How AI Transforms the Marketing Domain For the Better?

Have you ever heard of the term ‘Artificial Intelligence Marketing?’ Artificial intelligence marketing solutions offer several ways to bridge the gap between data science and execution. Many of us would have been subjected to the tedious process of sifting through and analyzing the abundant dumps of data. Thanks to artificial intelligence, it has become easier and feasible.

Big data has evolved to a great extent, and the advanced analytics solutions it offers make it possible for marketers to get a clearer picture of their target audiences. Artificial intelligence marketing refers to the method of leveraging customer data and artificial intelligence concepts such as machine learning to improve the journey of the customer and anticipate the next move of the customer.

So, what is Artificial Intelligence?

Understanding Artificial Intelligence

Artificial intelligence (AI) deals with using computers to understand human intelligence, and it is the science of making intelligent machines, especially intelligent computer programs. It refers to adding human capabilities into machines. AI initiates problem-solving, common sense, and analytical reasoning power in machines. Put simply, AI involves making computer programs that imitate human behavior.

This article will delve deep into some of the ways in which artificial intelligence improves the marketing domain for the better.

How AI Transforms Marketing for the better?

Let us look at some of the areas in which AI is incorporated in marketing.

1.Search Engines

AI has a profound impact on the manner in which we search and the quality of the search results that define the search experience. Google first innovated with AI in search in 2015 by introducing its machine learning-based algorithm, RankBrain. From that time onwards, many e-commerce websites have followed Google’s footsteps and incorporated artificial intelligence into search engines to help make product searching smarter. Innovations such as semantic search and natural language processing help search engines determine the links between products and provide similar product suggestions, find relevant search results, and autocorrect mistakes, thus aiding customers in discovering products even if they do not have a clear idea of what they are looking for.

2. Product Pricing

Demand-based price changes are not new. A perfect example of this is the change in hotel room rates based on seasons. Using artificial intelligence in marketing will help determine and optimize prices with a whole new level of precision by taking into account a wide variety of data. AI and machine learning are used to analyze a customer’s data patterns, predict their receptiveness to special offers, and the price they would be willing to pay. This helps businesses target customers with more precision and helps them calculate the exact discount needed to pull in a sale. Businesses can use dynamic pricing to determine if their pricing of products is too high, too low, or almost at the same range in comparison with their competitors.

Airbnb is a perfect example of a dynamic pricing system that helps property owners determine the price at which their property must be listed. It takes into consideration a wide array of factors such as local events, geographic location, photographs, reviews, time to the booking date, and market demand. Using these calculations, marketers can provide which the users will choose to follow or ignore. The system will then adjust the algorithm based on the results.

3. Audience Targeting and Segmentation

To reach out to customers with a proper level of personalization, marketers need to target increasingly granular segments. Artificial intelligence can help achieve this. Based on the data that marketers already have regarding customers, machine learning algorithms can be trained against a gold standard training set to pick out incorrectly identified contacts and identify common properties and important variables. The amount of customer segmentation that can be done by marketers depends on the data they have. Segmentation can be based on past behaviors and buying personas, or it can be as simple as gender and age.

Segmentation is not limited to just being static. Dynamic Segmentation is an application of artificial intelligence that consumer behaviors are rarely unchanging or fixed and people can take on different personas for different reasons at different times. For example, if a young individual browses for items to gift for an older friend or relative, dynamic segmentation will group them in with the segment that is most appropriate to current buying behavior. It uses real-time data to present the most relevant offers and avoids making use of outdated data for targeting.

4. Sales Forecasting

This is another prediction-based application of AI. Using economic trends, past sales data, and industry-wide comparisons, artificial intelligence can help companies predict short-term and long-term performance, inform business decisions, and forecast sales outcomes. Sales forecasting can also be used to estimate product demand, though sales teams must also take other factors into account. It is important to not rely just on sales figures to predict demand as that would produce an inaccurate forecast.


Machine learning and artificial intelligence are becoming an increasingly integral part of many industries. AI has the ability to eventually transform the economy and reshape most businesses by introducing new products and business models. Artificial intelligence goes beyond the functionality of virtual assistants such as Siri or Alexa. AI enables marketers to improve customer service, improve products based on feedback, and address any dissatisfaction with respect to your brand. Artificial intelligence has, no doubt, transformed marketing for the better and will continue to do so.

If you are interested to know more about artificial intelligence certifications, check out Global Tech Council.