How AI Understands Content in Marketing & Advertising

AI Understands Content & Advertising

We might think about the future and immediately go to flying cars and sentient robots, but in some ways the “future” is upon us. AI is becoming sophisticated. It’s able to write and speak for us. 

By using natural language processing, AI has already entered into the content marketing and advertising space to make content more accessible and conversion friendly. Read on to learn how AI understands human language as well as the three key ways NLP can be used in marketing  including personalized content, AI-written content, and our favorite, contextual advertising.

How AI Understands Human Language (What is NLP)

Natural Language Processing is a field that has interested many people because of its potential applications in the future. While this technology is still relatively new, it has already impacted our lives. Natural language processing (NLP) can be defined as an area of computer science and artificial intelligence dedicated to understanding and analyzing human language written and spoken content, images, videos. The purpose for this in advertising and marketing is to then deliver personalized content.

This technology's impact on society started with simple things like spell checkers, but now spans across all forms of media including social media posts, online shopping, customer service chatbots, or e-commerce product descriptions. news articles, emails, etc. You may have seen NLP at work if you've ever used Siri on your iPhone or Google Assistant on your Android device.

NLP allows us to communicate more efficiently with each other by helping computers understand human speech much better than they ever could before. As a result, the system generates a high-quality content feed based on each user's preferences and interests. The more material the system amasses, the better the algorithms get at improving the user's experience with it.

How AI reading and analyzing content can be used

While new uses are being developed daily, AI has already been integrated into our daily content and advertising strategies. Learn the 3 useful ways AI understanding content can help you.

AI Personalized Content on Websites

Have you ever been on a website and been served up an article that was completely irrelevant to what you were trying to find? Or have you visited a site with content so generic it didn't seem personalized at all?

AI is being used more often these days because of its ability to process information quickly - without human intervention. It's able to collect data from various sources and create relevant articles based on user trends and interests. For example, if someone visits a travel site, they might be shown an article about their upcoming trip or one from another person who has been there before them. This type of personalization is important because people are more likely to engage with content that is tailored to them according to their interests.

 Companies like  Amazon use this technology frequently to suggest similar products to sell to you, or Buzzfeed uses it to suggest articles that fit the article you’re reading.

AI Writing/Content Improvements

How many times have you typed a text message to someone, and they responded with "I don't understand"? How about when looking up the definition of a word? If this has happened, then you've encountered AI. Predictive text on your phone is an example of how AI can help us communicate more efficiently. Intelligent software can also help us find definitions for words we're not sure what they mean. These technologies use algorithms that learn from past data and make predictions based on that information.  For example, if you type "Bank" into Google search, it will predict the next word as "Of America or Near Me". It's because these systems know common patterns such as people often type the word after "bank".

Business owners, marketing consultants, and authors may use AI writing assistants to write more material, from blogs to job descriptions. AI writing assistants employ machine learning, a branch of AI technology, to assist content creators with study, grammar, and sound in the creation process. Natural language processing (NLP) is used to analyze writings and make appropriate content suggestions. Companies like Persado and Jarvis are starting to capitalize this market to create AI-generated content, but also to curate better performing content through AI-informed A/B testing of your ad copy, email content and more.

Contextual Advertising

Contextual advertising has been around for a while. Think about street vendors who suddenly start selling umbrellas or push them to the front when it is raining. The world of advertising is constantly evolving. It's now not enough to just place an ad in front of a consumer and hope they notice it - marketers need to understand the content they're placing their ads around, as well as what those users are looking for at that particular time so that the right message can be sent out to the right people. These are called "contextual" ads because the ad placement takes into account both the content on the page as well as keywords related to what you searched for.

Since Google’s announcement that third-party cookies are going away, contextual advertising has been making a resurgence - and it makes sense. Behavioral advertising takes into account what a user HAS been reading and consuming, not what they’re interested in at the moment. 

How CatapultX is Taking Contextual Advertising to the Next Level

Contextual advertising has existed on the internet for a long time - it was the original format for digital advertising. Then, it morphed into native ads, which were contextual ads placed to integrate into the web content.

CatapultX is taking it a step further: contextual video advertising that integrates with video content. Our advanced AI analyzes not just what the website or copy around the embedded video, but also what is happening in the video itself moment-by-moment. So, if a garden-store advertiser wants to increase purchases, they can serve ads during moments in video that showcase gardens, salads being eaten or general greenery. All of this, and the ads are cookieless, non-interruptive and preferred by audiences 9:1.

What’s Next for AI & Content?

So, what does all of this mean for the future of content marketing? The answer is twofold. On one hand, it means that machine learning will soon be used to create all sorts of valuable content – from blog posts and videos to advertising copy and social media messages. But on the other hand, human interaction will become valuable as well! Marketers should concentrate on business intelligence and consumer behavior and create a marketing mix that balances AI and human interaction. It will be important for marketers to analyze where their users are and make a concentrated effort to be there. For example, by 2022 it is estimated that 82% of internet traffic will be to watch online video. Is your video marketing and advertising strategy up to par for the future?