Author: Julia Voloshchenko, PR professional and Editor-in-Chief of the Usetech blog. Expert in media relations and branding. I write about technology and business.

In recent years, it’s impossible not to pay attention to the penetration of artificial intelligence in all areas of human activity. Artificial Intelligence is capable of radically changing many areas, from healthcare to real estate.

Artificial Intelligence in marketing is nothing new, but more and more companies are investing in this technology and incorporating it into their business in order to optimize and increase productivity.

In this article, we will look at the main directions of artificial intelligence in marketing, trends and predictions for the next few years.

How Do Big Brands Use Artificial Intelligence?

Large technology giants, medium-sized businesses, and small companies are all keeping up with the times and using new technology in their developments to be competitive. For example, AI is an integral part of Alibaba, which uses it to predict customer purchases. The next example is Amazon, which uses AI in its digital voice assistant Alexa. Amazon’s AI also collects data on customers’ shopping habits and makes purchase recommendations using analytics.

Jeanel Alvarado, Retail Expert at RETAILBOSS, gives examples of the following brands:

ASOS: The British online fashion retailer utilized AI technology to conduct virtual photoshoots, where real-life models had virtual copies of the brand’s clothes mapped onto their bodies. This provided shoppers with realistic garment images without the need for physical photoshoots.

H&M: The popular clothing store relies on AI to stay on top of local trends and optimize its supply chain. By analyzing store receipts and returns, H&M can evaluate purchases at each store and tailor their inventory to meet local customer preferences.

Zara: The fashion giant uses robots powered by AI to help customers pick up their orders in-store quickly and efficiently. Customers enter a code at a pickup station, activating an in-store warehouse robot that locates the order and deposits it in a Dropbox.

Macy’s: The department store’s “On Call” app features an AI-powered in-store shopping assistant that helps customers navigate the store, find items, and check stock availability.

Uniqlo: The clothing retailer uses AI-powered UMood kiosks in select stores to measure customers’ reactions to different products through neurotransmitters. Based on these reactions, the kiosk recommends products tailored to each individual’s preferences.

Most recently:

Levi’s brand: The renowned apparel company, has recently announced a groundbreaking partnership with, a digital fashion studio specializing in AI-generated models. This collaboration aims to revolutionize the way Levi’s showcases its clothing line by using artificial intelligence to create a diverse range of models that reflect various skin tones, body types, ages, and sizes.

Where Does Artificial Intelligence Find Its Application In Marketing?

Using chatbots based on Artificial Intelligence

With AI, companies are improving the customer experience, for example, by communicating with users using chatbots. Ilya Smirnov, head of Data Science at Usetech, describes how he participated in the development of chatbots for call centers:

“Modern machine learning technologies help to significantly reduce the cost of providing services, as well as increase the efficiency of the centers. Practice shows that about 70% of the requests coming to the hotline are of the same type. Currently, the robotic services of the so-called “first line” support effectively allocate these requests. To provide high-quality services, it is enough for them to recognize the subject of the request and ask the client a few clarifying questions. This allows the company to clearly, quickly and unambiguously satisfy the client’s request.

It’s worth noting that a request from a client can come in various forms and through various communication channels — messengers, chatbots, a voice assistant or an operator working according to a definitely verified algorithm. And in all these cases, machine learning technologies come to the rescue. They allow you to determine the most appropriate “mask” of questions and give a more accurate answer to customers.

The most primitive robotic systems are linear chatbots. We meet them in messengers, social networks, mobile applications and on websites. The listed chatbots are untrained and work according to a certain scenario. But they are useful — with their help, you can order a pizza or a table in a restaurant, specify the cost of sending a parcel or get a ticket to see a doctor. At the same time, the average request processing time will be reduced by about 3 times. These bots allow you to maintain customer loyalty — it is known that more than 50% of people would prefer to solve issues without communicating with people. And prompt and more detailed information undoubtedly leads to an increase in sales.”

