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4 things to beware of with Google’s Performance Max automated campaigns

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4 things to beware of with Google’s Performance Max automated campaigns

4 things to beware of with Googles Performance Max automated

With Google on its way to over $200b per year in ad revenues, companies that aren’t yet advertising online should think long and hard about why everyone else but them seems to be growing their business with Google Ads.

Perhaps they’ve tried and failed. Let’s face it: Especially in recent years, Google advertising has gotten increasingly automated, yet strangely also more complex with a multitude of campaign types, bidding strategies, and targeting options to choose from. 

In what appears to be an effort to simplify, Google recently introduced a new, streamlined, all-in-one automated-campaign type: Performance Max. This new campaign needs minimal setup and promises to run a company’s ads as appropriate across Google’s six primary advertising channels: Search, Maps, Display, Gmail, Discover and YouTube. 

But as with any automation, Performance Max shouldn’t be thought of as a set-it-and-forget-it campaign. After all, as we’ve established many times before, the best PPC results come from humans and automation working together. Or as Frederick Vallaeys put it in his first book, Digital Marketing in an AI World:

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What inputs does Performance Max use?

To get started with automated ads on Google, you need to provide:

  • Your marketing objectives and goals
  • Budget
  • Creative assets 
    • Text 
    • Images 
    • Video (optional, since this will auto-generate)
  • Geo-targets
  • Feeds (optional)
    • Google My Business
    • Google Merchant Center
    • Dynamic Ads feed
    • Business data feeds
  • Audience signals (optional)
    • First-party Audiences, including remarketing lists
    • Google Audiences, including custom audiences

From there, automation is off to the races and promises to show your ad when it expects to be able to get you a conversion.

Where do Performance Max ads run?

To find conversions that meet your stated objectives, Performance Max can, as appropriate, automatically serve your ad across its six channels: Search, Maps, Display, Gmail, Discover, and YouTube. Performance Max will replace Smart Shopping and Local campaigns but is intended to be a supplement rather than a replacement for the other campaign types like Search and Display.

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Image source: Google.com January 2022

For new advertisers, this is a big deal and significant simplification because the same possible coverage would have previously required creating a separate campaign for each channel. And for advertisers who are just getting started with Google Ads, they may not have the time, or necessary experience and skill, to set up each and every one of these campaigns correctly to drive success. Now, with only a single campaign to create, advertisers can start seeing immediate results and focus on optimizing those aspects of their campaigns that have the biggest upside potential.

What could go wrong?  

It’s important to understand what any automation’s capabilities and limitations are. If you overestimate an automation’s capabilities, and it fails to deliver, you really have only yourself to blame.

A good analogy is to self-driving cars’ five levels of automation, as defined by the SAE (Society of Automotive Engineers) and National Traffic and Highway Safety Administration: 

What happens when a ‘self-driving’ car crashes?

As long ago as 1979, IBM put the prosecution’s case this way:

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Image source: https://samim.io/p/2022-01-24-a-computer-can-never-be-held-accountable-an-ibm-slid/

In Los Angeles, a driver is now being prosecuted for vehicular manslaughter for letting his “self-driving” car run a red light and killing two people in the process. The driver treated his car’s capabilities like a level 5 automation when in fact, it was just a level 2 automation or a driver-assistance feature.

Likewise, in PPC, Performance Max campaigns are not level 5 fully self-driving automation, but more like a level 2 or 3 assist feature. Performance Max handles a narrowly defined task quite well, but it lacks context to be able to do it fully alone.

It’s up to you, the human advertiser, to supply that context, which includes your ultimate business goals. As an account or campaign manager, you’re in the driver’s seat. Google automation can’t be held accountable when problems arise. 

So what can go wrong…

1. You give the automation incomplete goals. 

Think of automation in PPC as your newest team member. When a new person joins your team, whether they’re a hired consultant or a new full-timer, you’ve got to teach them about your business, like your goals and how you make money. If you share incomplete information, for example, by failing to specify that you don’t just want leads but rather leads that convert into sales, they will probably do a poor job.

It’s the same with PPC automation. For example, if you tell the automated Google Ads system that your goal is to get leads, it will probably get you lots of leads. But that wasn’t your real goal. You want leads that turn into customers. It’s critical to have a way to feed this and other goal-related data back to Google so they can deliver what you truly want.

