Paid advertising is the bandwagon that everyone is jumping on in the 21st century. And there’s a very good reason for that; it works. In fact, it works so well that almost 50% of all clicks go to the top three paid advertising positions. So any business that isn’t making use of paid ad campaigns in 2021 is seriously lacking in its digital marketing strategy.
And it’s not like there’s any shortage of paid advertising sites. From Google Ads to Facebook Ads, there’s a paid ads platform around every corner. The challenge is choosing the right one for your business and knowing how it does what it does. The key to overcoming this challenge is understanding the role of artificial intelligence in paid advertising.
This is especially true in 2021 as AI is revolutionizing programmatic advertising radically. Advertisers and publishers now have access to advanced artificial intelligence that allows them to personalize user experience. As a result, modern users expect ad campaigns to be specifically designed for them.
Let’s take a look at how businesses can use AI to get the most out of their paid advertising efforts.
Recapping Role of AI in Digital Marketing
Before we dive into the world of programmatic advertising, it’s helpful to recap the role of AI in digital marketing. Essentially, businesses use artificial intelligence for two main purposes. The first is automation and the second is insights. Through advanced learning capabilities, AI and machine learning models can learn to automate repetitive tasks.
This helps marketers save time and money by diverting attention to more pressing matters. All the while, AI executes automations flawlessly while collecting data. This data is then analyzed by using predictive analytics and AI offers insights into how strategy can be improved. This two-prong aspect of AI is quite similar in programmatic advertising, as we discuss below.
Using AI in Paid Advertising in 2021
2021 will bring a lot of change in the paid advertising side of the industry. Particularly, the enhanced role of artificial intelligence in automating processes and analyzing data will be essential. Trends such as contextual targeting and accurate measurement will be on the rise in 2021
Check out this piece on the Dynamic Impact of AI on Ad Tech Evolution
In particular, advertisers and publishers will be looking to improve efficiency in bidding and managing ads through the use of AI. In addition, users also expect more sophisticated and personalized paid advertising experience in 2021. With the help of machine learning models, advertisers will be able to dissect individual user preferences with greater accuracy.
Now let’s take a closer look at the automation and insights aspect of AI in paid advertising.
AI Automation Aspect in Paid Advertising
Let’s take a look at the automation factors first. The main aim of automating processes is to save time and ensure faultless execution. This is also the case in paid advertising. Advertisers set triggers for machine learning models such as Robotic Process Automation (RPA) and Intelligent Process Automation (IPA). These technologies not only automate but also collect insights for agencies.
1. Automation in Bidding Process
One of the most frequent and essential processes in paid advertising is real time bidding or RTB. This is the process by which ad agencies make a bid for an ad space present on the publisher’s website.
This bidding process is carried out through Demand Side Platforms (DSPs). For an advertiser to be successful, they have to win RTBs and put up creative ads on ad spaces.
The real challenge in RTB is to adjust the bidding price so as to acquire relevant ad space. However, agencies have to take care not to incur additional costs. That’s where artificial intelligence comes into play.
With AI systems, advertisers can set up automated bidding strategies. These strategies keep agency budgets in check while maximizing bidding opportunities.
2. Creation of Dynamic Paid Advertisements
The creation of dynamic paid ads is one of the miracles of modern AI. As we mentioned earlier, users expect and look forward to customized online experiences. AI allows this customization through the creation of dynamic advertisements.
Dynamic ads are those ads that adapt to the preferences of the user. This maximizes the conversion rate of paid ads since each user is served up a personalized version. As the machine learning model collects more data, it is able to adjust ad creative in real time. Both Google and Facebook Ads offer this dynamic ad creative capability. The AI in these platforms collects data regarding online user activity. Subsequent ads are then based on the information collected for each individual user.
Thus, dynamic ads use the most relevant imagery, content and graphics for each user. This ensures greater conversions and goal completions for the business, whether that is website visits or sales.
3. Automated Fail-safes in Paid Advertising Campaigns
One of the easiest ways to lose money is by bidding on poorly performing keywords and ads. That’s why advertisers set up automations to restrict bidding on campaigns that lose money. The effectiveness of the AI in this case, depends on the accuracy of the trigger.
For instance, some of the common triggers in automated fail-safes are costs per conversion and click-through rates. An agency can set a trigger that if a particular ad has less than 1% CTR per 1,000 impressions, then AI should pause that ad. Similarly, if a keyword has a high cost per conversion, then ads running on that keyword can be automatically paused.
4. Creative Fit Selection by Machine Learning Models
Finally, advertisers use artificial intelligence to select the right creative for the right target audience. Thanks to techniques such as cohort analysis, ML models bunch users into groups with similar characteristics. This makes it easier for systems to present ads with a higher click probability to a set of users. This creative fit selection by ML models minimizes costs for advertisers while maximizing conversions.
AI Insights Aspect for Paid Advertising
All the data in the world can’t help you if you don’t know how to drive insights from it. This statement holds true for all spheres of digital marketing, including paid advertising. In 2021, advertisers are more likely to use AI to drive insights regarding their audience target and ad performance. Let’s take a closer look at what some of these insights entail.
1. Enhanced Audience Targeting for Paid Advertising
The success of any paid advertising campaign depends on how relevant it is to the target audience. And the selection of an appropriate target audience is more important than ever before. Thanks to artificial intelligence, advertisers can now rely on insights from user data to target audiences. This data comprises everything from user generated content to similar interests, keywords and affiliates.
For instance, you have an e-commerce website and run ads on product X. AI will analyze traffic on this ad and identify characteristics of users landing on this webpage through the ad. It will then offer insights into similar products that the user will be interested in, like Product Y. This generates a relevant audience for Product Y without extensive research by the advertiser.
2. Improved Budget Allocation
As a natural extension to enhanced audience targeting, AI insights also improves budget allocation for ads. It’s a known fact that some ad campaigns bring in more revenue than others. That’s why it is essential to allocate advertising budget accordingly. You don’t want to waste money on campaigns that barely convert. And deciding which ones to spend money on isn’t easy.
These decisions have to be based on data-driven marketing trends. Modern AI systems break down campaigns into hundreds of micro-campaigns to increase budget allocation efficiency. Basing decisions on such micro-campaigns can improve media buying strategy.
3. Better Metrics for Paid Advertising Measurement
Finally, artificial intelligence allows better measurement of ad campaigns and ad sets. In addition to automating ad campaign performance, Machine Learning models also recommend KPIs for measuring performance. This provides dual benefits to advertisers.
Firstly, they save time that would have been spent tracking KPIs to measure. Secondly, ML models recommend future adjustments based on performance measured for each KPI. Thus, the overall decision making process in paid advertising improves thanks to AI systems. As a result, advertisers can measure performance more accurately.
Using artificial intelligence in paid advertising is a necessity today, especially if a business wants to gain a competitive advantage. Although the cost of acquiring an artificial intelligence system may be high initially, the return you’ll gain over time with smarter decision making and automated adjustments will compensate for it.
Contact Lucrative.ai today to get started with integrating AI in your paid advertising today.