Ilya talks about the experience of creating chatbots and the results:

“Let’s analyze another example of a first-line chatbot, in the development of which I happened to participate. The company was engaged in insurance and wanted to create its own chatbot with AI. The peculiarity of this project was the complete absence of chat, and the entry point of the request was in the voice channel. The pandemic worsened the situation and led to a severe overload of the voice channel. As a result, it was decided to configure a first-line support bot to improve the quality of service and unload the call center.

At the first stage, we just launched a chat and in a month tried to make it a single entry point for most requests.

Then we analyzed and configured a system of quick widgets of the following type: information about the policy, an appointment with a doctor, an insurance case, etc. The client could choose one of these widgets and continue to communicate with a live operator in a chat. At the same time, the operator tagged the dialog with the client. In fact, at the first stage, the operators carried out data markup.

Then the system put down the tags automatically, and at the end of the conversation the operator had to confirm them. This procedure took no more than 10 seconds. By the way, this option is still valid.

Every two weeks, we conducted additional training in recognizing the topic of communication.

At the final stage of the project, the chatbot completely closed 30% of requests in automatic mode without operator participation, another 35% of requests required only operator confirmation, due to the specifics of the insurance business. Of the remaining 35%, about 80% of the chatbot clients correctly redirected to the operator, making mistakes only in 20% of cases. As a result, the average time for solving a request in which the operator’s participation is required has been reduced from several hours to 10–15 minutes.”

AI-based personalization

We won’t argue with the assertion that personalized messages seem more appealing. This especially applies to marketing and PR when you’re doing consumer mailings or advertising.

Angelo Sorbello, Linkdetta Founder, notes:

“Artificial intelligence enables marketers to deliver highly personalized content and offers, resulting in improved customer engagement and increased conversion rates.”

“An area where AI has shown great promise is in personalization, which we use a great deal in our marketing. This helps us better understand our customers and target them more effectively. With the ability to analyze vast amounts of data, AI can create highly tailored content and experiences for each individual customer. This not only increases engagement, but also builds trust and loyalty with the brand.” — adds Teajai Kimsey, Director of Marketing & Communications at Crystal Structures Glazing.

Predictive analytics

One of the most promising areas of data processing is predictive analytics. The development of artificial intelligence, in turn, has accelerated the development of predictive analytics, which has brought it to a new level. In addition to marketing, predictive analytics is used in healthcare, industry, and transportation.

“AI-driven predictive analytics helps marketers identify trends, anticipate consumer needs, and optimize campaign strategies. In my experience, utilizing AI for data analysis has allowed us to make informed decisions and better allocate our resources, leading to more effective campaigns. One of the most famous examples of AI-driven predictive analytics and personalization in marketing is the story of Target’s pregnancy prediction model. Target’s data analysis team developed an algorithm to identify customers who were likely pregnant based on their purchasing habits. In one instance, a teenage girl received targeted pregnancy-related offers in the mail before her family was even aware that she was pregnant. This demonstrated the power of AI in identifying consumer needs and preferences, even before they’re explicitly expressed, enabling marketers to deliver highly relevant content and offers that drive customer engagement and sales.” — adds Angelo.

Artificial Intelligence for content creation

Artificial Intelligence comes to the rescue when you need an effective headline or text, need audience analysis for engaging content, or analyze audience behavior. AI’s capabilities in this area are only growing and evolving: Think of the highly acclaimed ChatGPT or Midjourney. Of course, AI text needs to be edited and augmented to make it more lively and understandable, but AI can help you with topic selection or headline choices.

“Currently, the main point of contention is how AI is used for content production. Now we can research, strategize and write content in seconds, but this leads to so many questions about search engine standpoints, user experience, and the degree to which we can capitalize on this technology. Some will use it too excessively, while some will avoid it until they can’t any longer, but the truth is that the impact of AI is indeed revolutionary for the industry.” — notes Joe Cowman, Head of SEO at FATJOE.

Another expert, Vladimir Fomenko, Founder of Infatica, adds:

“Using natural language processing (NLP) to produce more tailored and engaging content is one of the most interesting new advances in AI marketing. For example, businesses may use this tool to analyze massive volumes of client data to find trends in language and sentiment and then adjust their marketing appropriately. This not only increases engagement and conversion rates, but it also aids in the development of better customer connections.”

