The way businesses function today it seems marketing is the most important business operation that is likely to be mainly run on artificial intelligence, if not completely. As dystopian as this may seem, the essence of marketing is to understand customers, match the correct products and services to them, and, lastly, persuade them to buy said things. 

With these factors of marketing in mind, it is no wonder businesses are on the path to putting AI into this role to enhance their marketing strategies. In the past, marketers were the ones to gather customer data and analyze it for trends, feedback, and so on. With this gathered information, they could use strategies to attain customers and reach company goals. 

Artificial intelligence is found basically everywhere in today’s marketing climate, among many other sectors, such as job boards like Lensa. It isn’t a tool meant to replace marketers but rather facilitate mundane tasks such as data gathering, which we will expand upon later.

The Use and Role of AI in Marketing

In recent years, artificial intelligence has taken the front lines of marketing firms and departments. The market value of artificial intelligence technologies used for marketing hovered around $12 billion globally, demonstrating how necessary and widespread its use is.

 It is being estimated that the role of AI in marketing will not only be even more widespread, with companies such as Lensa already utilizing it in strong aspects but will be worth over $35 billion within the coming years. 

Last year, statistics showed that 80% of marketers were implementing AI in their strategies to some extent. The two main categories are for stand-alone AI or one that is used on a broader platform. There are different levels of implementation that companies use for artificial intelligence, which we will explain below. 

Task automation

Past marketers were tasked with gathering data, interpreting and analyzing it to bring outcomes for probable trends, leaving feedback, and so on. These outcomes would influence future business decisions at a company but be volatile due to the guessing nature of this strategy and human error alike. 

These repetitive tasks, such as sending out automated news emails or reminders, can be done by low-intelligence level AI. Think of these as simple chatbots, which is also what they are. In essence, they provide basic help for basic requests but can’t handle more complicated inputs such as customer feedback and so on. 

This automation method doesn’t learn or grow, nor does it provide specialized services such as interpreting intent within texts. Its job is to simply remove an extra load of unnecessary work for marketers to focus on more important matters. 

Machine learning

AI with machine learning could be the greatest addition marketers could have. It consists of intelligent, algorithm-based software that requires massive amounts of data to make accurate yet complex predictions or decisions. 

These AI models can interpret text data to understand the intent behind a man-made body of text, organize and aid customers, even those with specific requests, recognize images and voices, and even predict how customers will respond based on past data. 

Programs such as text classification AI fall under this category. The algorithmic nature of this program allows for heightened accuracy compared to human counterparts and is a preferred method of predictive marketing among many other methods. 

The downside of machine learning is the extreme amount of data it needs to function accurately. Some smaller firms cannot allow themselves the convenience of having the capacity to provide so much data, thus creating gaps in the market. Let this be the only setback though because so far, machine learning AI has proven itself cost-effective and accurate globally to businesses.

Let’s expand on stand-alone applications versus integrated ones to better understand the challenges and opportunities AI in marketing can bring. 

Stand-alone 

These applications are programs that are separate from the main channel of execution. in other words, these AI programs can help customers determine their tastes and such but the purchase of the products the AI chose for them has to be done on the main channel of operations. 

Integrated 

As the name suggests, these AI programs are integrated into the main order of operations without even being noticed by customers. Integrated applications use extremely fast decision-making to bring outcomes such as showing a specific ad to a specific customer or product recommendations. 

Customer relationship management systems (CRM systems) are the main wing of marketing that has incorporated machine learning into their operations, as mentioned earlier. The immediate feedback they get from these applications is a big positive. These AI have gotten smart enough to train people in assisting calls and so on. 

Conclusion

So far, from business experiences, the positives of AI implementation in marketing have outweighed the negatives. Predictions show it will only get better from this point, making it a strong element for businesses to own.