MARKETING
Facebook campaign budget optimization: How marketers must prepare for September 1, 2019
If you are using Facebook’s Ads Manager, campaign budget optimization (CBO) will become mandatory for all ad campaigns as of September 1, 2019.
If you are using an API tool like AdRules, you have until September 2020 before it is mandatory.
If you do any advertising on Facebook, you will be affected by this change. It will apply to both new and existing ad campaigns.
If you don’t want a rude awakening on September 1 when CBO activates in Ads Manager and your Facebook campaigns start to behave very differently, you need to start testing campaign budget optimization now.
While nobody likes mandatory, sudden changes, this is not all doom and gloom. There are some considerable upsides to CBO. You will have to give up some control over your campaigns after September first, but with CBO:
1. You’ll have less to manage
If you spend hours adjusting bids every week, or if you pay someone else to adjust bids every week, much of that bid optimization work will be over.
When campaign budget optimization is activated in Ads Manager, Facebook automatically shifts the ad budget to whichever ad set in a campaign is most effective. You get to control the definition of what “effective” means by specifying a goal for each campaign. Goals that are fairly late in your sales funnel, like a purchase or a download, tend to work best with CBO.
Because all that bid management work will be done by the Facebook algorithm, you may be able to hire less expensive people to manage your campaigns or have your team members work on more networks or accounts. Or, if you’ve been doing those bid edits yourself, you may find you suddenly have extra hours free every week. We recommend using those free hours to develop better creative, to study your competitors’ creative, or to set up a more efficient creative testing machine.
2. You’ll get a better return on ad spend (ROAS)
While there were some early reports of CBO not working as well as human-managed campaigns, the algorithm has gotten considerably smarter than when it first launched.
We’ve found that if a campaign is set up properly and the bids are high enough, CBO generally can get better results than a human can get.
CBO will also reduce how often your campaigns are put into “learning mode”. That means you won’t get penalized when Facebook’s algorithm reassesses your campaigns.
But you do need to give campaign budget optimization time to work. The algorithm needs about 50 conversions per ad set, per week, before it accrues enough data to ramp up your campaigns. And speaking of ramping up campaigns if you want to scale your campaigns, CBO is extremely effective. Especially if you keep feeding it new, high-quality audiences.
3. You will still be able to control spending (to an extent) with ad set spending limits
If you set a minimum spend for an ad set, Facebook will dutifully spend at least that amount. And if you set a maximum ad set spending limit, Facebook will not go over that limit.
This is a way to set a “governor” of sorts on your spending. It will force Facebook to run ad sets perhaps longer than it might otherwise have, but if you’re not quite ready to relinquish control, ad set spending limits are a way to ease into this new campaign management approach.
Those of you who also advertise with Google’s App Campaigns may have an edge already. Facebook is in some ways following Google’s lead by requiring advertisers to shift over to automated budget optimization.
You could, potentially, get around CBO by creating dozens or even hundreds of campaigns, each with on single ad set. But that would be working against the algorithm. And besides, CBO works well. There aren’t many good reasons to try to circumvent it. Especially when you use it along with other Facebook best practices and Facebook’s simplified campaign structure recommendation.
Start testing campaign budget optimization now
The benefits of CBO are proven, but you need to start testing now to see how to make it work well for your accounts. We still have a couple of months until the change in Ads Manager, but you may need to run multiple week-long tests to get the hang of this new budgeting strategy.
You may also need to shift how you’ve been defining goals. Using CBO for clicks is a waste of potential. Instead, look towards the end of the buyers’ journey. We like to optimize not just for app installs, but for specific app events like purchases. And not for just two-dollar purchases, we target people who are likely to spend $20 or more.
As you begin to test and measure CBO, don’t get too attached to the results of individual ad sets. Look at the campaign level, as this graphic illustrates:
Also, get ready to bump up your creatives. For CBO to work, it often needs several creative assets for each ad set. Including a few videos and elements for dynamic creatives helps too.
Pay close attention to your audiences, too. Many advertisers have found that CBO works best for them if they create separate campaigns for different audiences like one campaign for cold audiences and another campaign for a “warm” audience, like a retargeting audience.
Get ready for things like “The Breakdown Effect” to make your reporting look a little strange at first. “The Breakdown Effect” occurs when discount pacing (how frequently your ads show) intersects with discount bidding and makes it look like the system is overcharging you for conversions. What’s actually happening is the system is trying to find the most affordable conversions first, then it tries to find more expensive conversions.
If you do a lot of testing, this breakdown effect pattern may be familiar. It’s similar to how one cell of a test can look like a winner at first but as the data accrue, that early winner falls away and another cell is shown to perform better in the long-term.
Closing thoughts
Facebook is evolving. Everyone knows this, but the CBO change in September for Ads Manager is yet one more example of it happening again. And because Facebook’s advertising platform is evolving, advertisers have to evolve with it, too. If you’re still doing Facebook advertising like you were a year ago, you’re losing money and missing out on better ROAS.
Brian Bowman is the CEO of ConsumerAcquisition.com.
MARKETING
YouTube Ad Specs, Sizes, and Examples [2024 Update]
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!
MARKETING
Why We Are Always ‘Clicking to Buy’, According to Psychologists
Amazon pillows.
MARKETING
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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