A rtificial Intelligence (AI) is revolutionizing many fields, including advertising. Thanks to its ability to process and analyse vast amounts of data in a short time and the development of models, AI opens up new possibilities for marketers. AI enables the creation of more advanced, better personalized, and more effective marketing campaigns. At the same time, we are increasingly understanding the potential of this technology as well as its limitations.
In this article, we will look at how AI is changing the world of marketing. I will present not only the benefits but also potential difficulties and dangers. Indirectly, we will also learn about competencies that should be in the arsenal of every marketing specialist.
This will be just an extended introduction – in subsequent texts and maybe in courses, I plan to continue this topic!
Benefits of Using Artificial Intelligence in Marketing
Let’s start with the aspect that attracts the most comments. Generative artificial intelligence (gen AI) allows marketers to generate ideas and create content. Often, their quality does not yet allow for direct use, but it can be a valuable starting point for further work, especially if we’re stuck at a dead end. Here, in addition to language models (ChatGPT, Gemini, Claude, etc.), one can also mention AI for generating graphics (MidJourney, Leonardo.ai) and sound (ElevenLabs). There are also a number of specialized applications, for example, for creating texts for Google Ads, generating company names based on specified criteria, or creating logos.
According to a 2023 McKinsey report, thanks to generative artificial intelligence, the increase in marketing productivity alone can translate into $463 billion per year, which means an increase of 5 to 15 percent.
Meanwhile, research conducted by the Boston Consulting Group and Harvard shows that ChatGPT improves the efficiency of marketers by 40%.
AI in marketing also opens up new possibilities for content personalization (I wrote a bit more about personalization in the later part of the article), customer relationship management, and increasing user engagement. For example, machine learning algorithms can analyse purchase history, including data from CRM, study preferences and interactions of users on websites and in social media, or determine the likelihood of some action (including conversion). Artificial intelligence will also help in automatic customer segmentation and enable the prediction of market trends.
Of course, that’s not all. AI also enables automation and optimization of advertising campaigns in real-time, adjusting content and targeting based on continuous conclusions drawn from audience reactions. Multidimensional data utilization will allow companies to recognize subtle patterns and trends that could elude traditional analysis. This enables marketers to achieve higher conversion rates at similar or lower costs. (I wrote a bit more about the impact on online advertising in the later part of the article and will deep dive in subsequent texts.)
Using AI to analyse customer data and adjust marketing strategies in real-time can increase the ROI of campaigns.
Artificial intelligence is also used for sentiment analysis, especially in social media, enabling companies to monitor and analyse consumer opinions about their brands, products, or services. This makes it possible to quickly respond to needs and communicate appropriately to improve the image and build good relationships with customers. It can also assist in combating fraudulent activities and false opinions.
AI also opens up new possibilities when it comes to the use of chatbots. Currently, they sometimes cause frustration, but gradually they will provide efficient support 24/7. They will answer questions, solve problems, and even conduct transactions.
In short, the use of AI in marketing can be a breakthrough in communication with customers and campaign management. Now, let’s take a closer look at three examples of the use of artificial intelligence to support marketing activities: personalization, online advertising, and content optimization.
Content Personalization Using AI
The use of AI for content personalization allows for communication to be tailored to each customer on a scale that was previously unattainable (in this context, we also talk about hyper-personalization). Thanks to the ability to analyse huge data sets, AI enables companies to deliver content, offers, and product recommendations that match the individual needs and preferences of each of us.
A study conducted by McKinsey showed that personalization can increase the efficiency of marketing expenditures by up to 30%.
AI can analyse data from various sources, including purchase history, information about products viewed, social media interactions, preferences of previous customers, similarities between customers, and much more.
Content personalization has a direct impact on customer engagement and satisfaction. A report by Segment (now Twilio) indicates that 60% of consumers whose shopping experiences are personalized are likely to make repeat purchases from the same retailer. Therefore, delivering content tailored to individual customer preferences not only increases the likelihood of conversion but also builds brand loyalty.
”The future of consumer goods is Data + AI +CRM + Trust. You can’t think about these things in a silo and you can’t think about them as separate investments. All of them work together in a continuous loop to help you unlock the step change and amazing transformation ahead of you.
Najah Phillips
It is worth mentioning that companies must find a balance between delivering valuable, personalized content and maintaining discretion and respect for customer privacy. From the consumer’s perspective, the use of AI may mean even greater inundation with information and messages. Moreover, when everyone relies on highly personalized communication, it will be harder for companies to stand out. This may create pressure to cross new boundaries…
Perhaps the future of marketing with AI is hyper-personalization, where almost every interaction with a customer will be unique.
AI in Content/SEO Optimization
In this section, I deliberately omit discussing how generative artificial intelligence aids in content creation, as that topic merits its own extensive article or course. However, I want to highlight how AI algorithms can analyse data on search trends, competition, and user behaviour. Artificial intelligence also helps in identifying keywords and generating meta tags, as well as in optimizing content and website structures.
Tools such as NeuronWriter, Surfer SEO, and MarketMuse come into play here, utilizing AI to craft content and recommend SEO optimizations, thereby enhancing search engine visibility and boosting organic traffic. This group also includes Yoast SEO and Clearscope.
