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I was talking with Kelly Wortham during her excellent AB Testing webinar series. During the conversation, one of the attendees asked if they just wanted to pick between A and B, did they really need to run standard significance tests…
The key idea behind Conductrics is that marketing optimization is really a reinforcement learning problem, a class of machine learning problem, rather than an AB testing problem. Framing optimization as a reinforcement learning problem allowed us to provide, from the very beginning, not just AB and…
UPDATED: 5/20/2021
A version of this post was originally published over at Conversion XL
For all of the talk about how awesome (and big, don’t forget big) Big data is, one of the favorite tools in the conversion optimization toolkit, AB Testing,…
Personalization, one to one, predictive targeting, whatever you call it. Serving the optimal digital experience for each customer is often touted as the pinnacle of digital marketing efficacy. But if predictive targeting is so great, why isn’t everyone doing it…
Normally, when we talk about AB Tests (standard or Bandit style), we tend to focus on things like the different test options, the reporting, the significance levels, etc. However, once we start implementing tests, especially at scale, it becomes clear…
(Updated: Aug 2020)
Whether you are in a large company running marketing campaigns, or in digital analytics, or a data scientist at a tech startup, you probably are on board with the importance of analytical decision-making. Go to any related conference,…
Every now and then I get asked for some help or for some pointers on a machine learning/data science topic. I tend respond with links to resources by folks that I consider to be experts in the topic area. Over…
Right now online advertisers and marketers have a lot of interest in attribution analysis. Marketers are struggling to determine the impact of each individual campaign, across various channels, that make up their online marketing efforts. While they can discern the…