Quick Glance at the Algorithm-Making Craft

So, we already talked about the use of Applied Mathematics in digital advertising. We touched on the subject how algorithms associated with the programmatic media buying help us engage in a more meaningful and profitable way with our consumers. With this article we are going to bring you a step closer to what algorithms are made of. Ever wondered that? Well, here are some of the components of our algorithm-making process (let’s start with the more familiar ones):


Machine Learning

There are two key things you need to remember about Machine Learning. One, it is a core subarea of Artificial Intelligence. Two - “learning”. It is the field that explores the construction of algorithms. Its main goal is to devise them to learn automatically, without human intervention or assistance, how to make predictions or decisions based on given data. Starting to sound familiar yet?

In advertising Machine Learning is what makes the buzzword “data-driven decisions” possible. Its algorithms are the ones which do the Big Data analyses, which extract meaningful information and collect it in consumer behaviour profiles, which build audience segmentation profiles, which improve your advertising buying by determining the optimal bid price, and so on and so forth. You might easily say that Machine Learning is in the very heart of the programmatic idea of “right message to the right person at the right time”.


Reinforcement Learning

Another one you’ll hear often. Reinforcement learning is actually an area of the Machine Learning field. Here, instead of being explicitly taught, the algorithm learns by itself to determine the best course of action to maximize its performance. The decision is normally taken on the basis of past experiences and new choices calculation - this is the infamous balance between exploitation (past experiences) and exploration (new choices).

In advertising Reinforcement Learning is of particular importance for the A.I. Campaign Optimization Engines. This is one of the magics behind the campaign optimization process - A.I. engines are able to explore the changing nature of the market and independently determine the ideal strategy that will bring you higher results.



No. Don’t run away. It’s pretty amazing. Statistics, as the definition goes, is the study of the collection, analysis, interpretation and organization of data. Nowadays this field is an area of particular interest and active research. Why? Because Statistics hold the key to how to analyze Big Data.

In advertising Big Data is the source of everything. It is the ocean that collects the entire information about the market dynamics, the consumers behaviour characteristics, the impact of our advertising efforts. Through statistics, we are able to slice through this bulk of information and categorize it into meaningful insights. Thus we are able to achieve better informed decisions and reach even higher performance.