Uncovering hidden ecommerce, marketing gems through knowledge graphs
Article by Neo4j APAC VP of Marketing, Daniel Ng.
Marketers have access to more data than ever before – and it’s growing exponentially. The pandemic-driven acceleration in digitisation has created vast repositories of data around consumers, products and purchases. According to Statista, global data creation – the total amount of data created, captured, copied, and consumed – is projected to grow to more than 180 zettabytes by 2025 globally.
The challenge is how to sift through it and identify the trends and patterns that can be used to generate valuable insights. As a massive stream of data, it has little to no value to marketers without context and relevance. How can marketers transform realms of information and make data meaningful and useful?
The power of knowledge graphs
In today’s data-rich world, marketers can convert data into greater marketing intelligence through knowledge graphs. Unlike a traditional database in table form, with rows and columns of data, knowledge graphs store data as linked nodes and the relationships between them. This data can then be displayed visually, as colours and shapes, making it easy to detect patterns and anomalies.
For example, in an Excel spreadsheet you can fairly easily log one data set (customers) against another (their purchase history). But trying to add in additional context such as demographic information, the path to purchase, time and date of purchase, and weather patterns in a locality is difficult, unwieldy, and impossible to do in a single sheet. However, this context can be critical for spotting patterns of who buys what, when, and how.
Knowledge graphs are designed to uncover insights into customer needs, product, and market trends, alleviating the challenges of continually growing, highly interconnected datasets. They excel in connecting and managing masses of buyer and product data to answer complex queries.
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