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Identity management in a world without third-party cookies

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Identity management in a world without third-party cookies

The restrictions on data collection via third-party cookies have made customer identification more important than ever. And while many marketers focus primarily on developing new methods of data procurement and analysis, some professionals argue improving customer experiences accomplishes the goal more effectively.

“We’re talking about customer experience — classically that can mean outbound campaigns, product-driven or brand-driven, but it can also mean modern, inbound campaigns where we’re trying to map and follow a customer journey,” said Steve Zisk, senior product marketing manager at Redpoint Global, in a recent webinar. “In that context, we all understand that the customer data we’re looking at today is based on the number of different channels and the devices they like to use.”

“The real core question becomes, ‘What can we, as marketers, do to improve the customer experience?’” he added.

Successful customer identity management begins with orchestrating high-quality customer experiences. This means marketers must address their data issues and, ultimately, craft engaging journeys that help create full customer profiles.

Data quality issues

“One of the challenges that we see with our clients is getting quality data,” said Kris Tomes of Redpoint in the same webinar. “The struggle becomes, ‘Is my data dirty? Is there consistency in how it’s formatted and how it’s stored?’”

“At the end of the day, there are [often] inadequate data,” he added.

Identity management in a world without third party cookies
Source: Kris Tomes

Poor data makes it difficult for brands and marketers to communicate effectively with their customers. Zisk and Tomes highlighted some of the most common data quality pain points brands experience:

  • Dirty data, which is missing, inconsistent, or erroneous
  • Noisy data, which is conflicting or misleading
  • Sparse data, which has too few values or too many attributes
  • Inadequate data, which wasn’t fully collected or used biased sampling

In an era of third-party cookie depreciation and privacy concerns, these pain points can be addressed effectively with identity resolution platforms. Tools of this nature comply with privacy legislation while providing valuable insights to marketers by connecting customer data from multiple touchpoints.


Marketers look to adtech and agencies to solve the addressability

Identity resolution is not only critical to marketing success but is essential for compliance with consumer privacy laws such as CCPA and GDPR. Explore the platforms essential to identity resolution in the latest edition of this MarTech Intelligence Report.

Click here to download!


What should marketers do with third-party data?

“We all recognize that the data we have about customers is imperfect and incomplete,” Zisk said. “To overcome those problems, we often will turn to something else to get more information about our customers. Sometimes it can be very reliable … Other times we’re looking for other information from adtech or something else. At some level, we feel that the information isn’t relevant or personal enough.”

Zisk noted that marketers may also use third-party data to “shake the tree,” or attempt to procure customers from larger platforms such as Amazon. However, this information may not be the most actionable.

“[Third-party data] is cheap and it’s easy, but there are potentially some problems with it,” said Zisk. “Consumers may not like to have ads following them around the network. They may not want to come back if we’ve done something to fatigue them.”

He added, “39% of consumers say they’ll no longer do business with a company that doesn’t offer a specific, personalized experience, so if I misuse the data, I’m going to have problems.”

Zisk argues that procuring first-party data is a more effective way to understand consumer preferences. Instead of relying on a slew of ads across third-party platforms, marketers can use information gleaned from their own resources to gain insights and resolve all signals from customer journeys. This can help improve personalization and, in turn, engagement.


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Why brands are turning to identity resolution platforms

To make the most out of customer data, more and more marketers are turning to identity resolution processes. This data collection method works to create a picture of the customer, including their preferences and needs, using information from relevant touchpoints.

Tomes says identity resolution is all about “finding commonality within an entity across disparate data sources.”

“It’s about identifying the elements that we would use to create the [customer] identity,” he said. “It’s about pumping all that data into an identity resolution process that uses those [data] fields to compare the records.”

“Across those disparate data sources we’re able to identify a person,” he added.

1645106529 686 Identity management in a world without third party cookies
Source: Kris Tomes

He and Zink recommended that marketers prioritize creating a “golden record” while undergoing the identity resolution process. This information is designed to serve as the single source of truth for customer profiles, helping to ensure marketers retain the most accurate view of their audience.

1645106530 794 Identity management in a world without third party cookies
Source: Kris Tomes

“That record shows the best way to identify a person,” Tomes said. “It could be based on any number of rules … It usually is narrowed down to the elements of PII [personally identifiable information].”

PII is the cornerstone of identity resolution and management. Without it, marketers have little chance of offering engaging, personalized experiences.

Tomes suggests marketers build their golden profiles using this information gleaned from identity resolution platforms. And once collected, they can use it to build better environments for their customers.

“At the end of the day, we can begin to create summary data sets,” he said. “Then we can look across transactions and web behavior and begin to create a one-stop-shop.”

Watch this webinar presentation at Digital Marketing Depot.

Identity resolution platforms: A snapshot

What it is. Identity resolution is the science of connecting the growing volume of consumer identifiers to one individual as he or she interacts across channels and devices.

What the tools do. Identity resolution technology connects those identifiers to one individual. It draws this valuable data from the various channels and devices customers interact with, such as connected speakers, home management solutions, smart TVs, and wearable devices. It’s an important tool as the number of devices connected to IP networks is expected to climb to more than three times the global population by 2023, according to the Cisco Annual Internet Report.

Why it’s hot now. More people expect relevant brand experiences across each stage of their buying journeys. One-size-fits-all marketing doesn’t work; buyers know what information sellers should have and how they should use it. Also, inaccurate targeting wastes campaign spending and fails to generate results.

This is why investment in identity resolution programs is growing among brand marketers. These technologies also ensure their activities stay in line with privacy regulations.

Why we care. The most successful digital marketing strategies rely on knowing your potential customer. Knowing what they’re interested in, what they’ve purchased before — even what demographic group they belong to — is essential.

Read next: What is identity resolution and how are platforms adapting to privacy changes?


About The Author

4 ways to build a successful ABM strategy

Corey Patterson is an Editor for MarTech and Search Engine Land. With a background in SEO, content marketing, and journalism, he covers SEO and PPC to help marketers improve their campaigns.


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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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