However, not every organization has the necessary knowledge to understand this functionality and how it is possible to improve existing actions. After all, if what is already in use works, AI comes in as an additional tool to contribute to the results.
One example is the banking services sector, which currently uses several machine learning solutions to obtain positive returns when collecting consumer data. And, clearly, opting for artificial intelligence should be an addendum to the next steps.
One case is for those who rely on hyper-personalization in the principalization process. In other words, it refers to the practice of personalizing interactions and experiences with customers in a highly individualized way.
But in the end, what exactly is the moment when AI can be applied to this practice?
Applying AI
Artificial intelligence (AI) plays a crucial role in hyper-personalization , enabling businesses to collect, process, and interpret massive amounts of data to deliver personalized experiences at scale.
Some tips and examples used in this case are:
1. Data collection
With AI, it is possible to collect data about customers from various sources, as well as having access to purchase history, previous interactions and stated preferences, online behavior and even demographic data.
This is the type of information that is essential to understanding your consumer and providing personalized recommendations.
2. Data analysis
AI is capable of analyzing large data sets to identify patterns, trends, and relevant insights.
Machine learning and data mining algorithms can be applied to discover correlations between different variables and segment customers into groups based on similar characteristics.
3. Personalized recommendations
Nothing new here, but it is important to note that yes, AI can generate personalized vietnam phone number example recommendations for customers. On an e-commerce website, for example, it is possible to receive product suggestions based on the customer's purchase history, the preferences of other similar customers, and market trends.
Something already extremely common.
4. Chatbots and virtual assistants
AI can be used to develop chatbots and virtual assistants that interact with customers in a personalized way. These systems can answer questions, provide relevant information, help with product selection, and resolve issues, all based on customers’ individual preferences and needs.
5. Content personalization
AI can be used to personalize the content presented to customers.
Based on customer data, it's easy to adapt visual elements, marketing messages, and website layout to suit individual preferences.
6. Marketing automation
With this technology, marketing campaign automation can become highly personalized, whether it's sending simple emails or even targeted messages and ads with relevant content, at the right time, increasing the chances of engagement and conversion.
Read also: Artificial Intelligence Marketing: 6 examples to apply in your business
7. Customer behavior prediction
With it, predictive analysis techniques can predict future customer behavior.
All of this is pulled from interaction history and demographic data, making it simple (for AI) to identify patterns that indicate the likelihood of a customer making a purchase, canceling a service, or engaging in other relevant actions.
However, although it is “easy to access” - and precisely for that reason - it is important to keep in mind that its use requires a well-defined strategy and the guarantee of compliance with data privacy laws and regulations, such as the LGPD.
Transparency and customer consent are also key to building trust and successfully implementing AI hyper-personalization.
Brands that already use AI in hyper-personalization
Banking institution
With the consultancy support of MATH Marketing , a bank specialized in granting credit and services to medium and large companies, it used AI models for the hyper-personalization front, which are already used as a way to obtain consumer preference.
The idea is to help the channels area understand the customer experience by mapping the user journey, as well as tagging, collecting and visualizing data.
With MATH 's expertise , indicators have already been used to carry out this monitoring, such as:
Error rate;
Success rate (micro flow conversion);
Fee for using Internet Banking for Companies (IBPJ) features.
In this context, it was already possible to map 100% of the flows, have more than 550 tags mapped and more than 380 tags implemented.
Netflix
Although this time the case was not mapped by MATH, Netflix also adopted AI to improve its hyper-personalization strategies, for personalized recommendations of series and films.
Amazon
Another brand that uses personalized recommendations on its website is Amazon, which, based on purchase history, website navigation, reviews and preferences of other customers, creates a recommendation of highly relevant products for each user.
In addition to these, several other relevant brands in the market are looking for the current alternative that is AI and its technology to collaborate with the growth and professional maturity necessary for a highly competitive market such as the digital one.
For support, to change routes and create alternatives with AI, contact MATH. We will know how to help you!