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How Marketers Are Preparing for Google’s Third-Party Cookie Phaseout

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How Marketers Are Preparing for Google's Third-Party Cookie Phaseout

Over the past few years, consumers have become increasingly concerned with how companies use their data. And many feel passionate about protecting their privacy — in fact, HubSpot’s Blog Research found 80% of consumers believe data privacy is a human right.

Data security has become a critical component for long-term customer retention and loyalty. So it’s vital brands behave responsibly when it comes to collecting and protecting consumer data.

But many marketers have relied on third-party data for years, so the phaseout of Google’s third-party cookie in 2023 will likely cause some concern. Fortunately, it doesn’t have to.

Here, let’s explore the effective strategies marketers will implement to ensure they’re still reaching new audiences and connecting with customers even without third-party data.

How Marketers are Preparing for Google’s Third-Party Cookie Phaseout

1. Marketers are enhancing or developing their data collection operations and management models.

One surefire way to prepare for the third-party cookie phaseout? Begin developing or refining a strong first-data party data strategy.

As Microsoft Advertising’s Head of Evangelism, John Lee, told me, “Microsoft Advertising is working with the digital advertising industry and its clients to evolve and uplevel data privacy maturity for a privacy-first cookieless world. While there is no market-ready solution available today that manages data end-to-end, our guidance for our clients is to take steps now to prepare a first-party data strategy and to conduct robust data management practices.”

how marketers are handling the third party cookie phaseout

He adds, “First-party will lead the way and now is the time to ensure that you have the best resources and information available to enhance or develop data collection operations and management models. It is your ability to communicate with your customers transparently and in a personalized, yet meaningful way, that will enable better relationships and business success in the future.”

Ultimately, creating a strong first-party data management framework will enable your entire organization to transition seamlessly off third-party data while continuing to reach new prospects and leads.

To create an effective enterprise data management strategy, take a look at Everything You Need to Know About Data Management.

2. Marketers are gathering customer data through email marketing.

Cynthia Price, Litmus‘ SVP of Marketing, believes email marketing is a powerful option for continuing to collect customer and prospect data instead of relying on third-party cookies.

As Price puts it, “About eight in 10 marketers depend on third-party cookies, so when they do vanish, those who haven’t adapted their data structures and their data-gathering processes will struggle to effectively personalize their email programs.”

To combat these challenges, marketers will need to shift to ensure their email strategies leverage first-party data. This will help you create a more individualized email experience

Price suggests, “Email can be used to gather customer and prospect data with new, evolving email software and with dynamic content templates. Forms, in-email purchase options, and customizable marketing paths are all valid, successful tactics to use in order to garner more first-hand recipient information.”

Price adds, “Brands with siloed data structures have been unable to achieve a full, single view of their customers, with data getting pulled into multiple directions.”

Price says, “The evolution of privacy regulations will put email even more at the center of the marketing mix — as the channel that offers the most comprehensive view into zero and first-party data, and the ability to use it effectively.”

She continues, “This adoption of zero and first-party data will also allow for more practical uses of AI in email, with AMP and dynamic content automation.”

3. Marketers are focusing more on customer loyalty and retention.

The phaseout of third-party cookies will impact how some marketers acquire new customers, but it won’t impact how marketers retain existing customers — which is why some marketers will adjust to this third-party phaseout by refocusing their efforts.

SVP of Marketing at Cordial, Carrie Parker, says, “The phaseout of Google’s third-party cookies is forcing marketers and advertisers to think about engaging their customers and audiences in more personal and authentic ways. With cookies going away, acquiring new customers will become more complex, but on the other hand, retaining customers will be a much more critical piece of the puzzle than in the past.”

She adds, “More marketers are increasingly focusing on loyalty and retention within their current customer base, enhancing their experience with the insights readily available that consumers have provided.”

Parker told me Cordial recently conducted a study and found 70% of consumers dislike online ads that target them using websites and products they’ve viewed — and, on the contrary, more than eight in 10 consumers are more likely to buy from stores and brands that communicate with them in personal, relevant ways.

Parker continues, “Consumers want more from companies when it comes to personalization than what they’re receiving from most brands these days. Personalization does not mean inserting a name on an email and hitting send. Instead, it requires considering the value added to the consumer and keeping them loyal customers. With cookies going away, first-party data strategies allow brands to emphasize personalization, loyalty, and retention of their customers. Brands can use their customer base and provide something of value to make them come back.”

how marketer are handling the third party cookie phaseout

Ultimately, the phaseout of the third-party cookie is a good opportunity to re-evaluate how you’re interacting with both new and existing customers. First-party data strategies will ultimately help you better connect with your customers.

4. Marketers will focus on the best impressions rather than the best users.

Melinda Han Williams, Chief Data Scientist at Dstillery, says, “One of the most challenging aspects of preparing for this transition is that any good campaign will include a portfolio of post-cookie solutions and technologies after third-party cookies are gone. Even the marketers who are furthest along in their post-cookie testing journeys may still have much more preparation to do.”

She adds, “New identity solutions, such as UID2 and RampID, allow advertisers to reach people who have opted-in to tracking and addressability. Marketers who have tested these solutions have progressed toward post-cookie readiness, but they’re not done yet.”

“Why? Because some people don’t want to be tracked on the internet.”

Williams points out that marketers need to prepare solutions to reach people without tracking them or compromising their privacy or preferences.

The solution here? Understanding you might not need that much data about each customer in the first place.

As Williams told me, “The good news is you don’t need to know who someone is to know whether they’d be receptive to your message. Today’s artificial intelligence (AI) enables marketers to choose the best impressions rather than the best users.”

She adds, “Once you reframe the problem this way, rather than trying to find out as much about the user as possible with increasingly limited data, it is possible to do inventory-based targeting with performance and scale rivaling the cookie-based, tracking-based solutions that will soon be retired.”

Change is always difficult, particularly when it comes to the ways in which marketers reach new audiences. Fortunately, this change is likely for the best. Shifting to a first-party data model will help your organization appeal to the majority of consumers who are hesitant to share their data with companies, and it will set you up for long-term growth after Google’s third-party phaseout.

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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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