Connect with us
Cloak And Track Your Affiliate Links With Our User-Friendly Link Cloaking Tool, Try It Free

MARKETING

The power and limitations of universal IDs

Published

on

Something must replace the cookie. It’s due to disappear by the middle of next year.

Marketers are checking out zero-party data, first-party data and cohort analysis. But don’t forget universal IDs.

At its most basic, the UID should recognize the user, compile their information, and share that data with approved partners. How that is done varies, as there is no standardized method or practice for doing this.

“Universal IDs come in two main forms: authenticated and inferred. Authenticated IDs are built by using unique pieces of user data, such as an email address. Inferred IDs are created by device-level data, such as an IP address, user agent string, and device model,” explained Mike Sweeney, head of marketing at adtech and martech software development company Clearcode. “Some universal IDs would use both user-level and device-level data to enrich the IDs and help improve match rates.”

The good news is that the UID is one pathway to a future without cookies. The bad news is that the pathway is not entirely clear, and the future is a bit hazy.

Cookies and UIDs both have their limits.

“Every company that sets a cookie has their own ID, and then has to basically do a live exchange of information or share a common cookie space,” explained Rob Armstrong, SVP for product at data transformation company Eyeota. “That’s partly why we’re in this problem because a website could have a carpet bomb of 50 different companies creating cookies.”

“While there is no one-to-one replacement for third-party cookies, universal IDs are probably the closest thing the programmatic advertising industry has to them,” Sweeney said. “However, they lack one key advantage — scale.”

A UID requires a consumer action, like providing an email in exchange for more information, while a cookie is slipped into the user’s browser simply upon visiting a web site, explained Tom Craig, CTO at consumer intelligence platform Resonate. While a cookie can track a user across multiple domains, the UID is limited to the domain the user visits. “This limitation is one of the primary reasons that marketers need to be thinking more broadly than UIDs as they plan their go-forward marketing strategies,” Craig said.

How a user identity is established requires an authentication. “Email is the easiest way to do it in the U.S., where log-ins are usually email address,” observed Chris Bell, VP for Product Management at Oracle. “In Asia, it’s the mobile phone number.”

“You have to shift. Try to meet the user where they are with the piece of personal information they are comfortable giving up,” Bell added.

One size does not fit all

UIDs are not standardized — yet. LiveRamp, The Trade Desk and ID5 are a few among many vendors offering solutions in the UID space.

The Trade Desk’s approach with Unified ID is to generate the UID using the email address provided by the customer, usually in exchange for site access or additional material, Sweeney explained.

“Companies like LiveRamp, Tapad, Signal, Neustar, Zeotap, Epsilon, Flashtalking and others, would also use email addresses to generate an ID,” Sweeney continued. “But they would also use other pieces of deterministic and probabilistic data collected from different sources, e.g. cookie IDs from web browsers, mobile IDs from smartphones, and IP addresses.”

“Proprietary solutions will never get the scale to be viable solely on their own,” Craig said. “Each site needs to implement a solution for it to be addressable, and those sites will not likely implement proprietary solutions.”

“Standardization brings adoption and it brings capital investment. It brings stability, and it’s lacking,” Armstrong said. “This is why we see certain companies having a much more prominent universal ID posture because of their presence in the industry and being a known entity that a lot of companies are working with.”

Read next: Sharing The Trade Desk’s Unified ID will not end adtech disruption

Many players in a game with few rules

The UID market is young, with about 40 or so vendors all providing solutions, Bell noted. Starting such a company is easy. What’s hard is “getting one to be meaningfully different.”

To succeed, they must “have a strong touchpoint” with publishers, so that they are using that firm’s UID scheme, Bell said. Then you must encourage adoption by adtech providers. It is a game about creating mindshare.

“The lack of standardization around universal IDs isn’t too much of an issue at the moment,” Sweeney said. “However, the sheer number of universal IDs causes issues around interoperability.”

For the digital marketer, it is too soon to place a winning bet on one UID. Some UID solutions revolve around deterministic identification, others rely on probabilistic determination. “It’s not clear at this point what the answer will be,” Bell said. If all these competing UID firms knew the answer, “they’d all be skating towards the puck.” He said. “My hypothesis is [there will be] a rapid winnowing down to a smaller number [of solutions].”


Get the daily newsletter digital marketers rely on.


Don’t throw your hands up in despair

UID is young. Best practices are still being discovered. What can marketers do?

“Focus should be more about building relationships with customers and collecting consented personal data,” Bell said. And cover your bets in the vendor landscape. “Putting all your chips on a single UID scheme is risky.” Things will shake out in the next 12 to 36 months.

“It’s definitely a time of testing.” Armstrong said. “Test the parachute before you jump out of the plane.” Try to understand performance in regular browsers with cookies, tested against browsers without cookies, but using UID.

“Also be mindful of the methodology going into it. If it’s probabilistic, then it’s going to be more like a cookie. If it’s deterministic, it’ll look a lot different. And in that case, you could start to think about it a little bit more strategically versus just, does this work?” Armstrong added.

“I think a great first step would be to speak to your existing adtech partners and find out whether they’ve integrated with any of the universal ID solutions,” Sweeney said.

Craig offered this checklist:

  • What interactions are had with consumers, both customers and prospects?
  • How can those interactions be identified after cookie deprecation?
  • Is there an opportunity to capture or request email addresses from those interactions?
  • Which identity provider, if any, best suites the business’ needs?
  • Does my company have a strategy to increase coverage of identities and collect emails?

“Companies with email and UID collection will be able to work with programmatic platforms to target and retarget those customers,” Craig said. “They will have the ability to know more and take personalized actions with their customers. Without UID collection, marketing will become limited to contextual or cohort-based targets and all personalization will be a thing of the past.”


About The Author

Getting back to basics Marketing ROI
William Terdoslavich is a freelance writer with a long background covering information technology. Prior to writing for Martech, he also covered digital marketing for DMN. A seasoned generalist, William covered employment in the IT industry for Insights.Dice.com, big data for Information Week, and software-as-a-service for SaaSintheEnterprise.com. He also worked as a features editor for Mobile Computing and Communication, as well as feature section editor for CRN, where he had to deal with 20 to 30 different tech topics over the course of an editorial year. Ironically, it is the human factor that draws William into writing about technology. No matter how much people try to organize and control information, it never quite works out the way they want to.

Source link

Keep an eye on what we are doing
Be the first to get latest updates and exclusive content straight to your email inbox.
We promise not to spam you. You can unsubscribe at any time.
Invalid email address

MARKETING

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

Published

on

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!

Keep an eye on what we are doing
Be the first to get latest updates and exclusive content straight to your email inbox.
We promise not to spam you. You can unsubscribe at any time.
Invalid email address
Continue Reading

MARKETING

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

Published

on

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

Amazon pillows.

(more…)

Keep an eye on what we are doing
Be the first to get latest updates and exclusive content straight to your email inbox.
We promise not to spam you. You can unsubscribe at any time.
Invalid email address
Continue Reading

MARKETING

A deeper dive into data, personalization and Copilots

Published

on

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.”

Source link

Keep an eye on what we are doing
Be the first to get latest updates and exclusive content straight to your email inbox.
We promise not to spam you. You can unsubscribe at any time.
Invalid email address
Continue Reading

Trending