MARKETING
A Powerful Clean Room Solution [Updated]
Amazon Advertising kicked off 2021 by announcing the beta release of Amazon Marketing Cloud, a measurement and analytics solution designed to help marketers measure performance across different media channels. As an Amazon Ads Advanced Partner, Tinuiti teams were eligible to take part in the AMC alpha program, and have now had more than a year to familiarize themselves with the platform, strategically experiment, and experience its many impressive and game-changing capabilities firsthand.
In this article, we’ll share everything you need to know about the Amazon Marketing Cloud.
What is the Amazon Marketing Cloud?
The Amazon Marketing Cloud (AMC) is a secure, privacy-friendly, dedicated cloud-based measurement and analytics solution.
“AMC is a clean room solution that advertisers can access, and essentially structure custom queries to explore specific questions that help address top business priorities and measurement challenges. Allowing brands to access incredibly detailed data that is specific to their audiences’ journey. AMC gives us the ability to understand what is working and what is the connectedness between “events” – going beyond what traditional reports provide.”
— Nancy McLaughlin, Senior Director, Marketplaces at Tinuiti
Built on Amazon Web Services (AWS), AMC’s flexible environment supplies advertisers with customizable reporting on event-level data, across multiple data sets. Those data sets can include both advertiser data and Amazon Advertising data, offering advertisers a more holistic view of campaign performance.
In other words, AMC gives advertisers the transparent, cross-channel data they need to make more informed decisions about their marketing.
And today’s marketers need that transparent, actionable data more than ever before.
It can be a challenge for advertisers to access the information they need for in-depth analysis. In fact, when it comes to programmatic advertising, more than 1 in 4 advertisers name supply transparency as their biggest challenge.
The problem is, as marketers, we’re data-obsessed — and rightfully so. For the past several years, marketers have expected that cross-channel measurement and attribution activities will remain their highest priority, occupying most of their time and resources.
But as browsers begin blocking third-party cookies, advertisers are struggling to measure conversions and access the information needed for in-depth reporting. And as the industry continues to change, it’s getting more complex and challenging to measure attribution and campaign performance across channels.
AMC aims to help advertisers overcome that challenge by offering analytics beyond what traditional reports can provide. Advertisers can generate aggregated reports based on both their own data sets and their Amazon Advertising campaign events.
“If you find yourself looking at reports trying to string together various metrics—especially if it’s across search and display—and really trying to make a story out of it when it’s not clear, this could be a great indicator that you simply need more than what’s available to you. This is where AMC can come in and provide a huge variety of reporting and metrics that just aren’t available in the standardized reporting we have today.”
— Jen Acosta, Senior Strategist, Marketplaces at Tinuiti
How does Amazon Marketing Cloud work?
Amazon Marketing Cloud is designed to maintain end-customer privacy, so it only returns aggregate analytics. No individual user data is ever returned from the Amazon Marketing Cloud.
To protect customer privacy, all aggregations must contain a minimum of one hundred users. Advertisers cannot access Amazon Advertising event-level data directly. Aggregating over a minimum number of users gives advertisers significant, actionable reporting while maintaining end-customer privacy.
“Each Amazon Marketing Cloud account is scoped per advertiser, and uses AWS for storage. All results from AMC are aggregates that need to exceed minimum thresholds that typically require over 100 unique users. Advertisers cannot access Amazon’s Advertising event-level data, so aggregating over this minimum number really allows us to understand the paths while still protecting that customer data.”
— Nancy McLaughlin, Senior Director, Marketplaces at Tinuiti
Amazon Marketing Cloud also lets marketers join advertiser data to Amazon events data, creating an even more robust opportunity for cross-channel analytics, as well as the option to enable custom attribution. Like user data, advertiser data is protected, meaning neither the advertiser nor Amazon can access each other’s event-level data.
Amazon Marketing Cloud’s top reporting abilities
With AMC you can create custom analytics based on advertisers’ campaign objectives, tactics, and channels.
