Analytics Software

How Knowledge Graphs Drive Better Customer Information Strategies

We live in revolutionary times when it comes to how individuals understand and contextualize knowledge. In recent years, knowledge graphs have transformed search as we know it, modeling the complex relationships between the facts and ideas that people access on search engines every day. In an increasingly networked knowledge society, the same technology has the potential to transform more than just search. Knowledge graphs can drive more insightful customer information management strategies, allowing business leaders to create a multi-dimensional view of each customer and leverage customer information to drive revenue across a range of industries.

Historically, businesses have built CRM and MDM systems on incredibly rigid, traditional models. They lacked agility and were slow to adapt to changing business dynamics, but they more or less passed muster. These days, we’re living at the edge of a new frontier. The business that treats its enormous amounts of transactional and social customer data as an asset is the business that will thrive. Unlike traditional data management systems, knowledge graphs can help contextualize and link these new sources of unstructured and semi-structured data-sets, and help businesses make sense of them.

For example, marketing and sales professionals at a global retailer could use an individual customer view built by a knowledge graph to create a highly tailored approach, and act with greater insight based on customer location, social network, product preferences, brand sentiment and purchasing power. When connecting with Customer A, a mother of two in her thirties interested in home décor with an annual household income of over $150,000, the retailer would be empowered to speak to her in the casual tone of voice she prefers, and with the knowledge that she engages most with brands on her smartphone, between nine and eleven in the morning, once the kids are at school. They would understand not just her past purchase history, but also her spending power, and where she is likely to flex it next. With this information, the retailer would be able to build outreach that drives trust between customer and brand, ensuring that every action they take to engage the customer is highly personalized to her tastes and lifestyle.

A knowledge graph would allow those same retail professionals to judge that Customer A’s sphere of influence across her social and professional networks, including friends from her hometown, her family network, and other mothers she has connected with more recently, makes her an especially relevant, powerful customer. By powering a customer information management strategy with knowledge graphs, the retailer would be able to weigh each customer’s value as a connection and ultimately drive the cost effectiveness of every action.

But the power of knowledge graphs doesn’t just stop with sales and marketing. The ease of use characterizing knowledge graph technology makes customer information accessible across multiple touch points, allowing every business stakeholder to look at a customer’s information from a relevant perspective. This agility allows them to bypass the more cumbersome process of extracting, transforming and loading data into rigid, non-conforming data models of the past, requiring months of effort, and instead making the business more responsive to quickly changing and constantly evolving customer information dynamics. Executives at that same global retailer working beyond sales and marketing would be able to access the very same knowledge graph as their colleagues, but they would be able to view Customer A’s full profile from the perspective that’s most valuable to them.

Knowledge graphs offer an incredible opportunity for businesses to enhance their customer information management strategies in our new, data-driven age through the creation of accessible, multi-dimensional and contextualized customer views, much the same way an average consumer now has access to a wealth of timely and relevant information with a click of a button. Knowledge graphs deployed to model customer data can help businesses create personalized brand experiences that deepen relationships, and give executives the tools they need to reduce churn and drive acquisition of new customers. By unlocking the true value of customer information with a knowledge graph, a business can turn an overwhelming deluge of customer data into a game-changing asset. More importantly, businesses can stop annoying their customers and differentiate themselves from their peers by driving the right customer experience.


Navin Sharma is Global Portfolio Director for Data Management Solutions at Pitney Bowes


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Navin Sharma

Navin Sharma is Global Portfolio Director for Data Management Solutions at Pitney Bowes

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