It is well known that to have success in business it is necessary to adapt, to analyse the market, to understand and listen to clients. Technology doesn't have to be something scary, not like in the movies where the robots take over Earth. If you use Google Maps, Facebook, or Amazon, you are already using artificial intelligence (AI) and machine learning (ML), maybe without realizing it. AI and ML can be extremely useful in marketing. And that is what we are going to show in this post. 
 

First of all, what is artificial intelligence? 

AI is nothing more than using machines capable of analyzing and understanding the data and making decisions accordingly. For that, it is necessary to give the engine enough information to categorize the required data correctly. As kids need to learn the name of animals and color, machines also need to learn the category, but the process is much more complex. Machine learning focuses on analyzing problems and processes and finding a way to optimize them. 
 

Why should you use artificial intelligence and machine learning in marketing? 

AI and ML reduces costs by automating repetitive data-driven tasks, with faster and exceptional results. And also improve performance and revenue by enhancing the ability to make predictions. Artificial Intelligence and machine learning don't use logic, but statistics, it works with probability. It analyses the data you have, optimizing the process. Machines can analyse a much more complex volume of data, faster than a human being, making the process cheaper and more precise. It makes predictions of future outcomes based on historical data. As the machines get smarter, the projections also get better. 
 

Where can artificial intelligence and machine learning help in marketing? 
 

The complex and highly personalized data obtained from ML and AI provide a better understanding of customers and prospects, building their profiles. Data such as more in-depth information about demographics, socio-economic, and geographical patterns from costumers.  Information that enables marketers to deliver the right message to the right person at the right time, and make proactive changes to their strategies. 

Artificial intelligence and machine learning can help during the planning, production, promotion, performance, and personalization process. Here are some examples of how AI and ML can help in marketing.  

Deep Data Analyzes and Segmentation 

It is impossible to imagine a marketing strategy without data. It is necessary to anticipate client behavior, understand the competitor, and define the four Ps (place, product, price, and promotion). AI-ML precisely analyze big data faster than human beings, capacitating marketers to create strategies relying on information and not on their guts. The analysis can contain all fonts of data, call center, chatbots, CRMs. It also can analyze the market and find people who are potential clients and content they think is relevant. It also can examine social and emotional content, understanding when a person talks about the product, what kind of emotions they have.  If being frustrated, or if they are interested and curious about the product, for example. 
 

Personalization 

 AI-ML provides specific information about customer behavior, purchasing patterns, and others. Those data are necessary for better conversion rates and personalized customer experience because it enables a marketing strategy focusing on personalization, behavioral targeting, micro-targeting, and other marketing parameters.  For example, with face recognition, a fast-food chain can suggest what the person would like based on her previous meal, and this information can also be combined with the time of the year and the customer habits for such season. 

On-time Experience and Trying on  

Artificial intelligence and machine learning offer not just a personalized but also an in real-time experience, cheaper than the traditional ways. For example, chatbots, answering clients' questions anytime, and combined with face recognition and augmented reality (AR), customers can try a product anytime, anywhere, and even see how that desired couch would fit in their living room. 
 

Recommendations: 

Big data combined with machine learning and artificial intelligence can result not only in the creation of better products and solutions to clients but also in a better suggestion of a new item to the client. That is possible because it uses statistics of the information of previous content and products consumed by the client instead of using logic and guts. An example is the suggestion system from Netflix. 

Other uses: 

• Content auto-generation and curation;  

• Email marketing; 

• Smart search results; 

• Voice searches; 

• Smart web design; 

• Testing data; 

• Object recognition. 
   

The best way to start with AI is step by step, finding the most time-consuming activity and the amount of data you need to analyze, and look for better solutions. Also, think if that data is relevant to build a better customer experience. 

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Article written by Juliane Verissímo - Marketing Department of VisionSpace