Some examples of what this data and reporting can help illuminate include:
- Total reach and performance across channels
- Path-to-conversion analysis, including multiple attribution models and cross-campaign data aggregation
- Custom reporting beyond what’s currently available in Amazon DSP
- Custom attribution analysis to measure how different media channels impact audience discovery, research, and purchase behavior
- Enhanced audience insights to inform decisions about how, when, and where to best engage potential customers
“With AMC, we’re able to unlock efficiencies through click pathing, attribution transparency, and full-funnel attribution. We can also understand the ideal media mix and how to best reach an audience. There are transparency challenges within the advertising world, and AMC is a great tool that can be leveraged to help break down these barriers.”
— Madalyn Kaseeska, Associate Director, Marketplaces at Tinuiti
All in all, Amazon Marketing Cloud offers reporting and analytics unique to each advertiser’s goals, channels, audience, and messaging. With AMC, advertisers can measure advertising performance impact across channels both on and off Amazon, creating a truly holistic reporting environment.
Amazon Marketing Cloud Provides the Whole Story
Simply put, Amazon Marketing Cloud helps provide the whole story—tangents, footnotes, and all. Historically, brands and advertisers have had to take the information they were given and ‘fill in the gaps,’ relying on their expertise and understanding of the brand to build the connective tissue between A, B, and C.
AMC offers reliable answers to important questions that were previously difficult to answer—and may become otherwise impossible to answer with the same reliability and durability AMC offers—in the increasingly privacy-focused future.
The queries themselves are limitless, and our teams have mastered custom query creation in the past 12+ months. If there is a question you’re trying to answer, and the data is available to produce that answer, our team will get to word determining the ‘best way to ask’ to get you the answers you need.
The broader categories for which AMC can provide actionable insights include:
- Performance deep dives
- Audience insights
- Consumer journey analysis
- Media mix analysis
- Purchase pattern analysis
- Omnichannel impact analysis
Some common questions brands and advertisers turn to AMC to answer within those categories include:
- Who are my most engaged audiences?
- In what geographies is my brand or product most viewed and purchased?
- What devices are most shoppers purchasing my products using?
- What media mix will be most impactful in reaching my goals?
- How are my upper-funnel advertising tactics driving brand loyalty and repeat purchases?
- How do my Amazon ad campaigns impact my conversions outside of Amazon?
Amazon Marketing Cloud is poised to help answer the limitless advertising versions of the age-old question: “Which came first, the chicken or the egg?” It just looks more like: “Which came first in this conversion journey, the streaming ad or the display ad?”
Is Amazon Marketing Cloud worth it?
The short answer: Yes.
AMC is a worthwhile tool for advertisers looking for more in-depth, actionable reporting across channels, especially as policies continue to be enforced on third-party cookies and other potential privacy concerns. One of AMC’s biggest benefits is that it is privacy-first by design and will provide insights across various ad platforms. Ultimately, this is going to be more user-friendly in the long-term.
“AMC gives brands the opportunity to develop a deeper understanding of how they’re engaging with audiences across Amazon platforms and devices today. At Tinuiti, we’ve seen the impact of using this data to supplement campaign planning and in-flight optimizations for our clients, and it’s a powerful asset to have. Clean rooms, like AMC, will play an important role in helping brands navigate and succeed in a cookieless world so they need to begin familiarizing themselves with its capabilities today, and incorporate AMC into discussions regarding future data strategy as well.”
— David Weichel, VP, Product Development at Tinuiti
Getting Started with Amazon Marketing Cloud
Interested eligible advertisers can reach out to their Amazon Ads account executive to learn more about getting AMC set-up via web-based UI and API. Your account leader will help you weigh the associated costs and benefits of AMC to determine if it is the right fit for your needs.
Amazon outlines AMC requirements as such:
“Advertisers need to have an executed Amazon DSP Master Service Agreement (MSA), planned campaigns or campaigns live in the last 28 days at Amazon DSP and a technical resource familiar with SQL. For AMC API users, advertisers should also have an Amazon Web Services (AWS) account.”
Amazon Marketing Cloud Examples: How Tinuiti Uses AMC
Amazon Marketing Cloud is instrumental in understanding how all your advertising efforts align with your goals, and ultimately impact your business. The wealth of privacy-compliant data enables us to ramp up our test-and-learn optimizations with the necessary confidence that we’ll be able to realize concrete findings from those investments.
Our teams are better equipped to collaborate internally, breaking down silos to determine the ideal media mixes across platforms. These thoughtful conversations lead to clearer narratives about how active campaigns interact with, and influence each other—that ‘whole story’ we talked about earlier.
