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How can marketers use artificial intelligence ?

How can marketers make use of AI in their marketing strategy?

Marketing and retail AI implementations pay off for brands

Brands are increasingly using AI tools to produce detailed customer insights, marketers are using this information to better target customers, the difference shows, as more than 80% of IT professionals in marketing and sales worldwide believed AI led to a reduction in costs.

In fact, many marketers already use AI without knowing it, by using email automation workflows or generating keywords, in fact they’re using AI to assist them in their functions.

According to the Harvard Business Review, out of all company functions, Marketing has the most to gain from AI, its used to better predict the accuracy of sales forecasts and ad targeting.

What can marketers do with today’s AI technology?

Today’s Artificial intelligence can drastically help marketers in their core activities such as analyzing customer needs, developing products that match those needs, and most importantly convincing customers to buy those products. A 2018 McKinsey analysis that studied 400 advanced use cases demonstrated that marketing would benefit immensely from Artificial Intelligence.

In fact, chief marketing officers are increasingly adopting Artificial Intelligence as a technology.

According to a 2020 Deloitte global survey of early adopters, three out of five AI objectives are marketing oriented:

  • Enhancing existing products and services
  • Developing new products and services
  • Improving relationships with customers

 

AI Artificial Intelligence Machine Learning

  Building Flexible, Living structures:

New AI technology has been described as “radically human” meaning its modelled on human brains and behavior, in what is now referred to as living systems. Artificial Intelligence models are now capable of seeing, talking and understanding human interactions in a much better and efficient way than previous intelligent technology could. This can give an edge to marketers as more data is collected from their customers in more than one way, from different sources.

 

 

 What are the different types of marketing AI in the market today?

Marketing AI is categorized in two ways: complexity level (intelligence) and whether it’s a stand alone or part of a broader platform.

Task automation is part of the repetitive and structured functions that require limited intelligence. An example of that would be a system which automatically welcomes customers by sending them a welcome email when they sign up to a service/platform. In addition, Chatbots such as those that are used in Facebook messenger and different social media providers are in this category as they can provide customers with basic guidance, directing them down a decision tree, but they don’t have the capability to offer adapted responses or learn from exchanges.

Machine learning is another type of Artificial Intelligence where algorithms are used to analyze large amounts of data and make intricate decisions and predictions. These models can distinguish images, decrypt texts, categorize customers and anticipate how customers would respond to a variety of initiatives such as offers and sales. Machine learning is also used in programmatic ad buying, e-commerce recommendation engines and other functions.  Deep learning is a more sophisticated variant of machine learning, and they constitute now the trendiest and most effective tools in marketing.

The two remaining types of marketing AI are Stand-alone applications which are separated/isolated AI programs. Hence the customer or employee would use the application outside of the sales channel.

The last type of AI is Integrated Applications which is set in existing systems, this of AI application is less obvious than the stand-alone ones to the customers and salespersons. For instance, machine learning making split second choices concerning which digital ads to offer users is built into platforms that handle the entire process of buying and placing ads. Another example of integrated applications is Netflix’s machine learning which have been offering customers customized streaming recommendations for the past decade.

In this video covering the main marketing trends in 2022, two of them are based on AI (AI supported marketing and hyper personalization)

https://www.youtube.com/watch?v=5ey3kICQrGg

 What are the different types of marketing AI in the market today?

Marketing AI is categorized in two ways: complexity level (intelligence) and whether it’s a stand alone or part of a broader platform.

Task automation is part of the repetitive and structured functions that require limited intelligence. An example of that would be a system which automatically welcomes customers by sending them a welcome email when they sign up to a service/platform. In addition, Chatbots such as those that are used in Facebook messenger and different social media providers are in this category as they can provide customers with basic guidance, directing them down a decision tree, but they don’t have the capability to offer adapted responses or learn from exchanges.

Machine learning is another type of Artificial Intelligence where algorithms are used to analyze large amounts of data and make intricate decisions and predictions. These models can distinguish images, decrypt texts, categorize customers and anticipate how customers would respond to a variety of initiatives such as offers and sales. Machine learning is also used in programmatic ad buying, e-commerce recommendation engines and other functions.  Deep learning is a more sophisticated variant of machine learning, and they constitute now the trendiest and most effective tools in marketing.

The two remaining types of marketing AI are Stand-alone applications which are separated/isolated AI programs. Hence the customer or employee would use the application outside of the sales channel.

The last type of AI is Integrated Applications which is set in existing systems, this of AI application is less obvious than the stand-alone ones to the customers and salespersons. For instance, machine learning making split second choices concerning which digital ads to offer users is built into platforms that handle the entire process of buying and placing ads. Another example of integrated applications is Netflix’s machine learning which have been offering customers customized streaming recommendations for the past decade.

In this video covering the main marketing trends in 2022, two of them are based on AI (AI supported marketing and hyper personalization)

https://www.youtube.com/watch?v=5ey3kICQrGg

In the podcast below, we’re going to discuss some concrete examples of how companies are using Artificial Intelligence to better target their customers. 

https://open.spotify.com/show/4suimK3zjOuJyPYQp9HknH

Bibliography:

  • Jessica Lis (July 13, 2022). eMarketer article from Report: Top Start-ups in AI 2022
  • Wilson, H. J., & Daugherty, P. R. (2022). Robots Need Us More Than We Need Them. Harvard Business Review, 100(2), 84–95.
  • Davenport, T. H., Guha, A., & Grewal, D. (2021). How to Design an AI Marketing Strategy. Harvard Business Review, 99(4), 42–47.
  • Ascarza, E., Ross, M., & Hardie, B. G. S. (2021). Why You Aren’t Getting More from Your Marketing AI. Harvard Business Review, 99(4), 48–54.
  • Daniel Konstantinovic (October 20, 2022). TikTok tries to help usher in an age of machine learning advertising. eMarketer
  • Albert Bollard, E. L. (2017). The next-generation operating model for the digital world. United States: McKinsey.
  • Jasmine Enberg (Mar 30, 2022). TikTok Commerce 2022 How Brands Can Cash In on #TikTokMadeMeBuyIt with a Content-First Strategy. eMarketer
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