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Using Google Analytics 4 integrations for insights and media activations

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Using Google Analytics 4 integrations for insights and media activations

No matter which stage of Google Analytics 4 implementation you’re currently involved in, the opportunities to integrate with other products shouldn’t be overlooked. The best part is that the basic versions are free for everyone, so there are quick wins to be had if you aren’t using these yet.

Other features and reporting experiences aside, an edge that Google Analytics has over other analytics platforms is that it fits well with the Google Marketing Platform (GMP). If you’re using Google Ads, Search Ads 360, DV360, or other media tools in the suite, GA can be a hub, as well as a source in the media activation process.

GA integrations as a hub

The paid media platforms in GMP have advanced, automated reporting. These platforms are powerful tools to analyze the beginning of the user journey by drawing people to the site and to the end of the experience by converting. 

What about the middle? A solid Google Analytics implementation offers multi-step conversions, custom user behavior data and rich segment data to build and share audiences.

GA integrations as sources for insights

Google Analytics 4 isn’t just about analyzing data, it’s about acting on it. For example, the Audience feature leverages your analytics implementation — you can use the data to segment users and create audiences for remarketing, targeting, A/B testing, and personalization. 

Through settings in GA, you can also link other products and share audience and conversion data.

Below are the integrations currently available for Google Analytics 4 as of June 2022. Notice that it’s already quite a lengthy list.

  • Google Ads.
  • BigQuery (extra costs are incurred in Google Cloud).
  • Display & Video 360 (DV360).
  • Google Ad Manager  (GAM).
  • Google Merchant Center.
  • Google Optimize. 
  • Salesforce Marketing Cloud (SFMC) (this one requires the Salesforce Journey Builder). 
  • Search Console.
  • Play integration.
  • Search Ads 360 (SA360).

The first step to building out your analytics insights is taking inventory of your GMP stack. Which products are you using right now? The products will depend on what type of site or app you have and the products in which you are investing. However, three of those integrations can apply to all properties — BigQuery, Search Console and Optimize. It doesn’t matter if you’re an advertiser, publisher, retail or service site — each of these integrations is a possibility to use today for free in Google Analytics 4. 

Let’s take a closer look at these three fundamental integrations.

BigQuery

What is BigQuery? A Google Cloud data warehouse that’s not exclusively for Google Analytics or GMP.

Who is it for? Teams and leaders that will benefit from this connection are involved in areas like BI, data science, and data administration.

With BigQuery, you’ll have all of your data exported to a data warehouse that you own and control. Once the data is in Google Cloud, there’s freedom to send to another database, blend with data outside of Google Analytics, and perform advanced reporting in other tools. The GA BigQuery data has other benefits, including integration with CRM data.

How to integrate. The integration is self-serve within the interface, but there needs to be a BigQuery project available to link the Google Analytics tool. If you do not have a project yet, go to the Google APIs Resources page to create a new one. On the page, it looks technical and there’s code references, but that part isn’t necessary and you can skip it. The instructions for doing it through the interface are in modules in the “Console” tab. Below are the simplified steps:

  1. Select the option to create a project on the upper left of the page.
  1. Name your project, select the “Create” button, and there’s now a new project in Google Cloud. 
  2. The last step is turning on a setting to use BigQuery. There are a lot of technical options in the menu, but the only area you need to go to for this is “Library” under “APIs & Services,” where you can search for BigQuery and enable it.
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After the project is created, it’s ready to be integrated with Google Analytics 4. Back in the GA interface, the option to link it is under property settings. 
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Now your raw GA4 data will start collecting into the project to be available for immediate use. Out of the integrations listed here, this one has the most steps. However, the other products are just a few clicks. (Note: BigQuery comes at an extra cost. However, for most accounts it will not be significant — it is sometimes just a few dollars.) 


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Search Console

What is Search Console? It’s a platform for monitoring in-depth metrics and reports related to organic Google search performance and site speed.

Who is it for? Most teams will benefit in some way from analyzing search data. This includes content creators, SEO teams, and web developers.

How to integrate. A Search Console property must be created, and it must be verified. Sometimes this is as simple as selecting a few buttons in the interface.

Once there is a Search Console property, or once there is access to an existing property, the link is in the same menu as the BigQuery link under Property Settings.

After, organic metrics and reports that are not out-of-the-box will be available in Google Analytics 4. Once the product linking is complete and working, there’s a last step to enable GA users to benefit from the enhanced data. It may be noticeable (and possibly confusing) that the Search Console data isn’t within the default interface navigation. To see the reports, the reporting collections in the menu should be edited.