Let’s look at a few ways our teams have used AMC to find the specific data they needed to make the most informed and effective decisions for their clients’ Amazon campaigns…
Example 1: Create Gateway ASIN (Amazon Standard Identification Number) Query
Scenario: One of our clients in the CPG space wanted to identify which of their products was most commonly the “gateway ASIN”—the ASIN that drove consumers to purchase from the brand for the first time. They also wanted to know which new-to-brand ASIN drove the highest repeat purchases. We did not have a query to support this question, and it wasn’t available in the UI.
Solution: We built a custom query to identify gateway products that drive new-to-brand purchases.
Outcome:
“Once we were able to determine the ASIN with high repeat purchases, we were able to push additional media behind it to see how it impacted new-to-brand orders. By launching media to expand targeting into adjacent categories, we saw over a 100% increase in new-to-brand orders when media dollars were running for that particular product. We also saw this strategy impact total business with an 11% increase in total orders.”
— Madalyn Kaseeska, Associate Director, Marketplaces at Tinuiti
Example 2: Identify Top Amazon Fresh DMAs (Designated Market Areas)
Scenario: A client in the CPG space wanted to identify their top DMAs for acquiring new Amazon Fresh (a grocery delivery service) customers so they could be more strategic and efficient with their targeting.
Solution: Use AMC data to determine the geographic areas with the highest number of repeat Amazon Fresh shoppers.
Outcome:
“By using AMC, the client was able to identify new shoppers who continued to buy after their first purchase, and narrow down to their top 5 performing locations. When comparing to all other available DMAs at the time, the top 5 selected DMAs outperformed by not only increasing their return on new-to-brand purchasers by 145%, but they also saw a 54% decrease in the cost to acquire this new customer. This process was then adopted as a best practice for identifying where it made sense to advertise for Fresh through DSP, which wouldn’t have been possible without the aggregated data available through AMC.”
— Jen Acosta, Senior Strategist, Marketplaces at Tinuiti
Example 3: Conversion Rate Analysis by Ad Exposure Mix
Scenario: An automotive accessories brand client wanted to measure the impact different campaigns had on their purchase rate. The advertiser was running a full-funnel strategy across Sponsored Products, Display, and OTT/Streaming TV.
Solution: Use AMC data to see how conversion rates are impacted by which ads, and combination of ads, shoppers are shown.
Outcome:
“We were able to use AMC data to understand the impact, and ensure our strategy was driving meaningful results. We found that audiences exposed to Sponsored Products and Display campaigns had a purchase rate that was 3-4 times higher than just Sponsored Products or Display alone. Additionally, our continued investment in OTT over the year showed a growing increase in purchase rate when exposed to an OTT, Display, and Sponsored Product ad. Ultimately, we saw that not only was our purchase rate higher, but we were also able to see an even higher new-to-brand purchase rate, which was 2.5x higher when a shopper was exposed to all 3 campaign types.”
— Karen Hopkins, Strategist, Marketplaces at Tinuiti
AMC Reporting: Tinuiti’s Custom Amazon Marketing Cloud Reports
Thanks to Tinuiti’s status as an Amazon Ads Advanced Partner, our teams’ eligibility to take part in the AMC alpha program gave them a head start on mastering the foundation of the platform’s capabilities so they could move into strategic experimentation with custom query creation and more.
With custom, individual SQL queries Tinuiti’s teams created based on common questions we experience as advertisers, we are able to offer our clients several unique, insight-packed reports that help in better understanding campaign performance and recommended next steps.
Some of our most popular reports include:
1. Media Mix Analysis Report: This report evaluates user behavior in a weekly or monthly snapshot, grouping users by the ad types they were exposed to during that time frame. This view allows our clients to understand how exposure to different ad combinations impacts key metrics, including: Customer reach, engagement, acquisition, and purchase behavior.
2. New-to-Brand Report (NTB): The NTB report illustrates what type of customer—new or returning—is purchasing a tracked ASIN(s) over a one-month period. These metrics are aggregated by two customer groups: new-to-brand and repeat customers.
3. Tentpole Event Analysis: This report is used to analyze the impact of advertising during Prime Day, and the halo effect. Metrics including customer reach, engagement, acquisition, and purchase behavior are aggregated by the following three time periods: before Prime Day, during Prime Day, and after Prime Day.
