Introduction
myAItesting was brought on to develop a personalized content experience for customers by using customer clusters and an AI vendor for content. The goal of the project was to increase engagement and satisfaction by providing relevant and timely content.
Methodology
The first step in the project was to use customer clusters to segment customers based on their behavior and preferences. This allowed us to understand the specific interests and needs of each customer cluster.
Next, we integrated an AI content provider that scraped the web for the most up-to-date sports content. The AI content provider used natural language processing and machine learning techniques to understand the relevance of each piece of content and how it aligned with the interests of each customer cluster. We also used recommendation algorithms like Collaborative Filtering, Content-Based Filtering, Hybrid Filtering to recommend the most relevant content to each customer based on their behavior and preferences.
We also integrated an analytics tool that would track the engagement of each customer with the content and their retention rate. This allowed us to continuously improve the content recommendations and overall customer experience.
Results & Conclusion
The analytics tool also helped us to understand which type of content the customers were more interested in, which helped us to create better-targeted content in the future. The results of this project demonstrate the power of using customer clusters and AI content providers to personalize the content experience. By understanding the specific interests and needs of each customer cluster and providing relevant and up-to-date content, we were able to increase engagement and satisfaction
