a fallback if more specific values aren’t provided at the campaign or ad group level.
For example, if you wanted to promote a 10% off discount using RSAs, you’d use the “Discount” attribute, a data type of “Percent,” and an account value of “10% off.” Then, when someone is searching for products, Google would test automatically inserting a copy regarding a 10% off promotion into your ad.
Once you’ve set up the right customization options, you can start to format your RSAs with customizers.
Here’s how:
Start by typing in {
Click on Ad Customizer then select your attribute
Google will populate your attributes that are already uploaded
For a simple offer, use the “Default text” attribute as a catch-all. This will ensure your ads run smoothly if Google can’t pull the right messaging from your RSA feed
How to Schedule Your Ad Customizers with a Feed
Now that we’ve covered the basics, let’s cover how to schedule your ad customizers.
Just follow this three step process:
1. Create the feed
Start by creating two sheets: The Parent sheet, and the Child sheet. The “Parent” sheet will act as the primary data source, while the child sheet will pull data from the parent sheet.
We’ll start by building the parent sheet. After opening the sheet, start by renaming the active tab to “Promotions.” Don’t skip this step, it’s crucial for referencing this range in formulas later on.
In your “Promotions” tab, head to the top row and label columns A, B, and C with the headers of your ad customizer attributes. For example, you might have “BrandSaleHeadline” as your attribute in column A, “text” as the Data Type in column B, and “Shop the Collection” as the Account Value in column C.
Once your headers are in place, move to cell C2. Here, you’ll input the expression =lookup(today(),F:G,E:E). This formula will play a key role in dynamically updating your RSA customizer based on the current date.
Next, go to columns E, F, and G, which will be used to manage your scheduling. In these columns, you’ll list out the different values your chosen attribute might take, alongside their corresponding start and end dates. For example, under the “BrandSaleHeadline” attribute, you might schedule various promotional headlines to appear during different sale periods throughout the year.
Here’s how your sheet might look:
Now look back at the first 3 columns on your sheet. They should look like this:
Now create a second sheet. We’ll call this sheet the Child sheet. It’s going to automatically pull in data from the parent sheet you just created, and will be the one you link to Google Ads later on.
Columns A, B and C will be almost identical to the child sheet, but we will be using a special formula later so we can automatically populate this. So, start by labeling Row 1 Column A “Attribute,” then the next column as “Data type,” then column C as “Account value.”
Then go to C2 and use this expression to populate the right account value from the parent document: =importrange(“[PARENT DOCUMENT URL HERE]”,”Promotions!C2″)
Your sheet should now look like this:
We recommend adding a date range with default text for any days you’re not running a promotion. In the example above, we have “Shop Our Collection” appearing as default text.
2. Input attributes
Once you have your feed created, the next step involves inputting your attributes into the Google Ads platform. This can be done either manually or through a bulk upload.
For the manual approach, navigate to “Tools & Settings” in your Google Ads interface, then go to ‘Setup’ followed by “Business Data.” Here, you’ll find an option for “Ad Customizer Attributes.” Click the plus sign to add your attributes. It’s crucial to use the same attribute names that you’ve established in your Parent Google Sheet template to ensure consistency and proper data synchronization.
Alternatively, if you prefer the bulk upload method, again head to “Tools & Settings.” This time, select “Bulk Actions” and then “Uploads.” For this process, you only need to upload columns A to C from your template.
Be aware that it might take some time for your uploaded attributes to be reflected in the business data section of Google Ads.
3. Set up an automatic schedule
At this point, you’ve almost finished scheduling your ad customizers. Navigate to Tools & Settings, then Bulk Actions, then Uploads, then click the Schedules tab at the top. Select your Child Google Sheet as the data source, and share your Google Sheet with the appropriate email.
And there you have it – Google will automatically pull in the data you populated in the sheets into your RSAs.
Common Challenges When Scheduling RSA Ad Customizers
When we test these sheets with our clients in the wild, we’ve uncovered five common challenges. Be on the lookout for these issues – solving them before they happen can save you a lot of trouble down the line.
Not scheduling your upload when the site changes
The first and most significant hurdle is the mismatch between the scheduled data upload and website content updates. For instance, if the Google Sheet is set to upload at 11 am, but the website changes occur at 3 pm, there’s going to be a discrepancy where the wrong message could be displayed for several hours, or new messaging could appear prematurely. Conversely, if the website updates happen before the scheduled sheet upload, outdated promotions might linger until the new data is imported. Synchronizing these schedules is crucial; it’s best to align them so updates occur simultaneously.
Skipping QA during a message change
Another pitfall is neglecting quality assurance (QA) during message updates. It’s vital to regularly check the business data section to verify that the correct values are in place post-update.
Issues with the IMPORTRANGE function
Then there’s the technical aspect of setting up the IMPORTRANGE function correctly in the Google Sheets template. The ‘child’ template must reliably pull data from the ‘parent’ sheet. If this function isn’t configured correctly, data won’t be imported as needed.
Not sharing access of the Google template for automatic uploads
Pay attention to your access permissions for the Google Sheets template. Google will prompt you with the email address that needs permission to access the ‘child’ sheet for automatic uploads. Overlooking the sharing of your sheet with this address will prevent the system from working.
Having date range gaps in your parent sheet
Lastly, a common oversight is leaving date range gaps in the ‘parent’ sheet. Every single date must be accounted for without overlaps. A practical tip is to have an ‘evergreen’ backup message ready, scheduled to run continuously, ideally through the end of the year, to cover any potential gaps.
Conclusion
Leveraging Google Sheets in conjunction with Google Ads to schedule RSA ad customizers is a game-changer for managing dynamic promotional content. This process not only streamlines your workflows but also ensures that your ads remain relevant and up-to-date, reflecting current promotions without the need for constant manual intervention.
By adopting this method, you’ll save significant time and effort, allowing you to focus more on strategy and less on the minutiae of ad copy updates. Give it a try and experience a more efficient way to manage your RSAs, keeping your campaigns fresh and engaging with minimal hassle.
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