4. Pathing Analysis: This model is used to analyze the typical path a client’s customer takes to convert. It illustrates what paths have the best results when trying to reach new-to-brand customers. The report can also be used to demonstrate how the first or last touch point in the path can affect metrics as well. Customer reach, engagement, acquisition, and purchase behavior can all be analyzed in this model.
5. Dayparting Analysis: This model helps clients understand how their campaigns are performing at different hours of the day. The model includes high-level metrics at the hour and day breakdown. Additionally, clients can see their advertising cost compared to different metrics by hour or by day.
6. Impression Frequency Analysis: This model helps clients understand how heavily they need to target customers before a conversion takes place. The report is broken out by impression frequency bucket, showcasing the optimal amount of targeting to drive conversion metrics. The report also demonstrates how often new vs. repeat customers need to be targeted, and how those customers’ yield changes as they are continually targeted.
Subscription-based Amazon Marketing Cloud
Amazon recently unveiled a new subscription-based version of Amazon Marketing Cloud. These subscription or paid features (although currently in beta) allows brands and advertisers to access their retail data within Amazon, providing insights into how shoppers are interacting with their products in relation to their advertising efforts.
“Thanks to our AMC alpha and beta access, our teams have had ample time to familiarize themselves with Amazon Marketing Cloud, and have been watching its evolution in real time. We’re so excited about the launch of AMC’s subscription-based features because it truly fills in all the gaps, providing valuable organic retail data and paid data. These comprehensive insights enable our team to make the most informed, strategic decisions in crafting a holistic marketing plan.”
— Aly Fields, Associate Director, Strategic Services at Tinuiti
What data is available in AMC’s subscription-based reports?
It’s important to note that the advertising data that has historically been available within Amazon Marketing Cloud is still accessible for free; AMC’s subscription-based feature is not replacing AMC. The difference is that AMC’s subscription-based feature also offers organic, product-level retail data in addition to that freely available advertising data. This makes for more robust reports detailing brand engagement, shopping trends, shopping engagement, and more.
AMC’s subscription-based feature leverages data presently available via the Amazon Selling Partner API. It provides reporting stats that highlight how shoppers interact with your products, including data on:
- Total browse
- Add-to-cart
- New Subscribe and Save (SNS)
- Added to gift list, wish list, or watch list
- Added to baby registry or wedding registry
- Customer review page visits
- Product detail page views
- Amazon Store visits (brand store engagement)
- Non-ad attributed purchase metrics for products (including product purchased and product purchased using one-click)
How do you sign-up for AMC’s subscription-based feature?
Amazon is currently offering a 30-day free trial. Once the free trial has expired, brands will pay a monthly subscription fee to continue accessing AMC’s subscription-based data and features. This monthly fee is determined and set by Amazon, and paid directly to Amazon; the cost considers how much data exists in the brand’s retail database.
- AMC’s subscription-based feature is currently available in the US; registered AMC brand owners in the US who sell on Amazon are eligible. AMC subscription-based feature can be cancelled at any time
- We encourage all of our eligible clients to consider the free trial to determine if the additional insights are worth the cost. If your AMC instance (connection) is already created, we can work with Amazon to get your free trial started. As the new feature is still in beta, Amazon requires that your AMC account has been in place (and acquiring data) for at least a few months before upgrading
- If you are currently working with Tinuiti for your Amazon advertising efforts, be sure to schedule some time with your AM to discuss AMC and AMC’s paid option. Our team of Commerce experts can help you launch a full-funnel Amazon strategy with AMC and guide you through the reports and recommended next steps that come from these richer insights
If you aren’t working with us yet, drop us a line! Also be sure to check out our recent webinar focused on using Amazon DSP and AMC to drive measurable, full-funnel results.
Editor’s Note: This post was originally published by Tara Johnson in February 2021 and has been regularly updated for freshness, accuracy, and comprehensiveness.
MARKETING
YouTube Ad Specs, Sizes, and Examples [2024 Update]
Introduction
With billions of users each month, YouTube is the world’s second largest search engine and top website for video content. This makes it a great place for advertising. To succeed, advertisers need to follow the correct YouTube ad specifications. These rules help your ad reach more viewers, increasing the chance of gaining new customers and boosting brand awareness.
