5 AI Marketing Case Studies

Artificial intelligence has come a long way, and many things that were once considered science fiction are now a reality. The world has been trying to become more digitized for years, but it has only been in the last few years that we have grasped the boundless benefits of everything AI has to offer.

Here are five examples of AI marketing.

Learning from the Ground Up

Benefits of Content and Search Recommendations

Marketing Automation and Ad Targeting


Pricing that changes as time goes on

Deep Learning

Humans are limited in their abilities; for example, we cannot manage and operate every aspect of a business on our own. Even having a team of people dedicated to a specific task can be stressful. Apart from a variety of responsibilities that may be mentioned, a computerized method of conducting marketing procedures is required.

Deep learning is an A. I function that is at the heart of computerized systems’ algorithms. These techniques have benefits such as speech recognition, object detection, decision-making, and language translation. As a result of the Deep Learning feature in the system, the system can comprehend your audience.

In today’s environment, deep learning is at the heart of marketing. It trains and instills skills in computers such as reading text, audio, or photographs, providing responses, clarifying queries, making suggestions, and even enhancing filters on the posts and adverts you generate. These are the factors that assist marketers in identifying their target market. What is an advantage for marketers if that isn’t a benefit?

Benefits of Content and Search Recommendations

The entire internet, as well as everything associated with it, is linked. There are layers upon levels of responsibility for one another, but they can also act independently for whatever reason they are entitled to. This entails considering web content and searches.

They’re both related to and derived from the internet. Nonetheless, it is a part of the larger system that is responsible for its activities, but it is still connected to and affected by what comes before it. That which comes before is (another layer) Deep Learning, which is derived from (another layer) Machine Learning, which is derived from algorithms that are part of the computer’s architecture.

That’s putting it mildly, but you get the picture. Each layer can become sophisticated in its way, and each part becomes increasingly intelligent, making the entire system and everything that comes from it smarter.

The material you see in various forms all over the place, as well as the searches you conduct and everything you get out of them, all come from the same source. It’s all powered by deep learning, which is also an AI computer that analyzes massive pieces of data every second. This mechanical mechanism captures data on people’s online behavior all of the time.

This is for one simple reason: it teaches you to give yourself what you desire. Algorithms evaluate your preferences and provide you with only what you want. A marketer’s greatest gift is this amazing system.

Marketers who use this technique understand what their customers want and go out of their way to satisfy them. People are pleased because they are understood and receive more of what they desire. This AI system analyzes all of your searches and recommends things to you based on the results. The system teaches you based on your searches, clicks, and purchases, and so provides you with just what you require.

When it comes to machine learning, Google is likely one of the better examples to employ. We commonly refer to it as a search engine, but it is a clever computer that was smart yesterday and is now even smarter. It’s so clever that it recognizes your words, regardless of how they’re pronounced or misspelled, and provides the most likely matches for your search terms while producing results based on your misspelled/mispronounced words.

Google’s algorithm and updates, such as Hummingbird and Penguin, are all enormous pieces of machine learning and operative code with holistic capabilities that, on their own, are added to an existing powerhouse of intelligence.

This massive electronic entity has an immense amount of organized data that is split into multiple configurations at unfathomable rates to provide user-specific recommendations. All of this is based on exploiting not only keywords, their variations, contextual occurrences, and so on, but also user intent, user behavior, and user search history, among other factors. And this is only the tip of the iceberg; everything we’ve covered so far is the minimal essentials.

While there are many numbers, alphabets, symbols, and other things, it is the code that produces the results you see and makes consumers go “Wow!” Tailored results, suggestions, and so on are just a few of the things that will ultimately, if not instantly, take you to your intended goal. After all, there’s a reason why we use Google and a few other top-rated search engines when we need answers.

Marketing Automation using Ad Targeting

The practice of carefully picking which ads to show to which audience is known as ad targeting. However, because of these criticisms, the whole process of designing and selecting might become complex and intimidating. To make the process of tracking website visits and ad targeting more efficient and seamless, A. I technology has devised a system for marketing automation called (RNN.) Recurrent Neural Networks.

The premise is the same whether you use Facebook or Google as an example; they and other search engines will show you adverts based on your search terms and user activity. This feature is extremely beneficial to both customers and brands. Both don’t have to put in a lot of effort to reach their goals. For firms creating advertising, their efforts constitute an investment that search engines value for the benefit of their users.

If everything is configured correctly, every time a brand funds and runs an advertisement, Facebook, Google, and other platforms will direct the ads to show up for customers whose user habits match the services and items in the ads. When it comes to targeting an audience, criteria such as location, gender, age groupings, and so on, brands must be cautious when structuring their ads. If the configurations are incorrect, search engines will not assist them in generating the leads that brands require.


Many marketers utilize AI-powered chatbots that can interact with humans to answer customer questions, assist customers with purchases, and more. Chat-Bots play an important function. They interact with consumers and guide them through the sales cycle by recommending specific material based on their frequently asked questions, communicating with them across platforms, and sending personalized email campaigns.

When you need direct responses, chatbots are becoming increasingly famous for their accuracy. They are alert by nature and will give you exactly what you require if it is in stock. They don’t mince words when it comes to providing you with reliable statistics based on their data warehouse. With enhanced cloud technology, memory access is even more readily available than before, and users are satisfied with the quickness and relative correctness with which they receive their responses.

Because of the level of customer-friendly involvement, most customers can’t tell if they’re talking to a human or not when they speak with customer care online. Customers assume a courteous machine is behind those professional encounters because there are few blunders or miscommunications. Brands have reported increased revenue since implementing chatbots, and this is just the beginning.

Pricing that changes as time goes on

Both your audience and you as a marketer gain from dynamic pricing. It is advantageous to your product’s entire supply chain process. It is based on changes in product supply and demand in real-time. It’s an important method for marketers to use in their product marketing and customer service.

Apart from other advantages, dynamic pricing gives a corporation selling goods or services an online advantage over price adjustments made on the fly in response to market demands.

Pricing bots handle in-the-moment price modifications. These are software agents tasked with gathering data and adjusting pricing based on algorithm calculations. The customer’s location, the time of day, the day of the week, the level of demand, and rivals’ pricing are all factors to consider.

These bots gather a lot of information to assess and target your audience, as well as fine-tune the price benefits. Pricing bots collect and analyze individual consumer data to forecast current and future pricing that customers will be ready to pay.

It’s a legal action, and it’s also practical because most consumers believe they’re being treated fairly. The best example of its implementation is probably when you buy airline tickets or book hotel rooms on the internet. Dynamic pricing is also referred to as a customizing service. Fixed pricing, on the other hand, is a method of determining the selling price of a product or service that does not change.

When modifying prices, market price fluctuations, competition activity monitoring, and product demand and supply are all factors to consider. Lowering prices to stay competitive and maintain internal supply levels is the most natural technique that this mechanism employs. As a result, you’ll be able to stay competitive in the market.


Artificial Intelligence benefits us in more ways than we can realize; it is being used to address global warming issues, environmental issues, and even education for all types of people. In terms of businesses, it aids financial operations and management, mitigates and manages work-time losses in a variety of ways, makes business processes run more smoothly, and improves marketing procedures.

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