Itâ€™s a looming fear in various industries that artificial intelligence will one day take over jobs, making human input obsolete. Itâ€™s true that search advertising is one area where AI and automation have had the biggest impact. So many PPC tasks that werenâ€™t automated 10 years ago are now run by AI.
But that doesnâ€™t mean that artificial intelligence is on the way to replacing human PPC teams. People will always be necessary for paid search success, no matter how much is automated.
How Artificial Intelligence Improves PPC in 2019
There are lots of ways that artificial intelligence can help improve PPC. Many capabilities expand beyond what normal people can accomplish, even if a whole team of data scientists work on a paid search account. Here are a few examples of the ways AI can outperform human PPC managers today:
Addressing Data Scarcity
Most advertisers donâ€™t realize how much they rely on historical data to make bidding decisions. Add a new keyword to your campaign that doesnâ€™t have a lot of search volume, and you have no idea how much to bid. A single low search volume keyword might not seem particularly important, but these keywords as a whole can make up a significant portion of your campaign targeting. With artificial intelligence, thereâ€™s no need to ignore low search volume keywords or simply guess at their value.
Thatâ€™s because bidding technology can harness artificial intelligence to infer the value of data scarce keywords. QuanticMind, for example, uses Natural Language Processing (NLP) to identify semantically similar keywords that have sufficient data. It can then estimate the value of long-tail keywords and bid accordingly.
The same technology can be used to improve location targeting, audience targeting, or other dimensions. Say an advertiser wants to target specific counties within a region, but only some of them have sufficient data to assign value for bid adjustments. Advanced bidding technologies can utilize audience demographics to supplement data from similar audiences in different locations around the country.
Artificial intelligence that you see in PPC technology today relies heavily on statistical analysis to make decisions. Machine learning technology can look at past performance and the current competitive landscape to make accurate predictions of how ads will perform. This includes considerations of numerous dimensions like device, audiences, time of day, or location. Advertisers can then use these insights to make targeted decisions to improve targeting, bids, and ads.
Googleâ€™s Quality Score metric is a good example of this in action. It considers historical click data to estimate the quality of your ads, keywords, and landing pages. Quality Score can offer insights into how to improve your ads, and impacts ad rank in search results.
Forecasting technology is another valuable way advertisers can use AI for strategy optimization. In the past, advertisers needed to create their own statistical projections of potential performance. Now Google Ads and many third-party bid optimization tools can do this for you, using current bid landscape data.
Automated Ad Creation
Artificial intelligence helps with more than just targeting, but also ad creation. Google Ads regularly introduces new ways to automate the development and optimization of ad copy creation. A great example of this is responsive search ads. These use the power of machine learning to help advertisers deliver the best ad for a search query.
Responsive search ads allow you to create different combinations of headlines and descriptions, then automatically test them to see which are most effective:
This helps advertisers save time creating and optimizing the best ad copy, and allows Google to show the most relevant combinations for customers.
Improving Spend Efficiency
Advertisers today have potentially thousands of bidding decisions to make, even with small paid search accounts. There are keywords to bid on, as well as audiences and dimensions to target with bid adjustments. Even if PPC managers could analyze all the relevant data, calculate cost per click (CPC) and bid accordingly, the competitive landscape is constantly changing. Any optimizations made will quickly become out of date.
Thatâ€™s why AI is so valuable for improving spend efficiency. Automated bidding technology can analyze relevant bid landscape data in real-time, then make quick changes to optimize bids. This ensures you only spend what you need on each keyword to reach target marketing goals.
Why Humans are Still 100% Necessary for Paid Search Success
Itâ€™s true that artificial intelligence is changing the way paid search advertising works. Automation has taken over many time-consuming tasks, and can optimize campaign elements with more speed and precision than a human could. But that doesnâ€™t mean AI is on the path to replacing human PPC teams.
People still have an important role to play in paid search management. This includes tasks that AI will never be equipped to take on, no matter how advanced it gets. Here are a few reasons humans will always be necessary for paid search success:
Creating a Strong Marketing Message
Artificial intelligence can help a lot with ad creation, especially when it comes to testing. While AI can determine the best possible ad copy, it canâ€™t infer why an ad is effective with your target audience. Thatâ€™s one major reason why advertising will always need people, no matter how advanced AI gets. Once you understand why a certain headline or description works so well with your audience, you can replicate that message across ads and campaigns.
Humans are still the creatives. AI can test ads and ad components, but itâ€™s people who need to come up with the most relevant ideas in the first place. No matter how intelligent a machine is, it canâ€™t understand how or why an ad is effective. For example, one ad description could have a much better clickthrough rate than others not because the wording is better, but because it promotes a better deal. An advertising manager could evaluate an ad and infer this, while AI and machine learning never could.
Itâ€™s a common misconception that AI and automation are designed to run your campaigns for you. Google Smart Campaigns are designed so inexperienced businesses can take advantage of Google Ads features without the knowledge of professional advertisers. But that doesnâ€™t mean competitive advertisers should simply â€śset-and-forgetâ€ť their campaigns.
If you want to stay ahead in a competitive market, making regular campaign adjustments is a necessity. Automating various processes just makes this a whole lot easier by freeing up your time to work on optimization and exploring new opportunities for growth.
Say, in the future, 100% of PPC advertising was automated. All people needed to do was select their goals, set a budget, launch their campaigns, then walk away. Since everyone is using the same technologies and strategies for optimization, thereâ€™d be no way to truly beat out the competition. Other than raising your budget, the only way you could stand out in a competitive market is by making manual changes to take advantage of different opportunities. This potential will always be there, no matter how much of your campaign is already automated.
Prioritizing the Right Business Goals
AI-powered bid optimization technologies are designed to help businesses work towards their most important marketing goals. Googleâ€™s Smart Bidding, for example, uses algorithms that optimize for different strategies, including:
- Target CPA (cost-per-acquisition)
- Target ROAS
- Maximize Conversions
- Enhanced cost-per-click (ECPC)
Selecting the right automated goal is valuable, but it isnâ€™t nuanced enough for most business objectives. Most companies want to target ROAS, but they may also care a lot about maximizing conversions, for example. How are they supposed to reconcile these needs with 100% automation?
Thatâ€™s why human input is always necessary. You can use automated bidding to save time optimizing towards a main marketing goal. Then you can make manual keyword and bid adjustments to also prioritize secondary and tertiary goals.
Diagnosing Performance Issues
Another major application of AI is to anomaly detection. Automation tools can predict future performance based on historical data. If actual performance ends up deviating from expectations, then itâ€™s possible to automatically pause campaigns to address the issue. This can be done using Google Ads scripts or another bid automation technology.
Itâ€™s a very valuable feature because it can prevent wasted spending on ads when a data or performance issue could be causing problems in an account. But detecting anomalies is one thing, diagnosing them is another. A PPC manager still needs to go in and figure out whatâ€™s behind the performance issue and fix it. It could be something as simple as using the wrong campaign setting or targeting the wrong dimension. But AI doesnâ€™t have the ability to reason and infer why performance might deviate from expectations. That will always need human intervention.
The Bottom Line
These cases are just a few of the many reasons humans will always be necessary for PPC. Even as artificial intelligence becomes more advanced and takes on new optimization tasks, it will always require people to manage it. AI is nothing more than an opportunity to streamline and optimize tasks that PPC managers have always been in charge of. Improving campaign accuracy with AI can free up more budget as well. This gives PPC managers more money and time to pursue new growth initiatives.
With this in mind, forward-thinking search advertisers can embrace what AI, machine learning, and automation have to offer for PPC. They also have peace of mind knowing the technology can never replace their critical role in the advertising business.