Blog
Documentation of Ad Ops, Stats and Marketing Processes
Out of Home Advertising Research with Python
Photo by Terabass from wikimedia Almost everyone is familiar with the phrase "location, location, location" when evaluating a property. Being mindful of location when purchasing out of home advertising placements is key to running successful outdoor campaigns. Python...
Short Term Directional Equity Forecasting with SVMs and R
This post outlines a framework for forecasting short term (i.e. daily tick data) directional movements of equity prices. The method used here relies on support vector machines and treats the system like a Markov Chain. Historical data is downloaded from stooq.com....
Google DV360 – Audience and Geography Targeting at Scale with Python
The Google DV360 platform is making great strides in its feature set and usability. The platform allows many bulk actions to be performed via the user interface, however, targeting unique audiences and geographies is still a very manual process. This code aims is to...
Multiple Variant Testing with R
This post overviews code for testing multiple variants using Bayesian statistics. It is especially useful when there is a defined action that can be classified as a success (i.e. a click or conversion) and when we have complete information about the number of trials...
Polynomial Regression for Digital Ads with R
This post discusses how to use polynomial regression for digital advertising data. Polynomial regression can help us better understand the relationship between spend and impressions (or spend and clicks). This method can be particularly useful when looking at daily...
Analyzing Page Relations With Google Analytics and R
This post outlines a method for analyzing how often pages appear together in user journeys on your website. To do so we utilize R and the Google Analytics API. You can find the full code on GitHub. We will rely on the dplyr, plyr, GoogleAnalyticsR, rio, RcppAlgos, and...