Quander Brings Consumer Data to Life for Big-Brand Clients Experimenting with New Immersive Digital Experiences
Quander’s people combine event production, retail experience and bleeding-edge technology for the benefit of brands like Sky, YouTube and Samsung that want to engage with customers more creatively out in the real world. Two important features of Quander’s proposition: that the consumer experiences it creates have the “wow” factor, and that the resulting interactions generates valuable data brands need to maximize future engagement.
As well as impressing its clients with advanced consumer experiences – from 4D virtual reality event check-in to state-of-the-art digital signage – Quander needs to powerfully illustrate what impact those experiences are having and how brands can improve on them. Previously, Quander used a traditional relational database management system to store consumer data, but this didn’t do justice to the emerging insights and it was difficult to bring this to life for clients. “We needed a new way to store information that was easier to access and easier to analyze,” Williams said.
Quander quickly discounted a NoSQL database. Although this option offered the ability to store unstructured data, it couldn’t easily represent data relationships. It was only when the team started searching for something compatible with Quander’s existing GraphQL-based API that Quander came across graph database technology. “We needed a data store that was a natural fit for the front-end – and there it was,” Williams said.
When he read about Neo4j, Williams knew he had found the answer. “We were taken aback by the ability to visualize the data we were storing, and the relationships between different data points,” he continues. “It would transform our own analyses and we’d be able to show our clients the richness of the data, and the kinds of queries we could perform in the future.”
Whatever the digital brand experience, Quander captures a lot of detail about the features consumers engage with most, so its clients keep improving results. “With a graph database, you get a lot of that data automatically, for free,” Williams said. “With a traditional relational database, there would be a lot of development work to achieve the same thing.”