Some talk about the negative impact of ChatGPT on marketing, but some believe that it can help marketers and content managers in their work and make it more effective. AI tools should be seen as assistants, not as replacements for humans.

“Creating targeted marketing campaigns can be time-consuming and resource-intensive. However, with ChatGPT marketers can create campaigns quickly and efficiently. ChatGPT can generate high-quality content in minutes, freeing up time for marketers to focus on other high-value areas and strategy.

Marketing campaigns can be expensive, especially if they are not targeted correctly. Using ChatGPT can help reduce costs by creating campaigns that are specifically targeted to the right audience. This can lead to a better return on investment (ROI) and a more efficient use of marketing resources.” — notes Simona Georgescu, CEO and Owner at Adduco Communications.

Artificial Intelligence and copyright

Following the discussion of content, we can raise the next interesting topic: copyright in artificial intelligence. Does it exist? Who is the author of the work — the artificial intelligence or a human? This question remains open. In some countries, copyright is recognized for the developer of artificial intelligence. Lawyers in many countries recognize that giving artificial intelligence as a subject of legal relations will have consequences that humans cannot control.

“AI will serve as the primary battleground for data, privacy, and copyright debates. Simmering just beneath the surface of the AI hype is a complex and important conversation about rights and licensing. While the visual and written content is considered ‘generative,’ the reality is, it is entirely ‘derivative’ of existing material. And when it comes to AI, the most valuable material is data. Companies like OpenAI and StabilityAI scour the web for data to train their models. That data provides the seeds that spring into answers to any and all requests consumers type into the chat interface. But who owns the answers? The clever individual who pieced together the query, the AI platform, or the original owners of the data? Marketers who fail to carefully consider these questions as they begin to incorporate AI-generated content expose themselves to incredible — and unnecessary — legal risk down the line.” — adds TJ Leonard, CEO at Storyblocks.

“AI tools will help marketing teams and their businesses save time and resources while improving the effectiveness of their campaigns. With the current AI trends, content will be the area most affected by artificial intelligence. Teams can integrate advanced language processing tools and machine learning algorithms to create highly targeted and personalized campaigns.” — also adds Matt Caiola, Co-CEO of 5WPR.

Artificial Intelligence for attracting and working with clients

Above, we’ve written about chatbots, which can help with customer interaction. But chatbots are not the only use of artificial intelligence in marketing.

AI helps in analyzing customer experience and collecting customer feedback. Since it works with large amounts of data, you don’t have to spend a lot of time analyzing and researching it. And when combined with Machine Learning and Data Science, you can achieve amazing results and analytics.

“The process of converting website visitors to leads or sales is known in the digital marketing industry as conversion rate optimization (CRO). CRO not only uses AI, but included in this process is A|B testing of web pages, heatmaps, search engine optimization, and more. The idea is to make the website more effective over a 90-day period before focusing on demand-generation campaigns to drive more traffic to the website.” — notes Melih Oztalay, CEO at SmartFinds Marketing.

What predictions do we have?

“On a more fun level, AI will continue to expand the ability to create music and art. AI will continue to inspire new and innovative applications, like the creation of virtual assistants that can mimic human conversation more closely.

In short, there is so much potential in what AI is already doing (self-driving cars and the Internet of Things), but there is also a lot of potential to be used improperly. The future will bring much more innovative AI uses, along with more ethical guidelines for those uses.” — notes Teajai Kimsey.

“AI is poised to revolutionize retail marketing in the coming years, with numerous major retailers already embracing AI technologies to enhance customer experiences, streamline operations, and improve overall business efficiency. As AI continues to develop and become more accessible, its applications in retail marketing are expected to expand and become even more sophisticated.” — Jeanel Alvarado predicts.

Experts predict that total spending on artificial intelligence systems will reach $97.9 billion in 2023. Artificial intelligence and neural networks are becoming a new challenge for the market, opening up new opportunities for companies.

As you can see, Artificial Intelligence has high potential to change and augment marketing practices, but despite this, it remains intimidating for some people. They are intimidated by the likely processes of replacing human resources with AI. But maybe we should work together with artificial intelligence and other technologies to achieve high-impact results?

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