Matt Gershoff, Conductrics
Often in analytics and data science we have the 'big table' mental picture of customer data where we are continuously trying to append and link new bits of data back to each customer. It turns out, however, that for many of the statistics needed for tasks like AB Testing, if we are intentional about how the data is collected, then often there is no need to link all of this information back to a central visitor or customer ID. Most of the basic statistical approaches used for inference in AB Testing (t-tests, ANOVA, nested partial f-tests, etc.) can be done on data stored in equivalence classes, or at the task level, rather than at an individual level. The hope is that once armed with options, attendees will be able to consider the trade-offs and make informed decisions on when each approach is most appropriate.
Matt Gershoff, Conductrics
![](https://www.usenix.org/sites/default/files/styles/speaker_photo/public/gershoff_matt_200x230.jpg?itok=gwgDVYre)
Matt Gershoff is co-founder of Conductrics, a software company that offers integrated AB Testing, multi-armed Bandit, and customer research/survey software. While having been exposed to various 'advanced' approaches during MSc. degrees in both Resource Economics and Artificial Intelligence, Matt's bias is to try to squeeze as much value out of the simplest approach possible and to always be intentional about the marginal cost of complexity. "Just as the ability to devise simple but evocative models is the signature of the great scientist so over elaboration and overparameterization is often the mark of mediocrity." - George Box '76 Science and Statistics.
![](https://www.usenix.org/sites/all/modules/usenix/usenix_files/images/usenix-locked.png)
author = {Matt Gershoff},
title = {Being Intentional: {AB} Testing and Data Minimization},
year = {2024},
address = {Santa Clara, CA},
publisher = {USENIX Association},
month = jun
}