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Google’s Topics API provokes a range of reactions

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Google's Topics API provokes a range of reactions

Earlier this week, Google announced the Topics API, its latest ad targeting proposal aimed at replacing third-party cookies. This leaves Federated Learning of Cohorts dead in the water while marketing and adtech platforms and advertisers try to make sense of the new proposal.

Topics may be a more realistic option than FLoC, marketers say

“Topics seem more likely to be acceptable to the broader ecosystem as they address several FLoC privacy concerns head on,” said Aaron Levy, head of paid search at Tinuiti. “It’s odd to call this an advantage, but I view anything that launches with a higher likelihood of stability and lesser likelihood of mass opt-outs a win.”

The other practitioners seemed to concur. “On their face, Topics seem like they should be less personally identifiable, which would be a plus for privacy,” said Julie Friedman Bacchini, president of Neptune Moon and managing director of PPC community PPCChat.

“I like that Chrome users will be able to see their topics and delete them if they wish,” said Christine Zirnheld, digital marketing manager at Cypress North. While this feature can make life harder for advertisers, options for users will help to appease privacy advocates and regulators, which increases the chances that Google will eventually be able to launch Topics.

Topic diversity and other potential hurdles for advertisers

The Topics API’s initial design includes approximately 350 topics, according to its GitHub page. Advertisers are concerned that this quantity won’t be sufficient enough to provide relevant targeting.

“Google’s current interest list [of topics] doesn’t offer the level of nuance most marketers need to target people who’d actually want to see their ads,” said Ashwin Balakrishnan, head of marketing at Optmyzr. “If Topics is going to be a success, Google needs to provide more detailed options.”

“Advertisers (at least as of now) would have few interests to actually target, and broader targeting does not usually lead to better performance,” Zirnheld said. “An interest in cars & autos doesn’t tell me if that’s luxury, rental, new, used, SUV, etc.,” Geddes added, “That means there will be more competition for less targeted ads,” noting that, at this point, it is still too difficult to predict how Topics will work in practice.

For reference, the IAB Audience Taxonomy contains approximately 1,500 audience segments. “One of the most popular drinks in the U.S. is Coffee,” Zirnheld provided as an example. “The IAB Taxonomy has ‘Coffee,’ ‘Coffee & Tea,’ ‘Coffee Creamer,’ ‘Coffee Filters,’ and ‘Tea/Coffee – Ready-to-drink.’ The closest topic Google has (at the moment) is ‘Food & Drink.’”

Despite the relatively low number of topics designed into the initial proposal, Google may already be aware of this issue: “This is a starting point; we could see this getting into the low thousands or staying in the hundreds [of topics],” said Ben Galbraith, Chrome product director.

In addition to the potentially limited topics, “The limited timeframe could be concerning for advertisers, as they are used to much more persistent inclusion of an audience than one to three weeks,” Bacchini said, caveating that it remains to be seen whether keeping interests more current might also yield benefits. Levy also touched upon this concern: “It feels more directionally accurate than truly precise,” he said. “I hope for some sort of a boolean setup longer term where we’re able to combine, expand or narrow topics, but of course time will tell.” 

As a privacy measure, there is a 5% chance that a random topic is returned, according to the GitHub page. This is to ensure that each topic has a minimum number of members. “While I understand that this helps ensure anonymity and privacy for internet users, this is obviously not a good thing for advertisers,” Zirnheld added.

Chrome might be the only browser to adopt, but that might not matter for some

“Chrome is still the big boy in the browser war,” said Steve Hammer, president and co-founder at RankHammer, “I do think Edge will matter as more people get Windows 11, but that’s the lone one I’d worry about for clients.”

“While Chrome’s market share is (slightly) shrinking, I don’t anticipate this’ll change our usage at all,” Levy said, “Rather, it will all fit into a broader theme of treating the data as directional rather than ‘right.’”

“If it’s limited to Chrome, we’ll see how that affects iPhone users,” Geddes said, noting that, “The lack of cross-browser support is a bit worrisome, but it won’t affect anyone’s budget if they are getting good returns from their marketing dollars.”

If Chrome claims enough of the browser market, that might empower Google to continue with the Topics API without having to go to the bargaining table with its competitors. That independence can help the company stick to its Privacy Sandbox timeline, which shows that all associated initiatives are slated to be launched in Chrome sometime in Q4 2022.

Is Topics an improvement over FLoC?

As with all potential third-party cookie replacements, Topics must be evaluated from the user privacy perspective as well as the advertiser perspective. “FLoC raised privacy concerns and Topics seems more privacy-friendly and attempts to provide more control and transparency to internet users. In that way, Topics is ‘better,’” Zirnheld said.

“However, this means broader targeting for advertisers, meaning less control over who sees our ads,” she noted. “We might have to get more creative with targeting for our clients if this is the route Chrome is taking.”

“For advertisers, I expect that Topics wind up more restrictive with less options and less precision than we were hoping for from FLoC (which is already a reduction of current tactics),” Levy said. “It’s annoying, but also encouraging that Google is trying to come up with a solution that works for everybody.” 

Google is trying to address the significant pushback and concerns provoked by FLoC, said Yahoo CBO Iván Markman. “It is yet to be seen whether this next iteration is workable, given how high level and short-time-spanned it is. Google’s FLoC received negative policy and industry feedback, and there was concern that FLoC IDs could have been exploited for cross-site user tracking. With the release of Topics API, Google is providing a higher level of user obfuscation and localized browser storage vs. a centralized storage location.”

Wayne Coburn, director of product at cross-channel marketing platform Iterable added: “Google’s pivot — from FloC to Topics — shows that consumers have lobbying power and a voice they are not afraid to use. People understand that their data is valuable, and they are moving to preserve the value of their assets. With FLoC, Google was trying to ensure their continued dominance in the advertising space, and both consumers and the ad industry responded with a resounding no. With Topics, Google is admitting they need to do more to preserve and protect consumer privacy.”

Ultimately, third-party cookies are going away, so expect growing pains

“The current conversations around FLoC Topics highlight one thing: Third-party (aka advertising) cookies are dead,” said Coburn. “It is more important than ever for marketers to have and maintain quality first-party data. Consumers have to be able to trust the brands they interact with — from the ethics of the brand through to the way it handles personal information — and if a consumer doesn’t trust a brand, they aren’t going to let their data anywhere near it. That isn’t going to change, so the way big tech handles data has to.”

However, “Anything that is a departure from cookies is going to feel like a step down in targeting, I think,” Bacchini said. “We are going to have to adjust our thinking about what ‘accurate targeting’ actually means and come down off of the sense of strong or accurate targeting that we feel like we have had up until this point.”

Additional reporting by Kim Davis.


About The Author

1640838256 758 Inclusive marketing resources to strengthen your brands messaging

George Nguyen is an editor at Third Door Media, primarily covering organic and paid search, podcasting and e-commerce. His background is in journalism and content marketing. Prior to entering the industry, he worked as a radio personality, writer, podcast host and public school teacher.


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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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