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How AI is Learning to Dominate Paid Ads

Sam Bocetta
Sam Bocetta
Security Consultant at Bocetta Consulting

AI algorithms are changing the marketing game by delivering higher quality information faster than any human ever could. Advertisers who haven't adopted AI into their work flow yet better start.

Paid ads have been a staple of online advertising for more than a decade. Over that time, advertisers have learned how to design and target them even more effectively. Now, though, that is changing.

Artificial intelligence is transforming the way that paid ads are delivered, giving advertisers more control than ever before as to when and where they are delivered to target audiences. Though these abilities are new, advertisers need to become familiar with them and fast. Advertisers who do not take advantage of these new abilities to leverage customer insights risk being left behind, and their ad campaigns are going to lose ground to more advanced competitors. 

This is already occurring but is going to shortly become apparent to everyone in the ad world. In the near future, AI is sure to dominate the delivery (and perhaps, eventually, even the design) of paid ads, but they are only able to do this with a skilled and experienced human controller. As a result, rather than seeing AI tools as competitors, advertisers must learn to work collaboratively with them

In this article, we'll look at the reasons why advertisers need to be aware of how AI is learning to dominate paid ads, how AI tools are doing this and how this impacts online advertising in the future.

Why advertisers need to know about AI

There are several reasons why advertisers need to care about the rise of AI tools in paid ad marketing. At the broadest level, it should be recognized that the 'traditional' model of paid ads, in which an advertiser specified a set of broad criteria for when and where these should be deployed, is dead. The agility and power of AI-driven paid ad campaigns far outstrips the ability of even the most experienced human advertiser, and any agency or company that is not taking advantage of these tools is likely to be left behind.

You should not, however, see these tools as a replacement for advertising professionals. As we've pointed out in our article on the impact of AI in customer service, in many cases, utilizing these tools allows you to free up time that you would otherwise spend responding to everyday customer queries and other basic tasks.

Beyond this pragmatic concern, there are a few key ways in which AI tools can make your paid ad campaigns more effective and more cost-efficient. With more detailed analysis of your target markets, and the ability to deliver paid ads directly to them, you can leverage your paid ad spend and get better results for the same investment.

It might even be, in fact, that using AI in your paid ad campaigns is going to lower your marketing spend. As AI targeting improves, a higher percentage of your ads reach the right audience at the right moment and in the right place. In the long run, this may mean that you can reduce the amount of paid ads you use.

Finally, by putting in place AI-driven tools today, you are preparing yourself for the future. As we see, the future landscape of paid ad campaigns is going to be driven by AI at its most basic level. Though these tools are already quite powerful when it comes to improving the efficacy of these campaigns, this is only likely to grow in the coming years. By familiarizing yourself with the technology now, you can ensure that your team is among the first to take advantage of any future developments.

How AI works in paid advertising

Paid ad campaigns rely on data for their efficacy. Instead of firing out millions of ads that are of little (or no) benefit to your target audiences, AI-driven paid ad campaigns can learn how to best speak to your customers and target paid ads where they are most effective.

If you are running a paid ad campaign, you are probably already using AI tools whether you realize it or not. Google AdWords, for instance, makes use of Google's proprietary AI system to gather data on website visitors and send ads to specific groups of consumers. As this technology develops, it is able to gather more and more information on individual users and to target ads even more specifically.

There are also plenty of widely used tools that already rely on AI systems. Most people don't realize, for instance, that Grammarly (an advanced text editor) uses AI to generate suggestions. Similarly, many of the best hosting services provide a set of AI-driven tools for analyzing traffic to your website and automating the delivery of ads to specific audiences. 

The value of AI technologies in all these processes is that they use existing data to make highly accurate (sometimes spookily accurate) predictions of future consumer behavior. Given enough data, AI tools can now estimate a user's income bracket, homeownership status and more. 

These tools are very valuable for advertisers, but they also have other uses: They have been implemented in order to enforce internet censorship in many countries, and are also being used to secure data systems against attack. For advertisers, though, their primary value is that AIs can target ads to specific audience groups. But it doesn't stop there: The more advanced AI marketing systems then look at the success of your paid advertising and automatically direct resources where they are most effective. 

The Three A's

In order to understand why AIs are having such a huge effect on paid ad campaigns, let's take a closer look at the way that these systems work. This can be best summarized by looking at three aspects of these systems: attribution, automation and audience.

Each of these builds on the last, so that improved attribution analysis can build into automated systems that are then able to target paid ads much more effectively.

1. Attribution

The great strength of AI is that it can quickly and effectively analyze huge data sets. One such data set is generated by paid ad attribution models. These are the models that are used to give credit to the click (or series of clicks) that brought a customer to your site. Google, for instance, uses a number of attribution models in order to provide this information.

