Written by Claudia Remlinger, originally posted on DigitalMarketingmagazine.co.uk

We all know marketers are keener than ever to ‘put data at the heart of everything they do’ and better understand their customers. But what’s becoming equally apparent is how broad that phrase becomes when putting it into practice. Not all data is born equal — and the specific way you use it is key to how you’ll be able to create value from it.

This distinction comes back to the way technology has changed in recent years. As marketers, we have to accept that everything is connected. But traditionally this isn’t how we’ve stored and accessed data. Individual datum would sit alongside each other with absolutely no attention paid to the ways they fit together.

Graph databases fix this by being built fundamentally around exploring connectivity within the data. While more traditional relational databases can only answer simplistic questions such as, “what is the mean age of people shopping on Oxford Street?”, graph databases can identify complex relationships and enable queries like: “how many customers are talking about my brand on social media and how many of them know each other?” It may seem like semantics but it’s a huge leap for informed marketers. This leap requires thinking about and asking the right questions to get the best insights possible.

Three things graph databases can teach marketers:

    How to drive loyalty – offer products and services that customers want

      Looking at data collected from past purchases and customer interests and hobbies, marketers are able to spot patterns and make appropriate recommendations or tailor relevant offers to customers for next time. With a graph database you can go one step further to make real-time recommendations, as the technology allows you to instantly capture any new interests shown in the customers’ current visit.

    How to identify brand advocates

      By looking at your customers, their connections and social media activity you could quickly identify those that are most likely to speak about your brand and recommend services to others. For example, you could ask the following: “Which customers of mine are mentioning my brand on social media and via which channels?”, “which have most social influence amongst their networks and like to write reviews?” and correlate this with, “which of these digitally active customers are buying most of our products?” The answers are likely to provide the most appropriate individuals that you can engage with and nurture into brand advocates.

    How to provide quicker customer service

      In an age where global selling is the norm, many businesses now offer a huge range of products and services that vary from region to region – such sprawling product catalogues can be difficult for employees and customers to navigate whether online or in-store. Using a graph database can allow organisations to quickly identify and offer customers a product that is closest to their needs and react quickly when problems arise.
For too long, it has felt like getting to know your customers is almost made more difficult by the way companies manage master data – databases are vast and can be overly complex to navigate. Graph databases change this, building the importance of relationships into every piece of data and every query you make. It allows you to ask better questions as a marketer, generate better insights and, ultimately, serve your customers better using that knowledge.

What may sound like a tech-y area is actually one that can manifest in the most old-fashioned marketing advantage of them all: happier, more loyal customers.


Want to learn more about graph databases? Click below to get your free copy of O’Reilly’s Graph Databases ebook and discover how to use graph technologies for your application today.

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1 Comment

d roy says:

Why two condition are not working? Like:

MATCH (kenu:Person{name:”Kenu Reeves”}) -[:ACTED_IN]->(movie)(movie) WHERE actor < kenu RETURN DISTINCT actor.name

I need to find those actor who worked with Keanu But not with hugo and who are older than kenu?
Plz help me. i am very new to Neo4j

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