Rethinking Buyer Behavior Algorithms

By: Katana Graph

July 29, 2022

Rethinking Buyer Behavior Algorithms

To standard traffic analyzers, one click is as good as another. Our impulse purchases and our most prized procurements are all weighted equally by the algorithms through which vendors characterize us as consumers. We still see advertisements for now-shelved quarantine hobbies as we scroll through our daily news because click-counting and similar metrics have failed to reliably predict our actual interest levels.

Buyers’ interests are not necessarily represented by the frequency with which they browse products, and standard tools used to determine buyer preferences cannot discern when a touchpoint is erroneous. An Ometria Consumer Census reports that 70% of consumers are annoyed by receiving algorithmic recommendations that are not of interest. Targeted advertising both uses and generates data events that are unrepresentative of a consumer’s real interests and preferences.

Creating realistic behavior models to determine how a company can best meet the expectations of their customers is an increasingly challenging process, requiring data points from multiple sources and devices. Market pulse studies show that most marketers pull data from an average of four hundred sources to perform their analyses and gauge customer engagement levels. However, if a prediction is derived from incomplete or erroneous data, it results in suboptimal guidance.

Leveraging all available data is the most effective way for a company to advance its market position. By understanding both customers and competitors, a company can more easily determine the best way to distinguish itself from the pack and gain consumer loyalty. A comprehensive data pipeline directly influences a business’s opportunities and sales pipeline. The Katana Graph intelligence platform has the capability to process heterogeneous data, opening the floodgates of stagnant data lakes to enable insight without the challenge of producing refactored datasets for analysis.

Data continues to be produced at alarming rates (data volume now grows at 20% annually, says Statistica), complicating the challenge of pulling meaningful knowledge from what seems to be an overwhelmingly unorganized collection of data. Katana Graph strives to make business intelligence faster and more comprehensive with applications providing a 360° view of the customer. By drawing on advances in high-performance parallel computing, Katana Graph provides a graph data platform that pulls customer insights from the world’s largest data sources.

Graphs are the least amount of structure that can be imposed on a collection of data before a user can begin to understand it, and graphs allow the user to find connections between almost any two entities as well as attribute weights or modifiers to the entities and their relationships. For example, recommendation systems used by platforms like Netflix and Amazon are based on graph technology with users, attributes, and click-throughs serving to either explicitly or implicitly connect entities.

Deriving consumer interests, preferences, and concerns from buying and browsing behavior combined with unrelated user data has transformed into a complex network requiring tremendous computational power to penetrate. The five primary consumer concerns — access, price, product, service, and experience — have historically been viewed as distinct from one another, but seeing the relationships between them is critical to growth. Using graph technology to understand how these five aspects are intertwined and intrinsically connected lets sellers create environments, both physical and digital, that consumers want to participate in.

Powerful graph algorithms designed to navigate these intricacies typically require significant resources to perform and are often outside the reach of most retailers. Katana strives to provide a graph platform that can execute these algorithms at speeds previously limited to the high-performance computing field. Rather than implementing bulldozer techniques that process data with brute force, Katana focuses instead on optimizing resources and streamlining internal processes to get answers on an actionable timeline.

In today’s fast-paced and dynamic environments, there is an increasing demand for receiving answers in time to exploit a window of opportunity before it passes. Fast answers from unstructured data are just one of Katana Graph’s capabilities.

Katana Graph was born of cutting-edge research and scientific rigor, and these beginnings have a powerful effect on who we are to this day. We’re devoted to problem solving, and are relentless in our pursuit of more effective and more efficient solutions to real-world challenges. Continuous improvement is the very foundation of our success.

Whether structured or unstructured data, Katana Graph can greatly improve the insights and opportunities uncovered from your organization’s data. Click to schedule a meeting.


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