At Neo4j we believe that “Graphs Are Everywhere”. In this session, we’ll be exploring graphs within the Retail industry. We’ll discuss a range of data that are commonly available within a retail organisation, both online and “brick and mortar". We’ll illustrate some graphs which can be created by linking together different elements of that data and discuss the retail use cases those graphs can enable and transform.
We’ll specifically focus on use cases like Personalised Recommendations (with a live demo), Supply Chain Management, Logistics, and Customer 360. We'll also look at some relevant graph algorithms and talk about opportunities for integration with Artificial Intelligence/Machine Learning technologies, which can be used along with Neo4j to generate new value using retail data.
Walmart, Wobi, and others already deploy Neo4j for use cases like price comparison or real-time contextual and learning recommendation engines. Read about their use cases!