Member Article

Graph Databases Will Help Meet the Personalisation Challenge

adidas Group is one of a growing number of signature brands using ’graph’ techniques to mine data relationships and offer customers a superior experience, explains database expert Emil Eifrem

To survive in our increasingly digital world, product and service providers need to offer the most personalised product and service recommendations possible to delight and engage with an increasingly demanding global customer.

To get there, brands need to understand each customer’s past purchase history, query that history then match the customer to the product or promotion that’s the closest match, based on their social media activity as much as previous buying patterns. Firms also need to instantly combine this knowledge with any interest shown during a visit to your branch, online shop or service centre.

And all this also needs to be done in milliseconds – as the next delight is only a click away.

It’s a tall order. What’s more, we know that firms that don’t meet these demands and which fail to offer this super-personalised experience to today’s customers will pay a penalty on Twitter.

However, there is hope on the horizon. Because although the challenge seem insuperable, technology help is available to make sense of these vast amounts of customer data. And all in real-time, too.

Step forward graph technology – something Web giants such as Google, LinkedIn et al, developed in-house at the end of the 90s, and which is acknowledged to have played a large role in these firms dramatic success.

However, graphs are no longer the preserve of these global corporations and the technology is now freely available commercially and in Open Source format.

Which means it’s giving all sorts of brands – ones just like yours – an invaluable leg-up in terms of making sense of all this data.

Creating the ultimate personalised experience

Graph databases are able to do a number of things better than the familiar relational database management systems that most organisations tend to use for most database tasks. For example, they are able to rapidly match historical data with live session data – as well as identify relationships between very large numbers of data points, and so help you work with social data better.

They are also very powerful when it comes to working at scale and with large datasets. A recommendation engine in a graph database can offer a staggering thousand times performance improvement, despite a thousand times increase in data size.

Large global retailers are starting to use graphs in response. The largest of them all, Walmart in the US, is implementing graph database technology to combine information from customer purchases at its physical and online stores in order to make real-time personalised recommendations, for example, while global sports and athletics giant adidas Group recently adopted the technology to offer enhanced features such as product recommendations to its audience.

In particular, unlike other online retailers that just offer static content on their website, the sports and equipment retailer wanted to personalise content based on user interests, local languages, regional sporting news and market-specific product offerings. That means its internal business users can categorise and search for user trend content across every platform and division of the enterprise, from sources ranging from marketing campaigns, product specifications, contracted athletes and associated teams to sports categories, gender information and more.

So whether it’s helping direct a fan to a great piece of their favourite team’s football merchandising, or making connections within a growing digital consumer data set, graphs are enabling adidas Group to deliver the super-personalised features to consumers we’ve been talking about.

One in four of us will be joining up the dots by 2017

You needn’t be a big global brand to introduce graph technology or as large as an adidas Group. Any UK enterprise can now do digital connections - work only a Facebook could do five years ago; analyst group Forrester Research estimates that in a little over a year’s time, one in four enterprises will be using the technology. Its peer Gartner predicts that for data-driven operations and decisions, graph databases are now “possibly the single most effective competitive differentiator”.

The attractions of a technology that can provide a 360-degree view of a customer in real time are clear.

Don’t ignore the power of graphs is the lesson, it seems – else you will be left holding the ball and your customers may have switched teams without you even noticing.

The author is co-founder and CEO of Neo Technology, the company behind the world’s leading graph database, Neo4j (http://neo4j.com/)

This was posted in Bdaily's Members' News section by Emil Eifrem .