Tools like Optmyzr can help advertisers create value rules to help steer Google automation to better quality conversions. 

2. You supply Google with poorly optimized feeds.

If you sell stuff, or you have multiple business locations, you can give this data to Google through one of their many structured data formats. In the case of products, this is a Google Merchant Feed. 

Google then uses the data from the feed to decide what searches are relevant to your offer and show what it deems the best image, title, and price in each ad. But if your feed contains incomplete data, or if your title text is poorly optimized, your ads will look and feel worse than your competitors’, and you’ll either get fewer or more expensive conversions.

While long-time PPC pros may stress the importance of keywords, bids, and creative, Performance Max lets you control almost none of this. In Fred Vallaeys’s just-published second book, Unlevel the Playing Field: The Biggest Mindshift in PPC History, he explains that modern PPC managers shouldn’t manage every detail but should rather know how to manage Google Ads on the periphery, where they interface with the automated system. 

Knowing how to optimize a feed is a great example of this. The feed connects to the ads system, where Google’s automation takes over and turns it into keywords, targeting, and the ads themselves. 

And if you want more control, PPC software can help turn your feed into keywords, ads, and campaigns from a template you control.  

3. You don’t leverage first-party data.

As privacy concerns mount, there’s a big shift away from third-party data in online advertising. That means that first-party data is gaining in importance. If you have a list of existing customers, feed that first-party data into your Google Ads campaigns to improve targeting. Yes, over time, Google AI could probably learn what type of audience would be best to target. But why let the system potentially waste thousands of dollars to learn what you could have told it right from the start?

And with more advanced PPC tools, you can bring virtually any first-party data into a rule engine to automate your PPC decision-making.

4. You fail to write “helpful” ad components.

If you’re used to advertising on social media and similar platforms, you may have gotten used to writing ads or posts that aim to be attention-getting above all. After all, when a user is rapidly swiping down their feed, the best way to stop them maybe with a controversial title or catchy image. 

Things are different and more complicated with Google Ads. People use Google to search for things they already know they need. If you can help them, there’s no need to stop them in their tracks. Instead, aim to answer their questions and assure them that yours is the best possible solution to their problem. How will you help them? That means including unique value propositions and clear calls to action in the ad text components that will then make up the various parts of your Responsive Search Ads (RSAs). 

For more great insights about how to create effective RSAs, take a look at Optmyzr’s 2021 RSA research and its RSA presentation at SMX Next.

So while Google makes it ever easier to run automatic PPC ads, the reality is that these campaigns will deliver far better results with your ongoing help and optimization. You can either do this work manually or get help from automations you manage and control, like those available in PPC-management software suites like Optmyzr

“Automation layering” is what we call automation you install that provides checks and balances to Google’s automation. This is automation you, the manager sitting in the driver’s seat, insert in the interface between you and the Google Ads system. To do this, you don’t need to spend inordinate amounts of time monitoring all the minutiae of the ad engine. Instead, use simple rules and scripts to do this work for you. You can then focus on the strategic elements that add the most value when you, the human driver, deploy them in the system.

Automation layering PPC software doesn’t have to cost a lot. Optmyzr recently introduced Optmyzr Lite, a free tier of service specifically designed for new Google advertisers with single-business ad budgets under $10k per month. Advertisers get access to a dashboard, reports, audits, and optimization suggestions different from and independent of those Google provides. It’s a great way to monitor and correct Google AI when it could use your help, as it inevitably will at times. 
Many advertisers say: don’t let the auctioneer tell you how or when to bid. Optmyzr Lite is a trustworthy third-party tool that can offer a different perspective on how to optimize your Google Ads account so that you can focus on growing your business.


About The Author

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Optmyzr’s PPC management platform provides intelligent optimization suggestions that help advertisers across the world manage their online advertising more effectively. Optmyzr connects with Google Ads, Microsoft Ads, Amazon Ads, Facebook Ads, Google Analytics, Google Merchant Center, Google Sheets, and SA360. The company was founded by former Google AdWords executives. The Optmyzr PPC suite includes over 30 tools to improve Quality Score, manage manual and automated bids, find new keywords, A/B test ads, build new campaigns, manage placements, automate budgets, and automate reports. Optmyzr was named best PPC management software at the 2020 US, UK, and Global Search Awards.


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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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