As search engine algorithms constantly evolve, marketers must continually adapt strategies and monitor algorithmic changes. In this area, AI can come to our aid by adjusting content and code on our behalf. However, this is still rather a song of the future.
On the other hand, the increasing use of AI in SEO presents new challenges, such as difficulties in competing with content generated by tools like ChatGPT, which can be optimized in a way that is difficult for humans to achieve. In one of the articles, I already suggested that in the era of AI, the way we search for information and interact with the knowledge available online may gradually change. The future may belong to optimization for large language models (LLMs).
AI in Online Advertising
AI is also revolutionizing the digital advertising market, allowing for even more precise targeting of ads and advanced optimization of campaigns in real time.
As I have already noted, AI algorithms can analyse various types of user data – thanks to this, ads will be even more relevant and engaging. Platforms such as Google Ads and Facebook Ads use advanced AI algorithms to automatically adjust offers, content, and ad targeting, which increases the effectiveness of campaigns and maximizes ROI. In this context, it is possible to use Google Ads in such a way as to increase the likelihood of sales or lead acquisition by directing ads to people similar to our existing customers.
I do not fully agree that AI will allow marketers to focus primarily on creative actions and strategic thinking. It can also lead to excessive reliance on tools and contribute to bland campaigns.
I assume that such development will make the dominance of online advertising giants even greater. Thus, slogans about reducing costs may depreciate against their growing oligopoly.
Risks and Challenges of AI in Marketing
The use of AI carries risks and challenges that require attention and responsible approach from companies and employees.
Data privacy is growing in importance, especially with the expansion of regulatory requirements. I mean, among others:
- GDPR (General Data Protection Regulation) in European Union countries and implementing regulations of individual member states;
- The European directive on privacy and electronic communications (refers, among others, to cookies);
- CCPA (California Consumer Privacy Act) in the state of California, in the United States.
Companies must responsibly define the basis of artificial intelligence operations and understand the consequences involved. Patterns (data connections) detected by AI may change the nature of personal data, for example, certain data indirectly may indicate a high probability of some disease. Moreover, improper handling of data may increase the risk of data leakage or discriminatory actions.
Success in using AI in marketing requires a balance between technological innovation and a deep understanding of human emotions and needs.
There is also a risk that companies may become too dependent on AI algorithms, which may lead to a loss of personal contact with the customer (even despite personalization) or loss of brand character. Excessive automation can therefore negatively affect customer experiences and their perception of the company. It may also cause entrepreneurs to miss certain opportunities, while strongly entrenching them in the current territory. Creativity and intuition remain crucial, enabling more effective utilization of AI’s potential.
Implementing AI in marketing strategies may also encounter technical and operational difficulties. According to a McKinsey Global Institute study, one of the main barriers to implementing AI is the lack of qualifications and experience of employees. To fully exploit the potential of AI, companies must invest in training and development of their employees’ competencies. Cooperation with data analysts will also be important. (On this occasion, I invite you to read the article about how to talk about AI – link under the article.)
In an ideal world, consumers should have full control over how their data is processed. However, this is hardly realistic, so it would be valuable if they were at least aware of the consequences of submitting their data.
Future Trends in AI in Marketing
The future will bring many more innovations and changes. I have timidly outlined some of them above. However, the list of possibilities is almost unlimited.
The growing popularity of voice assistants, such as Amazon Alexa and Google Assistant, will affect SEO and content marketing strategies, requiring optimization of content for voice search. I have already mentioned optimization for LLMs. In this context, we can also include new kinds of devices like Rabbit R1, which utilize large action models (LAM) to operate on behalf of the user.
Emotion recognition technologies will be increasingly used to analyse user reactions to marketing content, enabling the creation of even more personalized and engaging campaigns (plus they may raise even greater concerns about how much “our” decisions are ours). Primarily, advanced analytics will be used to assess emotions, but it is not excluded that devices (including IoT) will also play a role here.
The use of AI in analysing customer data allows for discovering hidden patterns of behaviour that “ordinary” analysis would never have revealed.
Increased awareness of the ethics of using AI will mean that some companies will want to adopt clear guidelines for responsible use of these technologies, caring for privacy and data security of users. This may be an opportunity to stand out. At the same time, for instance, the gradual phasing out of the use of cookies somewhat drives corporations to utilize more advanced algorithms in order to balance the lack of them or to achieve even better results than with their presence. (In the EU the use of cookies is being limited in the name of our privacy as consumers.)
Many more trends come to mind, including one particular trend that I want to dedicate a separate article to. So, I encourage you to subscribe to the newsletter – the form is located under the article!
From analysing customer data, through content personalization, to SEO optimization and online advertising, AI opens new horizons for marketers. However, the development of AI also brings challenges for privacy and ethics, as well as resulting from increased competition – they concern not only consumers but also companies. As technology continues to develop, companies will need to find a balance between leveraging AI capabilities and responsible data and customer relationship management.
The future of marketing with AI looks exciting but requires marketers to continuously learn and adapt to a rapidly changing environment. To stay updated, please subscribe to the newsletter (form below) and explore other AI-related articles:
