⏰️ Tracardi Office Hours 11 - Unlocking Personalised Experiences with Vector Databases
💡 Learn how intergrating a vector database with Tracardi can revolutionise customer experiences with personalised recommendations and intent analysis.
Top key takeaways from our ⏰️ Tracardi Office Hours conversation.
- Use case for vector databases - To show similarity between profiles.
- Use case for interest vectors - Store user interests as vectors, allowing for similarity analysis and personalised recommendations.
- New services opportunities - Creating interest vectors and intent analysis can lead to new service opportunities, such as predictive analytics and marketing automation.
- Reduce dimensionality - Vector databases can reduce the complexity of high-dimensional data, making it easier to identify patterns and clusters.
- How to use the vector database - Make an API call to store and query profile vectors, allowing for personalised recommendations.
Share your experiences and insights with us in the comments below!
Have you any questions or thoughts on getting started with or how you're currently using vector databases?
