Master Data Management and Why Graphs Matter

In order to keep pace with customers' buying patterns, companies need more efficient and intuitive tools for master data management.

Fri Oct 16 15:42:00 EDT 2015

Typically, whenever you read someone talking about shifting paradigms or the need for changing business models in their industry, they speak in the future tense – “times are changing,” as if players in that industry still have time to prepare and change accordingly. But, when we think about the business-customer relationship today, it’s pretty clear that the paradigm isn’t shifting, but rather it has already shifted and companies that don’t move with it will get left behind.

Nowhere is this more evident than in the customer journey. When you consider today’s customers are more than halfway through their purchasing decision by the time they even approach a supplier, it’s clear that the average customer is coming to you more than informed than ever before. So naturally, businesses have to be able to match them.

Upending Master Data Management Solutions

This means consolidating and interpreting data more efficiently and intuitively than many companies might be used to. In the old way of doing things, managing customer data often resulted in silos of information, where product data, campaign data, purchasing histories and other pertinent details about customer behavior would be stored separately from one another, based on department or team.

This was fine for when it was easier for companies to proactively approach customers that hadn’t started their purchasing journey yet. But, now that customers are doing their due diligence first – and will often drop in and out of that journey at different points – these data silos end up hurting rather than helping.

Fortunately, businesses are increasingly catching on to the fact that if they don’t update their master data management (MDM) solutions – moving beyond the traditional static customer key management approach to a holistic view that captures, manages and discovers complex and often hidden customer relationships across systems of records, insights and interactions for better context – then their customer-focused campaigns will fumble out of the gate and end up failing. Unfortunately, tried-and-true MDM solutions built on relational databases have shown that they are simply too limited in how they can collect and consolidate these disparate groups of data, unable to rapidly evolve their underlying data models to reflect this new reality.

The Role That Graphs Play

But that’s where graphs come in. Unlike relational databases, which struggle with retrieving and joining together highly connected customer data records, graphs utilize index-free adjacency to intuitively chart and combine different data domains.

Not only does this break down silos to pull together once-separate data groups into a single visualized model, it also helps to reinforce the business’ understanding of the varying relationships between customers, their social networks, their purchasing patterns and so on.

Are you interested in learning more about how knowledge graphs are essential to successfully accommodating the modern customer journey? Read more about “Using Knowledge Graphs to Unlock Customer Data.”

To learn more about how Pitney Bowes can help your business make the most of its customer information, join the Information Management webinar “Graph-based MDM: Why relational DBMS aren't relational enough” on April 25th at 2pm ET. Register here