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How to control Performance Max campaigns

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How to control Performance Max campaigns

Performance Max campaigns from Google are causing quite the stir in the advertising world. It’s one of the fastest major launches we’ve seen, with the product going from general availability (Nov 2021) to forced migration (Sep 2022) in less than a year. Here we’ll share some of the tips we’ve gathered from talking to a lot of our customers and several PPC experts, including some Googlers in our PPC Town Hall episodes.

Control is shifting to the periphery of the ads system

Performance Max campaigns are one of the most automated campaign types available in Google Ads, and the lack of controls is one of the main causes for concern among advertisers.

But as our founder Fred Vallaeys described in his recent book, “Unlevel the Playing Field, the Biggest Mindshift in PPC History,” advertiser controls still exist in the era of automated PPC; they’ve just shifted to be more about the big picture and less about granular details. Think things like:

  1. Set correct targets that are related to business goals.
  2. Feed more timely and more detailed conversion information into the Google AI.
  3. Optimize the structured data and feeds that Google uses to generate creatives and match ads to queries.
1661443777 230 How to control Performance Max campaigns

Automation needs space to learn

Historically, a best practice in PPC was to exert total control over a campaign by using exact match keywords with tightly themed ad groups. In Performance Max, it’s rather difficult to emulate this strategy because there are neither keywords nor static ads. Instead, machine learning determines on the fly what queries could be relevant and then generates a dynamic ad for each.

So the knee-jerk reaction to Performance Max’s lack of control may be to seek ways to reign in the automation and make it behave more like what we’re used to from 20+ years of having close control.

But some advertisers, like Kasim Aslam, pointed out in a recent PPC town hall that giving the machine more room to experiment may not be such a bad thing. It’s like putting a flea in a small box. Fleas can jump eight inches, 150 times their body height. But if you put one in a box that’s one inch tall, it’ll learn never to jump higher than that, wasting its potential. Could it be the same with PPC automation?

Regardless of how tightly you control it, the machine will identify a slice of traffic where it’s comfortably producing the results you’ve asked for. When you eventually want more results and change some of the boundaries, it may prioritize continuing to operate in the space it already knows well because that’s where it has a higher degree of confidence in its predictions.

So there’s something to be said for allowing the machine some freedom to test and let it find users who will convert in some unexpected places to achieve the greatest possible incrementality.

Here’s a concrete example of machine learning doing a good job for advertisers when it’s not being constrained. When Optmyzr recently evaluated 170 million ads to see the impact of responsive search ads (RSAs) that have now replaced expanded text ads, it was clear that giving the machine more breathing room led to more conversions.

The main reason is that ad groups with RSAs got around twice as many impressions as ad groups without RSAs because the machine was able to make ads relevant for a significant new number of searches. And while the conversion rate was around 11% worse, the large increase in impressions more than made up for that.

How to control Performance Max campaigns
Source (Optmyzr internal data from May 2022. 13,671 accounts and 1.7m ads)

Set expectations for how long it will take automation to learn

Besides the lack of ad control which it shares with RSAs, Performance Max exhibits a lot of other freedoms that can make it a nerve-racking proposition for advertisers to try:

  • Works with ad assets rather than ads that are fully written out by advertisers.
  • Operates with few keyword boundaries, much like Broad Match keywords would operate in a search campaign.
  • Bids are automated and determined by advertiser goals rather than a restrictive max CPC.

Learning what works takes time for the machine, and it’s frustrating that human insight is relatively hard to add to the equation to help speed up the learning. To get the most out of Performance Max, it needs two weeks of relatively unencumbered time to experiment and learn.

Agencies and PPC managers need to ensure their clients are ready for this wait. Setting this expectation requires a bit of client re-education because the industry has long touted a key benefit of PPC to be the immediacy of results and the corresponding ability to do instant optimization. While you can still see clicks being reported in near-real time, making course corrections until the machine has had some time to experiment and learn may be the wrong move.

Make sure your clients know your plan for how long you will let the machines learn before you start optimizing.

Advertisers must expect to give the machine time and not interfere with constant tweaking of a campaign that is still learning. Optmyzr has some great tools to help advertisers make sense of experiments in Google.

