In an increasingly digital business environment, artificial intelligence (AI) and generative models have become essential allies in improving team productivity and creating more personalized experiences for customers. One of the most effective strategies in this area is the implementation of personalized communications, capable of increasing user engagement and conversion rates.
An exemplary case is that of a marketing manager at a video on demand company, who is interested in sending personalized emails to their users. These messages should consider not only demographic aspects such as gender and age, but also each customer’s viewing preferences. To achieve this, they can turn to Amazon Personalize, which facilitates the generation of movie recommendations tailored to each user, complemented by Amazon Bedrock for the email content writing.
Amazon Personalize allows companies to develop personalized product and content recommendations on their websites, applications, and marketing campaigns. This service is accessible even to those without prior machine learning experience, as it uses APIs to build complex customization capabilities, ensuring that data remains secure and is only used to generate specific recommendations.
On the other hand, Amazon Bedrock is a fully managed service that offers a variety of high-performance generative models, allowing users to experiment and evaluate different AI approaches. This tool not only simplifies the creation of generative applications, but also ensures security, privacy, and responsible use of artificial intelligence.
To illustrate the effectiveness of Amazon Personalize and Amazon Bedrock in generating personalized emails, a workflow has been designed that includes multiple stages. The process begins with importing user data and interactions into Amazon Personalize, followed by training a recommender, obtaining movie recommendations, and creating compelling messages based on these recommendations.
Although the process may seem complex, there are tutorials that guide users in setting up the necessary resources in Amazon Personalize. Through steps ranging from training a recommender to creating a dataset, a high degree of customization can be achieved that substantially improves the user experience.
The generation of personalized marketing emails is carried out by integrating these recommendations into templates designed to capture the customer’s attention. With accurate information about the recommended movies and an engaging narrative approach, companies are able to send messages that not only inform, but also make the user feel valued and understood.
As the field of artificial intelligence and generative models advances, companies have the opportunity to offer even more personalized and effective experiences, thus achieving greater user engagement and more positive business outcomes. The implementation of AWS-managed tools, such as Amazon Personalize and Amazon Bedrock, makes it easier for companies to leverage these innovations without the need for deep technical knowledge in the subject.
Source: MiMub in Spanish
