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Intro to Amazon Non-endemic Advertising: Benefits & Examples

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Intro to Amazon Non-endemic Advertising: Benefits & Examples

Amazon has rewritten the rules of advertising with its move into non-endemic retail media advertising. Advertising on Amazon has traditionally focused on brands and products directly sold on the platform. However, a new trend is emerging – the rise of non-endemic advertising on this booming marketplace. In this article, we’ll dive into the concept of non-endemic ads, their significance, and the benefits they offer to advertisers. This strategic shift is opening the floodgates for advertisers in previously overlooked industries.

While endemic brands are those with direct competitors on the platform, non-endemic advertisers bring a diverse range of services to Amazon’s vast audience. The move toward non-endemic advertising signifies Amazon’s intention to leverage its extensive data and audience segments to benefit a broader spectrum of advertisers.

Endemic vs. Non-Endemic Advertising

 

Let’s start by breaking down the major differences between endemic advertising and non-endemic advertising… 

Endemic Advertising

Endemic advertising revolves around promoting products available on the Amazon platform. With this type of promotion, advertisers use retail media data to promote products that are sold at the retailer.

Non-Endemic Advertising

In contrast, non-endemic advertising ventures beyond the confines of products sold on Amazon. It encompasses industries such as insurance, finance, and services like lawn care. If a brand is offering a product or service that doesn’t fit under one of the categories that Amazon sells, it’s considered non-endemic. Advertisers selling products and services outside of Amazon and linking directly to their own site are utilizing Amazon’s DSP and their data/audience segments to target new and relevant customers.

7 Benefits of Running Non-Endemic Ad Campaigns

 

Running non-endemic ad campaigns on Amazon provides a wide variety of benefits like:

Access to Amazon’s Proprietary Data: Harnessing Amazon’s robust first-party data provides advertisers with valuable insights into consumer behavior and purchasing patterns. This data-driven approach enables more targeted and effective campaigns.

Increased Brand Awareness and Revenue Streams: Non-endemic advertising allows brands to extend their reach beyond their typical audience. By leveraging Amazon’s platform and data, advertisers can build brand awareness among users who may not have been exposed to their products or services otherwise. For non-endemic brands that meet specific criteria, there’s an opportunity to serve ads directly on the Amazon platform. This can lead to exposure to the millions of users shopping on Amazon daily, potentially opening up new revenue streams for these brands.

No Minimum Spend for Non-DSP Campaigns: Non-endemic advertisers can kickstart their advertising journey on Amazon without the burden of a minimum spend requirement, ensuring accessibility for a diverse range of brands.

Amazon DSP Capabilities: Leveraging the Amazon DSP (Demand-Side Platform) enhances campaign capabilities. It enables programmatic media buys, advanced audience targeting, and access to a variety of ad formats.

Connect with Primed-to-Purchase Customers: Amazon’s extensive customer base offers a unique opportunity for non-endemic advertisers to connect with customers actively seeking relevant products or services.

Enhanced Targeting and Audience Segmentation: Utilizing Amazon’s vast dataset, advertisers can create highly specific audience segments. This enhanced targeting helps advertisers reach relevant customers, resulting in increased website traffic, lead generation, and improved conversion rates.

Brand Defense – By utilizing these data segments and inventory, some brands are able to bid for placements where their possible competitors would otherwise be. This also gives brands a chance to be present when competitor brands may be on the same page helping conquest for competitors’ customers.

How to Start Running Non-Endemic Ads on Amazon

 

Ready to start running non-endemic ads on Amazon? Start with these essential steps:

Familiarize Yourself with Amazon Ads and DSP: Understand the capabilities of Amazon Ads and DSP, exploring their benefits and limitations to make informed decisions.

Look Into Amazon Performance Plus: Amazon Performance Plus is the ability to model your audiences based on user behavior from the Amazon Ad Tag. The process will then find lookalike amazon shoppers with a higher propensity for conversion.

“Amazon Performance Plus has the ability to be Amazon’s top performing ad product. With the machine learning behind the audience cohorts we are seeing incremental audiences converting on D2C websites and beating CPA goals by as much as 50%.” 

– Robert Avellino, VP of Retail Media Partnerships at Tinuiti

 

Understand Targeting Capabilities: Gain insights into the various targeting options available for Amazon ads, including behavioral, contextual, and demographic targeting.

Command Amazon’s Data: Utilize granular data to test and learn from campaign outcomes, optimizing strategies based on real-time insights for maximum effectiveness.

Work with an Agency: For those new to non-endemic advertising on Amazon, it’s essential to define clear goals and identify target audiences. Working with an agency can provide valuable guidance in navigating the nuances of non-endemic advertising. Understanding both the audience to be reached and the core audience for the brand sets the stage for a successful non-endemic advertising campaign.

Conclusion

 

Amazon’s venture into non-endemic advertising reshapes the advertising landscape, providing new opportunities for brands beyond the traditional ecommerce sphere. The  blend of non-endemic campaigns with Amazon’s extensive audience and data creates a cohesive option for advertisers seeking to diversify strategies and explore new revenue streams. As this trend evolves, staying informed about the latest features and possibilities within Amazon’s non-endemic advertising ecosystem is crucial for brands looking to stay ahead in the dynamic world of digital advertising.

We’ll continue to keep you updated on all things Amazon, but if you’re looking to learn more about advertising on the platform, check out our Amazon Services page or contact us today for more information.

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YouTube Ad Specs, Sizes, and Examples [2024 Update]

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YouTube Ad Specs, Sizes, and Examples

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!

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Why We Are Always ‘Clicking to Buy’, According to Psychologists

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Why We Are Always 'Clicking to Buy', According to Psychologists

Amazon pillows.

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A deeper dive into data, personalization and Copilots

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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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