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Paid Media 8 min read
Written by Natalie Yelton
Content Writer @ Galactic Fed
Expert reviewed by Dallin Porter
Communications Manager @ Galactic Fed
Published 10 Feb 2021
There’s no denying that AI enhances paid search advertising. The automation provided by Google, other search engines, and third-party providers has the potential to save you a lot of time and money when it comes to your paid search campaigns, ranging from bid management to predicting click-through rate (CTR.)
So can we all log off and let the robots take care of our digital marketing?
Humans are still needed to set the right goals and KPIs, along with many other vital tasks.
However, we can use AI to our advantage to dramatically improve the success of your paid search campaigns.
In this article, we provide a brief overview of what AI is in the context of paid search, examples of AI, and we explain how paid search and AI can work together to help you reach more customers and grow your business. Stick around!
Let’s take a look at the encyclopedia definition of artificial intelligence. Britannica explains that AI is:
‘the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings.
The term is frequently applied to the project of developing systems endowed with the intellectual processes characteristic of humans, such as the ability to reason, discover meaning, generalize, or learn from past experience.’
Using AI in the context of paid search means you can automate specific search engine marketing (SEM) tasks through tools supplied by third-parties or by Google Ads itself. We’ll dive deeper into what specific tasks you can automate to benefit your search ads later on in this post.
AI sounds impressive and all, but what exactly is in it for you when it comes to improving your paid search ads? Your search engine marketing can benefit in three ways, thanks to AI:
To understand how AI and machine learning can impact various stages of the buyer journey, take a look at this powerful illustration from Smart Insights:
AI and machine learning are closely linked. Machine learning is essentially a subset of artificial intelligence; it’s the algorithms used to learn without actually being programmed, as displayed in this infographic:
Source: Data Catch Up
Google explains it uses machine learning technology to help people get stuff done faster and easier than ever before.
How does Google use machine learning, you ask?
Boost the ROI of your digital marketing efforts with automation. Let’s take a closer look at specific tasks you can automate when running a per click search campaign on Google, in particular:
Enhanced bidding from Google Ads machine learning has the potential to make sure you get the most bang for your buck. Setting the correct bids for each keyword can be a massive job requiring constant adjustments. Your ideal cost-per-click (CPC) can change based on many factors, including business goals, competition, and demand. Managing bids manually just isn’t an option for larger accounts.
Google offers automated bidding for search; you can choose Smart Bidding for your campaign, and Google will automatically calculate bids for your business.
Google offers five automated bidding strategies. Which one your business should proceed with will depend on your unique business goals:
You’ll be able to analyze essential data in real-time, including time-of-day, operating system, language, device, and several other factors. Google then uses machine learning to set the right bids for your business to maximize your goals.
Google can predict the likelihood of click-throughs for your ads when shown for a particular keyword. This is irrespective of your ad’s position on the SERP, extensions, or any other ad formats that can potentially affect how visible your ad appears online.
Using how well your keywords performed in the past, Google can estimate an expected click-through rate (CTR.)
Google can finesse your expected CTR based on device type, search term, and other auction-time factors when it comes to auction time.
In addition, Google will provide you with one of three statuses: above average, average, or below average.
Getting an “average” or “above average” status means there are no significant issues with your keyword’s expected CTR compared to all other keywords.
You will want to consider changing your ad text to closely relate to your focus keywords if you get a “below average” status. Use the “below average” status to help your business identify keywords that aren’t relevant enough to perform well.
It’s important to note that your expected CTR is a prediction; thus, it’s different from your actual CTRs found in the CTR column of your Google Ads account.
We’re self-proclaimed data-nerds here at Galactic Fed, so we are big supporters of using historical data to enhance a PPC campaign and digital marketing more widely. We happen to do this daily for several clients.
So how does using historical data work in practice?
Google gives you the ability to use historical data to predict the likelihood of a conversion, meaning you’re able to fine-tune your ad copy and make it much more likely to entice your target audience to click.
Ultimately, AI can help you make better decisions when it comes to your business’s digital marketing spend.
From smarter bid management to predicting your target keywords’ click-through rates, Google’s machine learning can make your paid search ads more powerful. Artificial intelligence can help you reach customers that are more likely to purchase your product or service, sign up for your subscription, or request a demo of your software. This improves your ads’ performance, reduces ad spend wastage, and saves time in the process.
Use historical data to your advantage and drive traffic to your website as a result of PPC ads that are relevant and resonate with your target audience. If you want help using AI to enhance your PPC campaigns, send us a message. We would love to assist!
Content Writer @ Galactic Fed
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