Types of YouTube Ads
Video Ads
- Description: These play before, during, or after a YouTube video on computers or mobile devices.
- Types:
- In-stream ads: Can be skippable or non-skippable.
- Bumper ads: Non-skippable, short ads that play before, during, or after a video.
Display Ads
- Description: These appear in different spots on YouTube and usually use text or static images.
- Note: YouTube does not support display image ads directly on its app, but these can be targeted to YouTube.com through Google Display Network (GDN).
Companion Banners
- Description: Appears to the right of the YouTube player on desktop.
- Requirement: Must be purchased alongside In-stream ads, Bumper ads, or In-feed ads.
In-feed Ads
- Description: Resemble videos with images, headlines, and text. They link to a public or unlisted YouTube video.
Outstream Ads
- Description: Mobile-only video ads that play outside of YouTube, on websites and apps within the Google video partner network.
Masthead Ads
- Description: Premium, high-visibility banner ads displayed at the top of the YouTube homepage for both desktop and mobile users.
YouTube Ad Specs by Type
Skippable In-stream Video Ads
- Placement: Before, during, or after a YouTube video.
- Resolution:
- Horizontal: 1920 x 1080px
- Vertical: 1080 x 1920px
- Square: 1080 x 1080px
- Aspect Ratio:
- Horizontal: 16:9
- Vertical: 9:16
- Square: 1:1
- Length:
- Awareness: 15-20 seconds
- Consideration: 2-3 minutes
- Action: 15-20 seconds
Non-skippable In-stream Video Ads
- Description: Must be watched completely before the main video.
- Length: 15 seconds (or 20 seconds in certain markets).
- Resolution:
- Horizontal: 1920 x 1080px
- Vertical: 1080 x 1920px
- Square: 1080 x 1080px
- Aspect Ratio:
- Horizontal: 16:9
- Vertical: 9:16
- Square: 1:1
Bumper Ads
- Length: Maximum 6 seconds.
- File Format: MP4, Quicktime, AVI, ASF, Windows Media, or MPEG.
- Resolution:
- Horizontal: 640 x 360px
- Vertical: 480 x 360px
In-feed Ads
- Description: Show alongside YouTube content, like search results or the Home feed.
- Resolution:
- Horizontal: 1920 x 1080px
- Vertical: 1080 x 1920px
- Square: 1080 x 1080px
- Aspect Ratio:
- Horizontal: 16:9
- Square: 1:1
- Length:
- Awareness: 15-20 seconds
- Consideration: 2-3 minutes
- Headline/Description:
- Headline: Up to 2 lines, 40 characters per line
- Description: Up to 2 lines, 35 characters per line
Display Ads
- Description: Static images or animated media that appear on YouTube next to video suggestions, in search results, or on the homepage.
- Image Size: 300×60 pixels.
- File Type: GIF, JPG, PNG.
- File Size: Max 150KB.
- Max Animation Length: 30 seconds.
Outstream Ads
- Description: Mobile-only video ads that appear on websites and apps within the Google video partner network, not on YouTube itself.
- Logo Specs:
- Square: 1:1 (200 x 200px).
- File Type: JPG, GIF, PNG.
- Max Size: 200KB.
Masthead Ads
- Description: High-visibility ads at the top of the YouTube homepage.
- Resolution: 1920 x 1080 or higher.
- File Type: JPG or PNG (without transparency).
Conclusion
YouTube offers a variety of ad formats to reach audiences effectively in 2024. Whether you want to build brand awareness, drive conversions, or target specific demographics, YouTube provides a dynamic platform for your advertising needs. Always follow Google’s advertising policies and the technical ad specs to ensure your ads perform their best. Ready to start using YouTube ads? Contact us today to get started!
MARKETING
Why We Are Always ‘Clicking to Buy’, According to Psychologists
Amazon pillows.
MARKETING
A deeper dive into data, personalization and Copilots
Salesforce launched a collection of new, generative AI-related products at Connections in Chicago this week. They included new Einstein Copilots for marketers and merchants and Einstein Personalization.
To better understand, not only the potential impact of the new products, but the evolving Salesforce architecture, we sat down with Bobby Jania, CMO, Marketing Cloud.
