Author Archives: Matt Gershoff
Predictive Targeting: Managing Complexity
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 right now? The reason is that while targeting can be incredibility valuable, many in […]
Posted in Analytics, Testing and Data Science, Uncategorized
3 Comments
Big Data is Really About the Very Small
Awhile back I put together a fun list of the top 7 data scientists before there was Data Science. I got some great feedback on others that should be on the list (Tukey, Hopper, and even Florence Nightingale). In hindsight I probably should have also included Edgar Codd. While at IBM, Codd developed the relational […]
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AB Testing: When Tests Collide
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 that we need a way to manage how we assign users to each test. There […]
Posted in Analytics, Reporting, Testing and Data Science
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The World’s Top 7 Data Scientists before there was Data Science
I am often a bit late to the party and only recently saw Tim O’Reilly’s “The Worlds’ 7 most powerful Data Scientists”. As data science has become a big deal, there have been a several top data science lists that have been floating around. So for fun, I thought I would put together my own […]
Posted in Testing and Data Science, Uncategorized
10 Comments
Big Data or Big Distraction
Contrary to what you have heard, the unfolding technological transformation we are witnessing isn’t really about data, not directly at any rate. It’s not that data isn’t important, but the focus on data is obscuring the real nature of change, which is the transition from a world driven by essentially static and reactive systems to […]
Intelligent Agents: AB Testing, User Targeting, and Machine Learning
(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, blog, meet up, industry slack and you will hear many of the following terms: […]
List of Machine Learning and Data Science Resources – Part 2
This is a follow up to a post to the list of Machine Learning and Data Sciences resources I put up a little while ago. This post contains some links to resources on clustering and Reinforcement Learning that I didn’t get to in the first post. Like the first one, it’s a bit haphazard, and […]
Posted in Testing and Data Science
1 Comment
A List of Data Science and Machine Learning Resources
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 time my list has gotten a little larger so I decided to put it all […]
Posted in Analytics, Testing and Data Science, Uncategorized
7 Comments
Decision Attribution for Multi-Touch Optimization
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 aggregate effects, it is much more difficult to disentangle the individual effectiveness from any given […]
Conductrics’ Confidence and Lift Report – The Basics
While enabling Conductrics’ adaptive testing is a powerful way to auto-optimize your app, there are times when you might want to run non-adaptive tests. Maybe you want to test something that you will apply in other media, or perhaps you want to do online research on your customers, to give you additional insights into their […]
Posted in Analytics, Conductrics API, Reporting, Testing and Data Science, Uncategorized
Tagged Reporting
Leave a comment
Predictive Targeting: Managing Complexity
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 right now? The reason is that while targeting can be incredibility valuable, many in […]
Big Data is Really About the Very Small
Awhile back I put together a fun list of the top 7 data scientists before there was Data Science. I got some great feedback on others that should be on the list (Tukey, Hopper, and even Florence Nightingale). In hindsight I probably should have also included Edgar Codd. While at IBM, Codd developed the relational […]
AB Testing: When Tests Collide
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 that we need a way to manage how we assign users to each test. There […]
The World’s Top 7 Data Scientists before there was Data Science
I am often a bit late to the party and only recently saw Tim O’Reilly’s “The Worlds’ 7 most powerful Data Scientists”. As data science has become a big deal, there have been a several top data science lists that have been floating around. So for fun, I thought I would put together my own […]
Big Data or Big Distraction
Contrary to what you have heard, the unfolding technological transformation we are witnessing isn’t really about data, not directly at any rate. It’s not that data isn’t important, but the focus on data is obscuring the real nature of change, which is the transition from a world driven by essentially static and reactive systems to […]
Intelligent Agents: AB Testing, User Targeting, and Machine Learning
(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, blog, meet up, industry slack and you will hear many of the following terms: […]
List of Machine Learning and Data Science Resources – Part 2
This is a follow up to a post to the list of Machine Learning and Data Sciences resources I put up a little while ago. This post contains some links to resources on clustering and Reinforcement Learning that I didn’t get to in the first post. Like the first one, it’s a bit haphazard, and […]
A List of Data Science and Machine Learning Resources
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 time my list has gotten a little larger so I decided to put it all […]
Decision Attribution for Multi-Touch Optimization
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 aggregate effects, it is much more difficult to disentangle the individual effectiveness from any given […]
Conductrics’ Confidence and Lift Report – The Basics
While enabling Conductrics’ adaptive testing is a powerful way to auto-optimize your app, there are times when you might want to run non-adaptive tests. Maybe you want to test something that you will apply in other media, or perhaps you want to do online research on your customers, to give you additional insights into their […]