MARKETING
4 Ways You’re Not Utilising AI Properly In Your PPC Campaigns
![4 Ways You’re Not Utilising AI Properly In Your PPC Campaigns 4 ways youre not utilising ai properly in your ppc campaigns](https://articles.entireweb.com/wp-content/uploads/2020/01/4-ways-youre-not-utilising-ai-properly-in-your-ppc-campaigns.jpg)
By now you might have seen a thousand articles telling you why you need to use AI (Artificial Intelligence) for PPC.
I should know. I’ve written a good few of these articles myself, preaching the benefits for businesses of all sizes. If you’re unfamiliar with them, let me remind you that AI is:
- Fast, able to save you time and give you more hours to get your work done.
- Smart, able to process a lot of data and interpret the results before you’ve even got them loaded.
- Able to work 24/7, giving you around the clock monitoring of your campaigns.
This is all well and good, but just using AI isn’t the end goal. There’s a difference between simply using something and doing it correctly.
![4 Ways You’re Not Utilising AI Properly In Your PPC Campaigns Cartoon man using a colander wrong](https://ppchero-wpengine.netdna-ssl.com/wp-content/uploads/2020/01/Doing-it-wrong.jpg)
It’s like convincing someone to finally use Facebook for their plumbing business, but all they post about is what meal they’re having for dinner each day. I’ll be surprised if that’s able to bring the business in.
Get the picture?
So while using AI is essential for PPC, simply having it doesn’t mean you’re taking advantage of the best AI has to offer. And this is a damn shame. If you’re putting the time and investment into AI, you need to make sure that you’re finding the right solutions for your company.
To help, we’ve outlined 4 common ways you might not be utilizing AI properly – and how to change it.
1. Not using AI in the right areas
The first thing we need to cover what part of your campaigns you’re actually using AI for. This one is difficult because there’s no straightforward and easy answer. It all depends on your business.
Take a look at your current management process. Find out where most of your time is being wasted and then find the AI tools that solve this problem for you.
For example, if most of your time is spent on interpreting data, you need a way to do this faster. If it’s copy and pasting data into reports, you need an automatic reporting tool. If it’s adjusting budgets, you need an automated rule to do this.
Now, be prepared that although advertising platforms like Google will have internal AI tools, it’s not your only option.
In fact, I’ve argued before that AI for PPC is only useful if you use external tools. It was a bold claim but backed up by the fact external tools are just smarter, faster and ahead of the game.
You’ve just got to find the right AI that actually works for your company.
2. Using inefficient PPC scripts
Before I get started on this one, rest assured I’m not about to mindlessly insult PPC scripts. I’m very much in favor of them. When they work, they’re a brilliant way to save time and give you hands-free management.
Ah, hands-free campaign management. That’s the sweet stuff I like to hear.
PPC scripts are pieces of code you can copy into your account to automatically run certain jobs for you, like being able to change your bidding depending on the weather in a particular area.
That’s a game-changer for those whose business relies on the weather, like an outdoor crazy golf course or ice-cream parlor.
![4 Ways You’re Not Utilising AI Properly In Your PPC Campaigns Ice cream google ad](https://ppchero-wpengine.netdna-ssl.com/wp-content/uploads/2020/01/Ice-cream-google-ad.jpg)
They’re also needed for when Google inevitably pushes out another update and your script no longer works. Yeah, it’s all fun and games in the PPC script world.
By all means, use PPC scripts as part of your AI solution. But make sure that they’re adapted to your company and aren’t wiped out by every tiny Google Ads update.
If you don’t have the on-team skills to edit the code, maybe you need to try tools that can do it all for you. Or, perhaps even consider using a PPC management agency who have the skills and resources to control it.
There’s no right choice for everyone. It’s all about figuring out yours.
3. You’re overcomplicating it
Data is the sweet nectar needed to correctly manage and optimize your campaigns. Without it, you may as well be trying to build a wall by throwing bricks in the dark.
But there is such a thing as too much data.
AI is amazing at gathering and interpreting data for you.
If you go into data overload, you’ll be hit with so many choices and options to consider that it can cripple you. Instead of using AI to easily solve one problem, you’ve made it so complicated that it creates 5 more.
As this article on keyword research pointed out, the sheer amount of data you can get from AI keyword generating tools can set you back. They can supply potentially billions of keywords – which are never going to be used.
You’ll be spoilt for choice and will have to dedicate more time deciding between things that weren’t even an option before.
If AI is making things more complicated then you need to cut back.
4. You’re too reliant on AI
With AI capabilities continually growing, there can be a temptation to just let it mindlessly run in the background. But you need to see the bigger picture. It’s no use mindlessly accepting every change that AI sends your way.
The curious part of you needs to ask why. Why do certain ads consistently perform better? What is it they do that the others don’t? Why do certain timeframes decrease your conversions?
As this article on Google Ads management pointed out:
“Google Ads management is all about being reactive: take onboard the changes and latest trends and adapt to them.”
In order to take onboard the changes, you need to understand why it happens. And no AI is going to do that for you.
![4 Ways You’re Not Utilising AI Properly In Your PPC Campaigns Rubix Cube PPC 1](https://ppchero-wpengine.netdna-ssl.com/wp-content/uploads/2020/01/Rubix-Cube-PPC-1-690x460.jpg)
You can only make the best use of AI if you use it alongside your work, not to replace it.
Find the right AI solution for your business
If you want to make the best use of AI, you need to find the right tools for your processes.
Take a look at your current roadblocks and time-sinks. Find tools designed to help explicitly with this. Trial what works and see how much time it saves. Ensure it’s not creating more problems than it solves. Then use this time and data to better your strategies and campaigns. Don’t just rely on AI to fix everything for you.
The bottom line? AI and humans have to work together. Finding this balance is the key to your success.
MARKETING
YouTube Ad Specs, Sizes, and Examples [2024 Update]
![YouTube Ad Specs, Sizes, and Examples [2024 Update] YouTube Ad Specs, Sizes, and Examples](https://articles.entireweb.com/wp-content/uploads/2024/06/YouTube-Ad-Specs-Sizes-and-Examples.jpg)
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
![Why We Are Always 'Clicking to Buy', According to Psychologists Why We Are Always 'Clicking to Buy', According to Psychologists](https://articles.entireweb.com/wp-content/uploads/2024/05/Why-We-Are-Always-Clicking-to-Buy-According-to-Psychologists.pngkeepProtocol.png)
Amazon pillows.
MARKETING
A deeper dive into data, personalization and Copilots
![A deeper dive into data, personalization and Copilots A deeper dive into data, personalization and Copilots](https://articles.entireweb.com/wp-content/uploads/2024/05/A-deeper-dive-into-data-personalization-and-Copilots.jpg)
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.”
-
SEARCHENGINES5 days ago
Daily Search Forum Recap: August 14, 2024
-
SEO7 days ago
Google’s AI Overviews Ditch Reddit, Embrace YouTube
-
SEARCHENGINES6 days ago
Daily Search Forum Recap: August 13, 2024
-
AFFILIATE MARKETING5 days ago
Musk, Trump Hit With Federal Labor Charges Over Livestream
-
SEARCHENGINES2 days ago
Google August Core Update, Big Ranking Bug, DOJ Google Breakup, AI Overview Links, Gemini Research & More
-
SEO4 days ago
The Long-Term Strategy of Building A Personal Brand Through Content And Value With Eric Enge
-
SEO6 days ago
ChatGPT Study Finds Training Data Doesn’t Match Real-World Use
-
SEARCHENGINES4 days ago
Daily Search Forum Recap: August 15, 2024