Supercharging Your Optimization Practice With Satellite

“Can we run 8-10 optimization campaigns concurrently?”   It seems most executives must have attended the same optimization maturity workshop, as I’m often being approached by organizations, both large and small, to help them mature their optimization practices to a point where they are consistently running 8-10 optimization campaigns concurrently.   What I have discovered is that most organizations are getting bogged down doing ad-hoc testing and are struggling to reach a point in their maturity where they have the ability to run several campaigns concurrently that are based on clearly defined goals. Part of this lack of maturity comes down to simply not putting in the work — At times it’s just too damn difficult to get the technology deployed.   This technical hurdle is especially prevalent with the optimization market-leader, Adobe Test&Target, due to the solution requiring Marketing Boxes (mBoxes) be deployed around specific test content. NOTE: This hurdle can be overcome using a Global mBox Strategy however this strategy isn’t necessarily the best approach for organizations in the early part of the optimization maturity curve.   Tag Management Systems (TMS) brought hope to many organizations struggling with the complexity of optimization platforms however that hope was short-lived as it quickly became evident that most TMS were conceived to, as the name suggests, manage “tags.” The problem is that analytics & optimization isn’t a “tag,” they are business assets, and managing optimization “tags” through a TMS just introduced more complexities — TMS weren’t solving the problem, they were creating new ones.   As I began experimenting with Satellite, I could tell that this platform was different. Satellite...

Build a Simple Heatmap Using R

Heatmaps have historically been given a bad name in the web analytics industry but they can be a powerful tool for data visualization.   noun ˈhētmap   1 a : A heat map is a graphical representation of data where the individual values contained in a matrix are represented as colors.   In this blog post, I’m going to show you how easy it is to create a simple heatmap using R.   NOTE: This tutorial assumes you already have R installed. We will also be using RStudio in this example.     1. Import Your Dataset The data for this example are the total player stats to date (current as of 2.5.2013) for the Utah Jazz. The data is already prepared for import and is available here.   Load the data into R using read.csv:  ...