Creative assets make or break your campaign

Optimizing targeting and bidding have historically been the most important elements of running a great PPC campaign. Sure, ads were important too. But if you had the best ad and showed it to the wrong audience or paid too much for it, you’d get poor results. On the other hand, though, a mediocre ad shown to the right audience at the right price could still do quite well.

But now, with Performance Max, advertisers choose neither keywords nor bids. So the creative all of a sudden has become a much more important optimization lever. And for many advertisers used to only writing text ads, the mere fact that they’re now asked for video ads too can be daunting.

The advice we’ve heard in conversation with our customers is that it’s more important to have fresh video ads rather than perfect ones. It’s much more like social media advertising, where ads regularly go stale and stop driving results.

So the advice we have here is not to overthink video ads. Shoot some quick ads on your phone, or repurpose any assets you might already have. Neither may look beautiful, but the machine has a way of getting audiences to start clicking on these ads. And once the prospect is on your site, all the hard work you’ve done over the years on your landing pages takes over, and those new prospects can become customers.

When it comes to optimizing text assets for ad formats like RSAs, Optmyzr can streamline that quite a bit by providing insights into which frequently used assets are performing well, as well as suggesting variations for new copy when your current ones aren’t delivering.

You have flexibility with structure

Another control you still have is related to campaign structure.

E-commerce advertisers can continue to use shopping campaigns for full control or migrate their Smart Shopping campaigns to Performance Max (this is also happening automatically). The same concepts for structure that have worked well in the past can continue to work.

For example, maintain different campaigns based on profit margins so you can set different target ROAS values to maximize overall company profits. Use custom labels in the feed to split products into different campaigns, asset groups or listing groups.

With more advanced structures like this, an important optimization step is ensuring the Google Ads account has the right products in the right places.

For advertisers with constantly changing inventories or large product catalogs, tools like Optmyzr’s Shopping Campaign Builder and Shopping Campaign Refresher can automate much of the tedious account structure maintenance that ultimately contributes to the success of Performance Max.

A few final controls

Here are a few more ways that advertisers can still exert control over Performance Max campaigns:

Marketing objectives and goals

Make sure you’re feeding Google the best possible version of what your conversion really is. Set Conversion Value Rules to better represent your conversion values, or use offline conversion imports for even more precise data.

Campaign budgets

You can still allocate budgets to campaigns. Whether that means shifting budget from one Performance Max campaign to another, shifting budgets between Performance Max and a search or shopping campaign — or even shifting budgets between different platforms — there are many ways to ensure you get the most for your money with budget optimizations, many of which are easy to do in Optmyzr.

Geo-targeting

With automated bidding, you should be able to get conversions at the right price, even in locations that traditionally underperform. And while geo bid adjustments don’t work with Smart Bidding, you can still create different campaigns for different regions so that each can have better ROAS or CPA targets and creative assets that resonate more in each region.

Feeds

Feed optimization is a great example of managing PPC at a “big picture” level. Even in “old-school” shopping campaigns, there are no keywords. But the words you use to describe the products in a merchant feed will still impact what queries Google shows your ads for. So feed management is an important optimization technique, and Optmyzr has a beta for its clients who want help optimizing their feed-based data.

Audiences

The original form of targeting in PPC was through keywords, but audiences have continued to take on more importance for targeting. Specifying existing audiences helps Google target new audiences (those not on the list of existing audiences). Or adding audiences you find important to campaigns like Performance Max can help it deliver better results.

Account negatives

Performance Max campaigns respect negative keywords so long as you’re able to input them into the system. So ask an account rep’s help to upload negative keywords at the campaign level. And use tools like Optmyzr to set account-level negative placements that can help save thousands of dollars in wasted spend on apps and sites that bait users into clicking on ads and have a low probability of driving good conversions.

Conclusion

The introduction of Performance Max has changed how PPC advertisers manage the campaigns that drive conversions for their companies and clients. And while a lot of the management has shifted to the periphery of the system, there are still many things (like we shared here) that advertisers can do to continue to prove their value in the digital marketing space. If you’d like to test out some of Optmyzr’s capabilities and opt in to some of our more exciting betas, start a free trial or get in touch with our support team by writing to [email protected]


About The Author

How to get better leads and conversions with Googles AI

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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