Kinetic's technology goal is, in simple terms, to leverage multiple large data sets in order to make social advertising more effective, and then integrate at the data stream level across the social sphere and the broader digital ecosystem. To accomplish this, there are three major challenges we've needed to master:
Sophisticated Optimization Based On Statistical Analysis
Our systems must optimizing across vast amounts of data and disparate data types - in other words, the "Big Data" challenge, where data is measured in petabytes. Simple optimization is not rocket science, but our approach is. Literally. Kinetic reengineered a statistical analysis approach used at NASA, the Department of Defense and the Department of Energy's nuclear management program. The result is our patent-pending Polynomial Network Analysis (PNA) process, which underpins our Optimization Engine, and relies upon a Multivariate Testing / "Design of Experiments" approach.
Any data optimization schema is only as good as the data which is fed into it. In addition to open-source/publically available data, Kinetic's data analysis solution leverages on our patent-pending "Popular Culture Database (PCdb)", which we use in part to map audience segments to social media targeting buckets. The PCdb is a custom home grown database that is generated from multiple sources, including curated data providing popular culture context. In addition to driving pure popular culture targeting, the PCdb is also designed to incorporate product and brand data so that it can also generate targeting suggestions in these areas that are highly relevant with the audience segment being targeted. More on the PCdb.
At Kinetic, we believe digital advertising can be characterized as occurring in a "multi-nodal" sequence between demand (advertising dollars) and supply (media inventory). While the sequence itself is relatively straightforward, managing this chain can be complex. We believe that our ability to optimize at the level of each individual node in the sequence, as well as across ALL nodes in the sequence, is critical to achieving superior performance in social advertising and digital marketing overall. More on Multi-Nodal Optimization.
Kinetic began building its integrated delivery platform when it was still a subsidiary of EMG/Connexus (see Kinetic Social's History). After several iterations that involved full tear-downs and re-writing / reengineering the code base, the platform as it exists today allows Kinetic to plug a predictive modeling capability into a delivery platform integrated into the major social media channels. There are actually two key interlinked pieces of our technology architecture: a statistical optimizer known as the "Kinetic Optimization Engine (KOE)"; and a delivery platform known as the "Kinetic Social Platform (KSP)". If the KSP is analogous to the body of an automobile, the KOE is its engine; both are required to make a car.
With platform extensions and new technology coming on line continuously -- most recently, our Content Discovery Tool -- Kinetic Social stays on and helps shape the bleeding edge of technology development in the digital marketing ecosystem.