Personalization Architectural Patterns
5683 Views 07 Dec, 2022
Personalization Architectural Patterns
5683 Views 01:05:24
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Description
As most consumer -related businesses involve both offline and online experiences, consumer data such as personal preferences, interests/wish-lists, purchase data, order-history, LTV, demographic, etc. are readily available. There is a need to process the data collected in a unified way, to be able to provide seamless personalized experiences across the touch points. Many Personalization strategies are in practice across industries, leading to the evolution of different Architectural patterns. Publicis Sapient has been a pioneer in this space and has delivered a number of impactful personalization use cases, over the years, leveraging architectural patterns designed and implemented by our engineers. This session gives insights into these patterns that leverage industry-leading off-the-shelf products, cloud native/serverless implementation and AI/ML to achieve hyper-personalization in real time.
About Publicis Sapient:
Publicis Sapient is a digital business transformation company. We partner with global organizations to help them create and sustain competitive advantage in a world that is increasingly digital. We operate through our expert SPEED capabilities: Strategy and Consulting, Product, Experience, Engineering and Data, which combined with our culture of curiosity and deep industry knowledge, enables us to deliver meaningful impact to our client's businesses through reimagining the products and experiences their customers truly value. Our agile, data-driven approach equips our client's businesses for change, making digital the core of how they think and what they do. Publicis Sapient is the digital business transformation hub of Publicis Groupe with 20,000 people and 53 offices worldwide. For more information, visit publicissapient.com
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Key points of discussion
- Overview of different types of personalization
- Get insights on the degree of personalization
- Get an understanding of different architectural patterns
- Typical data flows across different systems
- Points to consider while choosing patterns for any of the business use cases
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