If you've ever seen one of these reports, the need for AI tools is clear enough. The journey of a typical customer is often complex, involving several different keyword searches and multiple click-throughs. As a result, it's often difficult for individual marketers (or even data teams) to analyze how effective your paid ads are. AI tools can help with this process by quickly processing attribution data and providing you with valuable insights that improve the efficacy of your paid ad campaigns.

2. Automation

AIs can also be used to automate many of the tasks that marketers used to do by hand. Taking the attribution data I've described, for instance, AI tools can quickly build customer personas that are far more detailed than those that can be created by hand. AI tools can automate aspects of the marketing process beyond working with attribution data. They can also be used to automate the process of lead generation, and some of the most advanced tools can even discover and identify new targets based on their browsing history. 

Implementing this kind of automation can give your marketing campaigns a powerful boost, but it needs to be done in a sensitive and transparent way. Customers are increasingly concerned about how companies use their data, and are taking active measures to improve cybersecurity and avoid precisely this kind of automated prospect discovery. Presenting customers with ads that are "too personal" can freak them out if you don't explain where you got the data from. 

3. Audience

Perhaps the most powerful functionality that AI tools deliver in relation to paid ads, though, is their ability to automatically target specific audiences at specific times. There are plenty of examples of this. In fact, one of the earliest AI systems, which Amazon used to deliver recommendations to their customers, was a basic implementation of this idea. 

Today, the ability to target hyperspecific audiences at hyperspecific times has been transformed by AI. AI tools can be used, for example, to send paid ads to customers when they are close to a Starbucks, offering them a deal on their favorite drink. This kind of real-time targeting is essentially impossible for humans, and can ensure that paid ads are directed to target audiences at exactly the correct time and place.

Though this kind of geographically specific targeting is becoming quite common, the parallel rise in consumer use of VPN technologies has made delivering ads in this way more difficult than it used to be. Many customers are now using VPNs specifically to hide their location, whether to avoid geographical blocks on Netflix or as a cost-effective way to increase their own cybersecurity. 

In response, tools have been developed (which also rely on AI) to overcome the anonymity that VPNs afford. Making use of these tools can restore the ability to deliver highly targeted ads to your customers at critical times. 

The future of paid ad campaigns

In the future, paid ads are going to be more targeted, and more specific, than ever before. By utilizing the kind of AI tools we've described, advertisers can develop truly individualized personas for all of their potential customers and retarget each of them with ads at precisely the times that they are most likely to make a purchase. 

This is already apparent in some innovative paid ad campaigns, such as the one run by Starbucks. But the vast datasets that AIs allow advertisers to work with is going to extend their capabilities far beyond individual consumers. Another future area for development is the way that AI is accelerating B2B demand generation and outreach marketing strategies used by digital marketers.

This is already apparent in a number of recent marketing campaigns in the financial industry where mobile advertising platforms are leveraging consumer spending data to advertise on many popular stock trading apps, often unbeknownst to users. However, as the technology develops, it's likely that the same kind of detailed personas that can be built from consumer data are going to also be available for B2B clients. 

Finally, in the not-too-distant future, it may even be that AIs will be able to design content. There are already tools, like those described above, that track the engagement of specific consumer groups with specific types of paid ads and make suggestions as to which types of ads need to be improved. Going a step further, into a world in which AIs can develop hyperpersonalized ads designed to resonate with specific individuals, is likely to take a few years yet. 

But the implications of this advance is sure to be widespread and groundbreaking: Ultimately, it might be that AIs can produce paid ads that are specifically designed for individual consumers. It might be, in fact, that within a few years the ads that we see are just for us.

The bottom line

Paid ads are all about maximizing your marketing spend, and incorporating AI tools into your processes can have significant impacts on the process of developing a marketing budget. By ensuring that you are talking directly to your target audience and by continually assessing how effective your marketing content is, you can make sure that every dollar you spend on paid ads is going to come back to you in increased profits.

Image Credit: mangpor 2004 / Getty Images
Sam Bocetta
Sam Bocetta
business.com Member
See Sam Bocetta's Profile
Former defense contractor for the Navy. Security analyst and freelance correspondent for a number of media outlets. I find radical -- often heretical -- solutions to "impossible"? network security problems, and push early stage concepts from research to development. Program setup, people acquisition, deployment. Specialties: Naval engineering, Mechanical engineering, Marine Ops. Agile Management. InfoSec. Cryptography. Cyberwarfare & Cyberdefense. PRESENTLY: KRACK attack prevention, micropower systems defense. Writing my first book, democratizing personal privacy solutions for the broader public, due to publish in early 2021.