Just like adtech (advertising tech) revolutionized digital marketing, artificial intelligence (AI) is now revolutionizing ad tech. Many digital marketers believe that AI is the next big thing when it comes to digital marketing. This is easy to believe since AI has made automating tasks for proper targeting and positioning of ads, extremely easy and highly effective.

AI is very effective at making ads both lucrative for advertisers and relevant to consumers. Many experts predict that AI will continue to grow significantly throughout the remainder of the decade. AI is being utilized to target ultra-specific niches in order to get the right ads in front of the largest number of highly targeted people.

AI has fully proven to be highly valuable in maximizing ad spend. With AI, advertisers are able to establish better quality leads than ever before. Adtech will continue evolving as AI technology continues to improve. This will create an ever-increasing number of adtech software development opportunities advertisers can take advantage of. We’ll take a deeper look at how artificial intelligence is changing adtech.

1. Consumer-focused advertising

Each consumer is relatively different when it comes to their online behavior. This means that the ads for each consumer should be unique too. However, before AI, it wasn’t possible to make content that’s customer-centric for each individual consumer. AI has made it possible for advertisers to create consumer-driven content, which makes ads perform better now, more than they ever have before. There’s an increase in consumer data and that makes it easy for AI to predict the ads that will perform best with different types of consumers.

2. Advanced audience targeting

Adtech has become more relevant with AI. The reason why ads are performing substantially better now than they were before, is because they’ve become more personalized. People get to see the ads that they are actually interested in. Several years ago, it was so hard to find the perfect audience to show an ad to. It was almost impossible. Now, the right audience is selected and targeted with AI-managed ad campaigns through the use of consumer data. Gigabytes of data are analyzed by artificial intelligence in a matter of seconds. It then is able to suggest an ideal audience for each ad campaign. It reduces the work that would have been done by humans in weeks. AI takes only a few minutes and the results are much better.

3. Sentiment analysis based on AI

One of the most recent adaptations of AI is sentiment analysis. Through the use of different techniques, such as computational linguistics and natural language processing (NLP), artificial intelligence can now judge what emotional state a consumer is in. Being able to understand consumer sentiment, allows AI to better understand the preferences and opinions of consumers. Consumer opinions are very important sources of consumer data. As a consumer, you’ll only see ads that are relevant to you. A business experiences an increase in ad clicks, conversions, and revenue through the use of sentiment analysis.

4. Network selection

When ads and keywords are strategically placed on relevant channels, they’re able to perform better and benefit advertisers. It’s easy for AI to do that quickly and efficiently. The ads that are getting more responses are analyzed by AI. The data is analyzed to determine which advertising platforms people are coming from, what webpage on the website they engage with the most, how long they remain on the website, and more. Using this information, companies are able to strategically place ads on networks and channels that are bringing more visitors that are more likely to purchase the product or services they sell.

5. The beginning of real-time bidding

Through using AI in marketing, real-time bidding (RTB) is able to save companies a lot of money every year. It’s a technique that uses real-time consumer data. Using AI, a business can place the lowest bid possible, to acquire ad space on a website, at a specific time range for a specific type of potential customer. These calculations and determinations are all done while a webpage is loading, to select which ad will be displayed and when. Bidding is now a mostly automated process and is no longer a problem for companies that want to save money and increase revenue using AI and real-time consumer data.

6. Using ML algorithms to position ads

Machine learning (ML) algorithms have made the process of positioning ads online much simpler than ever before. For example, it used to take ad developers several hours to figure out the correct bidding and positioning of Google ads. Through machine learning, the whole process is completed in seconds. User data is analyzed by ML algorithms to determine the best ad placement. Proper ad placement allows for the advertising network to maximize profits and the advertiser maximizes ad impressions and ad reaches among consumers most likely to be interested in what they have to offer.

7. Predictive analysis adaptation model

The process in which future user behavior is predicted is known as predictive analysis. The concept is what enables predictive advertising to succeed. Hence ads based on the consumer’s predicted future behavior are created. When companies know what consumers are going to search for in the future, it saves a lot of money on advertising while also increasing profits. This improved efficiency is a major reason why predictive analysis and artificial intelligence are leading the way in adtech now and will continue to do so in the many years to come.


Artificial intelligence is increasingly impacting advertising in a positive way, mainly due to the number of benefits it offers, as well as its ability to keep getting smarter as time goes by. 

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