The marketing community has repeatedly declared that artificial intelligence is to transform the industry soon. Everyone talks about the advantages and opportunities it offers.
Yet, the recent developments underline that AI technology may be challenging to implement. There are limitations, shifts within the market, impact on creativity, and growing operation volumes.
Will the marketing industry reject implementing AI or confine itself to automation with AI elements? Who and how will continue using it?
In this post, you will know more about the concerns regarding artificial intelligence implementation.
Artificial Intelligence for Marketing: More Concerns Than Implementations
For sure, the volume and amount of the data that marketers process today, as well as the speed of operations, push the sales and marketing departments to implement new approaches. Thus, it is no surprise that an average marketer uses AI for personalization, whether it refers to email campaigns, product recommendations on websites or entertainment pieces.
For instance, Lay’s developed a website to offer personalized messages for fans and users with an AI deepfake feature at the core. Such a case shows that AI can be effective for engaging with the audience.
In addition, the AI finds its application in advanced segmentation and media selection. Yet, some studies underline that AI has its limitations, referring to the adoption of technology and changes within the market.
First of all, 50% of marketers surveyed by Advertiser Perceptions did not consider using AI for their growth in the future. The apparent reason is that it is costly, requiring additional skills and expertise from the users. Lays’ example proves that mainly big companies with large budgets have time and resources for AI-based campaigns.
According to another report, around two-thirds of the marketing experts have struggled with personalization, while only 17% of the respondents apply artificial intelligence and machine learning for marketing solutions.
Why? Does AI fail to provide the solution?
The explanation can be mistakes that AI makes and the lack of expertise for its implementation. Among other things, there is even a threat to creativity due to the delegation of the processes to the machines or algorithms.
It urges sales teams to either have a well thought artificial intelligence marketing strategy or apply only some AI-based solutions.
Elements of Artificial Intelligence: Actual Contribution
AI-based solutions usually help to solve issues. That’s why many would argue with the fact that AI can negatively influence branding or digital marketing efforts. Indeed, the elements of artificial intelligence contribute to companies’ strategies. However, they are not problem solvers. The following elements seem to be widely used:
Machine Learning
Machine learning contemplates the use of data, usually collected by the marketing team, for further analysis. For instance, this element offers to assess the patterns and behavior of customers for achieving greater results or conversion.
With machine learning, a content marketer can get feedback on a post and add additional parts, like a video or gif. In its turn, they are to offer better engagement. However, it is not solely an AI program solving a marketing issue, only a way to point at the area to be enhanced.
Natural Language Processing and Conversational AI
The next part of AI technology relates to natural language processing (NLP). It contemplates identifying the speech of the humans, in particular, users. In terms of marketing, it is usually combined with conversational AI.
How are they applied? Well, they made chatbots employment possible. Almost every brand today has a bot on their websites, used for communication, feedback, surveys or polls. The NLP method within such bots sets the basis for greeting the customers and starting a conversation.
Nonetheless, they usually offer basic answers and depend on the script made by developers.
Computer Vision and Anomaly Detection
Lastly, other elements may be as handy in producing content. For instance, computer vision, concerned with recognizing contents or forms within images, is used on social media, like Instagram, for filters, masks, and AR creation.
Yet, it is only a tool, using a part of AI technology. The designers’ role is crucial there. THEY form the entertainment piece that becomes interactive. They are doing science.
Simultaneously, the concept of anomaly detection is widely used in SEO. It helps to report the changes in metadata, links and traffic. Some tools employ anomaly detection to show or predict the shift within rankings, making it possible for an SEO expert to answer the change accordingly. However, the particular tools lack advancement and only can offer data. The interpretation of information becomes the responsibility of the marketer.
The insights of the market research artificial intelligence helps to collect are beneficial for marketers. The majority of AI tools focus on data analysis. Thus, any AI operation involves collecting info, analyzing it with an AI mechanism, and interpreting results.
All these actions depend on a marketer, adding more pressure on them. This pressure appears to be a comprehensive explanation of why part of the community does not support the promotion of AI in the industry.
AI Marketing Automation: Is It a Solution?
Currently, benefiting solely from automation seems to suit the marketing specialists. It leaves a space for creative ideas, saving time and getting rid of repetitive tasks.
Let’s consider segmentation strategy as an example to define why using automation tools is preferable to AI. Imagine that a sales manager needs to find leads or segment the audience.
Using an AI can be efficient. However, there is a high chance of having wrong calculations. No one has a right to make a mistake. Besides, it requires much time and tests to make the right ones.
What would marketers do? They would likely resort to automation tools or a combination of some. Let’s say they can use a business email finder to find an audience within a B2B database. They will discover leads with verified emails and use simple AI marketing automation to create personalized messages.
Automation lets them think, be creative and follow a strategy. In the short term, when a person has no time for learning new skills or adopting advanced solutions, such a decision would be the right one. Unsophisticated AI marketing automation may improve and not worsen the situation.
As a result, any new artificial intelligence marketing strategy would require experiments and tests. Not many brands nor services want it and can let it happen. They have volumes to deal with and trends to answer to.
Marketers are too busy to manage rapid changes and follow key trends. And it is another explanation why only big brands are able to use the artificial intelligence marketing strategy to the fullest.
Summing Up
What is artificial intelligence for marketing today? The studies show it is concerned with using its elements to assess information and automate specific processes. However, the concerns are that marketers lack time and skills to implement advanced AI solutions. That’s why combining automation tools with some of the AI principles seems to be the optimal solution for an ordinary marketer.