Dig deeper: Salesforce piles on the Einstein Copilots
Salesforce’s evolving architecture
It’s hard to deny that Salesforce likes coming up with new names for platforms and products (what happened to Customer 360?) and this can sometimes make the observer wonder if something is brand new, or old but with a brand new name. In particular, what exactly is Einstein 1 and how is it related to Salesforce Data Cloud?
“Data Cloud is built on the Einstein 1 platform,” Jania explained. “The Einstein 1 platform is our entire Salesforce platform and that includes products like Sales Cloud, Service Cloud — that it includes the original idea of Salesforce not just being in the cloud, but being multi-tenancy.”
Data Cloud — not an acquisition, of course — was built natively on that platform. It was the first product built on Hyperforce, Salesforce’s new cloud infrastructure architecture. “Since Data Cloud was on what we now call the Einstein 1 platform from Day One, it has always natively connected to, and been able to read anything in Sales Cloud, Service Cloud [and so on]. On top of that, we can now bring in, not only structured but unstructured data.”
That’s a significant progression from the position, several years ago, when Salesforce had stitched together a platform around various acquisitions (ExactTarget, for example) that didn’t necessarily talk to each other.
“At times, what we would do is have a kind of behind-the-scenes flow where data from one product could be moved into another product,” said Jania, “but in many of those cases the data would then be in both, whereas now the data is in Data Cloud. Tableau will run natively off Data Cloud; Commerce Cloud, Service Cloud, Marketing Cloud — they’re all going to the same operational customer profile.” They’re not copying the data from Data Cloud, Jania confirmed.
Another thing to know is tit’s possible for Salesforce customers to import their own datasets into Data Cloud. “We wanted to create a federated data model,” said Jania. “If you’re using Snowflake, for example, we more or less virtually sit on your data lake. The value we add is that we will look at all your data and help you form these operational customer profiles.”
Let’s learn more about Einstein Copilot
“Copilot means that I have an assistant with me in the tool where I need to be working that contextually knows what I am trying to do and helps me at every step of the process,” Jania said.
For marketers, this might begin with a campaign brief developed with Copilot’s assistance, the identification of an audience based on the brief, and then the development of email or other content. “What’s really cool is the idea of Einstein Studio where our customers will create actions [for Copilot] that we hadn’t even thought about.”
Here’s a key insight (back to nomenclature). We reported on Copilot for markets, Copilot for merchants, Copilot for shoppers. It turns out, however, that there is just one Copilot, Einstein Copilot, and these are use cases. “There’s just one Copilot, we just add these for a little clarity; we’re going to talk about marketing use cases, about shoppers’ use cases. These are actions for the marketing use cases we built out of the box; you can build your own.”
It’s surely going to take a little time for marketers to learn to work easily with Copilot. “There’s always time for adoption,” Jania agreed. “What is directly connected with this is, this is my ninth Connections and this one has the most hands-on training that I’ve seen since 2014 — and a lot of that is getting people using Data Cloud, using these tools rather than just being given a demo.”
What’s new about Einstein Personalization
Salesforce Einstein has been around since 2016 and many of the use cases seem to have involved personalization in various forms. What’s new?
“Einstein Personalization is a real-time decision engine and it’s going to choose next-best-action, next-best-offer. What is new is that it’s a service now that runs natively on top of Data Cloud.” A lot of real-time decision engines need their own set of data that might actually be a subset of data. “Einstein Personalization is going to look holistically at a customer and recommend a next-best-action that could be natively surfaced in Service Cloud, Sales Cloud or Marketing Cloud.”
Finally, trust
One feature of the presentations at Connections was the reassurance that, although public LLMs like ChatGPT could be selected for application to customer data, none of that data would be retained by the LLMs. Is this just a matter of written agreements? No, not just that, said Jania.
“In the Einstein Trust Layer, all of the data, when it connects to an LLM, runs through our gateway. If there was a prompt that had personally identifiable information — a credit card number, an email address — at a mimum, all that is stripped out. The LLMs do not store the output; we store the output for auditing back in Salesforce. Any output that comes back through our gateway is logged in our system; it runs through a toxicity model; and only at the end do we put PII data back into the answer. There are real pieces beyond a handshake that this data is safe.”
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