To modify the navigation, select “Library” at the bottom of the screen:

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Next, begin the process to create a collection, under Collections. The template for Search Console will be located as the bottom right option. The option to start from scratch without a template is also available.

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After saving, go back to the library area and publish your collection. The report should now be accessible from the left navigation:

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Optimize

What is Optimize? Optimize is an A/B testing and personalization tool.

Who is it for? It’s for marketers, conversion rate optimization (CRO) teams, content creators, or UX leads.

How to integrate. This one isn’t as apparent as the other links. Right now, the integration option does not show up in the Google Analytics property settings. That doesn’t mean that it’s not available, it means that the linking hasn’t been done yet. 

So, instead of starting in Google Analytics, the process begins in the Optimize interface. Under Settings, navigate to the Measurement section and edit. A dropdown will be available with a list of all the properties that you have access to. Unlike the previous version of Google Analytics, the integration links to a GA data stream instead of the GA property.

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Once it’s linked, the icon will show up in Google Analytics:

1656518266 300 Using Google Analytics 4 integrations for insights and media activations

When the link is active, Google Analytics 4 data can be used for audience targeting, conversion optimization, and objectives.

Note: If you are already linked to a legacy Google Analytics property, check with your team to make sure that it is ok to switch it to the Google Analytics 4 data.

Read next: Is Google Analytics going away? What marketers need to know

With the integration of BigQuery, Search Console, and Optimize, anyone can advance their analytics capabilities for current or future initiatives.

Below are brief explanations of the media platforms that Google Analytics 4 can integrate with. Most of these depend on what products are in use, what vertical an organization falls under, or other specific contexts and devices. 

Google Ads

What is Google Ads? It’s the most popular and well-known search advertising tool, formerly known as AdWords.

Who is it for? It’s for marketers, advertisers and paid media specialists.

What it does. Google Ads was one of the first products to have GA4 linking capabilities. It’s built to provide value both ways – by getting Ads metrics and reporting from Google Ads to GA and by sending audiences and getting conversions from GA to Google Ads.

Google Analytics 4 to Google Ads linking information and instructions here.

Display & Video 360

What is DV360? It’s a programmatic advertising platform. Also referred to as a DSP, DV360 is used to bid on display ad placements on publisher/content sites.

Who is it for? It’s for marketers, advertisers and paid media specialists within enterprise organizations.

Google Analytics 4 to DV360 linking information and instructions here.

Search Ads 360

What is SA360? This is like Google Ads, but super-charged. It’s a management and bidding tool to run ads across multiple channels and search engines.

Who is it for? It’s for marketers, advertisers and paid media specialists within enterprise organizations.

Google Analytics 4 to SA360 linking information and instructions here.

Google Ads Manager 

What is GAM? It’s an enterprise platform for publishers to manage and serve ads on their site or app.

Who is it for? Marketers, advertisers and paid media specialists within enterprise organizations.

Google Analytics 4 to GAM linking information and instructions here.

Google Merchant Center

What is Google Merchant Center? A separate platform from Google Ads to promote products, mainly on Google Shopping.

Who is it for? It’s for marketers and advertisers within an e-commerce organization.

Google Analytics 4 to Google Merchant Center linking information and instructions here.

Salesforce Marketing Cloud

SFMC is for cross-channel digital marketers. This integration is meant for use in the SFMC Journey Builder and can bring in Google Analytics data.

Google Analytics 4 to SFMC information and instructions here (through Salesforce).

Google Play

Google Play is Google’s app store and it’s for digital marketers who analyze in-app purchases and subscriptions.

Google Analytics 4 to Google Play linking information and instructions here.

If your organization is using any of those media tools, it’s a great time to start the strategy and process of leveraging Google Analytics 4 data to enhance analysis across multiple products and teams. There’s no reason not to start since they are available to all GA4 properties.


Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here.


About The Author

Using Google Analytics 4 integrations for insights and media activations

Samantha has been working with web analytics and implementation for over 10 years. She is a data advocate and consultant for companies ranging from small businesses to Fortune 100 corporations. As a trainer, she has led courses for over 1000 attendees over the past 6 years across the United States. Whether it’s tag management, analytics strategy, data visualization, or coding, she loves the excitement of developing bespoke solutions across a vast variety of verticals.

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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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