Share this content

Digging through data: Four things that graph databases can teach marketers

10th Nov 2014
Share this content

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. It’s like building a Facebook where everyone just writes their details on a sheet of paper - it’s the network of connections between those records that really creates the insight and value.

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.

Here are four key things that graph databases can teach marketers:

1. 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. It’s possible to even match the customer to others that are similar both in their social network and in buying patterns to gain better understanding. 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. Amazon is a perfect example of this and companies including Walmart are using graph databases in this very way to make instant product recommendations.

Though retailers are leading the charge here, all sorts of brands stand to benefit from understanding what to offer customers next, based on their past purchases.

2. 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. Whether it’s offering free products and trials or just targeting communications via the channels they use most to enhance loyalty, build rapport and encourage them to spread the word.

3. How to be the first to deliver

We all know long waiting times for products and issues with deliveries can be a huge frustration. Graph databases’ unique properties can help solve this recurrent pain point and achieve real brand differentiation in doing so.

London-based company Shutl is using graph databases to determine the quickest possible way to deliver an item from sellers to buyer in real-time. When planning routes on its previous, relational database it could take several minutes to crunch the data – now it takes a second, and gives up to fifty different scheduling choices. Now, acquired by eBay, the company can deliver within 90 minutes of placing an order. 

4. 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.

Telenor, one of the world’s largest mobile operators, is one such organisation to benefit from this technology. With over three million mobile subscribers, keeping track of customers, their service plans and supporting the online self-service management portal was a serious challenge.

Using a graph database, Telenor is now able to navigate through vast amounts of data by asking it specific customer-related questions, which has improved performance and reduced query and response times from minutes to seconds (and in some cases, milliseconds). With customers increasingly after instant and seamless services, the quicker businesses are able to respond the better.

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 techy area is actually one that can manifest in the most old-fashioned marketing advantage of them all: happier, more loyal customers.

Claudia Remlinger is marketing director, EMEA at Neo4J.

Replies (0)

Please login or register to join the discussion.

There are currently no replies, be the first to post a reply.