AI has changed every online industry and ads have been one of the most impacted things. With how good AI is at writing, creating images, and optimizing things based on data, it's no wonder that every company is trying to implement it at least to some extent.
One of the biggest things that Artificial intelligence is getting better at is predicting trends, behaviors, and preferences. This power makes AI a priority for most online advertisers, and big players like Google, Meta, and others are investing heavily in it.
Now that you know this is a thing, it's time to learn how major advertising platforms integrate AI and how you can use it to improve your campaigns!
Understanding AI Predictive Targeting
AI predictive targeting uses machine learning algorithms to analyze user data and predict future behaviors and preferences of users. This includes things like purchasing decisions, interests, and content engagement. By finding these patterns and identifying them, it enables advertisers to:
- Segment Audiences Properly
You can group users based on predicted behaviors and preferences, giving you groups that you can use certain ads to target more effectively.
- Personalize Ads
The more personalized the ad, the more likely someone will engage with it. With AI you can tailor ads to individual interests and make them way more effective.
- Optimize Spend
Budgeting and ad spend can be simplified by adjusting bids and budgets in real time so that you dont overspend but retain the ideal spending for any campaign.
Predictive Targeting in Google Ads
Google has already made a name for themselves through AI bots like Gemini and their internal algorithms for content ranking and search. They also use AI to improve Google Ads!
- Automated Bidding
Google ads allow users to use AI to automate and adjust bidding strategies in real time. This can help drive traffic to profitable campaigns and limit spending on bad performing ones. It uses historical data on performance, real-time data, and prediction to make sure that there is an optimal bid for every situation.
- Audience Expansion
If you run on Google Ads, then you have likely seen the option for “Similar Audiences”. This feature expands your targeting and helps you reach users that might be outside of your usual interest group. In most cases, this feature targets people that are likely to convert and engage with your ads, improving your conversion rates! - Dynamic Search Ads
AI enables dynamic search ads as well. This means that Google will try to automatically generate engaging ad headlines, and adjust Landing pages based on the content you are advertising and how your audience is reacting to it. This helps keep your ads relevant to search queries without you having to make keywords lists and optimize every detail.
Predictive Targeting in Meta Ads
Meta probably has the biggest advertising audience through the mix of its platforms (Facebook, Instagram, WhatsApp, and more). Their AI models have also improved significantly in the last year, and some users are seeing better performance when using their AI features than when doing things manually.
- Meta Lattice
Lattice is an AI-driven ad delivery system that Meta has shown a few years ago. It works behind the scenes and utilizes multiple data points to predict user responses to ads. It analyzes data like user interaction across Meta’s platforms, as well as on external sites through various tracking methods and creates a unique profile on users that helps the algorithm better target users.
Since this is all behind the scenes, you as an advertiser, can just sit back and relax while their machine learning algorithm does the rest!
- Advantage+ Campaigns
In the last few months, Meta has started heavily pushing for their Advantage+ Campaigns. Users across the board have reported that the results from these campaigns usually start a bit worse, but once the algorithm learns enough about your audience, campaign performance exceeds expectations!
- Lookalike Audiences
Similar to Google, Meta also utilizes AI tech to find the ideal audience for your campaigns. With their lookalike feature, the algorithm will analyze your current audience and find people with similar interests all over the world.
Predictive Targeting in Native Advertising
Native ads are not tied to just one platform, so some features might be available on some and not on others, but the general improvements and AI implementations stay the same for the most part.
- Contextual Targeting
AI can analyze the context of web pages and place ads that align best with the content at hand. This can lead to a better experience for the user and higher engagement rates. With this, ads are more relevant to user intent and interest and rely less on personal data.
- Programmatic Advertising
This might sound like a difficult term to understand, but it all boils down to AI being able to buy ad placements in real time depending on what it determines is the best one in the current situation. This allows you to optimize ad spend and improve overall performance.
- Predictive Content Recommendation
AI roughly knows what content users are likely to engage with, and with this feature, it tries to personalize content recommendation to the audience based on what it thinks will work the best on them. It improves effectiveness and user interaction of ads in general.
What Are The Best Practices?
AI Integration on most things is still not 100% reliable and sometimes needs you to monitor things to make sure it's working as intended. There are some practices that you can implement to make the chances of things going smoothly better, and here are some of the ones you should know about!
- Use Platform Tools: Pretty much every platform utilizes some sort of AI tools. You should check them out and use them, even if they dont work as great as you might expect, some platforms give some algorithm bonuses for users that utilize them, and though this makes your ads and marketing efforts a bit better. You will also help train and adapt the AI to your use case, which is always a good idea.
- Focus on High-Quality Data: The better quality data you collect on various stats, the more you can extract from that data. Make sure your trackers are properly set up and keep track of KPIs that influence your results the most.
- Test and Optimize: Monitor your campaigns and do various tests with AI, without, with some of your custom settings, and without. Treat is as an advanced AB testing. This should help you identify if the AI features are helpful to you and if they are, what influences them the most.
- Stay Updated on Developments: Everything is changing rapidly, and staying on the edge of developments can be a great asset if you know how to use it properly. You also never know when the next feature will be the one to take your ads to the next level!
Conclusion
AI is everywhere, and there is no point ignoring it. With how advanced it has become in the last year, and with developments in things like predictive targeting, not using it can be a huge disadvantage.
With predictive targeting, your ads can be more personalized and campaigns can be more efficient at reaching the right audience and improving user engagement and conversion rates. As the tech continues to develop even further, it will likely be a requirement to run most campaigns successfully at all!
Have you used AI for your campaigns? What was your experience with it so far? Share it with us in the comments below!
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