How Graph Databases Make the Perfect Digital Match

At first glance the world of online dating seems like it would have little correlation with that of digital marketing – but dig a little deeper and you will see that there is much the latter can learn.

Online dating has turned traditional romance on its head. And it is a major success story. Online dating is estimated to be a £225 million business by 2019 in the UK alone, according to Minitel.

Match.com, eHarmony, Tinder, Zoosk to name but a few have one thing in common. They all use technology to make sophisticated recommendations to help members find the best matches. Just like B2B marketers they are looking to select the highest prospects.

Online dating sites excel at what they do because they are highly skilled at manipulating large sets of connected data so they can bring like-minded individuals together, at scale. Digital marketers can use the same technology to make data work harder for them – data mining to find target consumers who are in a specific market and in search of a particular product or service.

The key to this is recommendations. All online dating businesses are founded on personalised recommendations, with the most accurate and successful using graph database technology to manage those algorithms. Graph databases differ from traditional (relational) business databases in that they specialise in identifying the relationships between very large numbers of data points, and so enabling users to work with large amounts of data far more efficiently and productively.

Standing out from the crowd

Graph databases are a core technology platform used by Internet giants like Amazon and Netflix. Amazon’s success is partly built on its ability to rapidly exploit connections between people and products, and flash up “Other people also bought” recommendations. Netflix digitally connects people and content together in such a smart way that it has carved itself a slice of the broadcasting media market.