# How to Use Quasi-experiments and Counterfactuals to Build Great Products

DevFeed: [How to Use Quasi-experiments and Counterfactuals to Build Great Products](<https://devfeed.tech/articles/how-to-use-quasi-experiments-and-counterfactuals-to-build-great-products-1668.md>)

Original publisher: [Read original article](<https://shopify.engineering/using-quasi-experiments-counterfactuals>)

Author: Antoine Rebecq

Published: 2020-09-28T18:29:06Z

Content type: article

Language: en

Sources: [Shopify Engineering](<https://devfeed.tech/sources/shopify-engineering.md>), [Shopify Engineering - Shopify Engineering](<https://devfeed.tech/sources/shopify-engineering-shopify-engineering.md>)

Topics: [Statistics](<https://devfeed.tech/topics/statistics.md>), [Data Science](<https://devfeed.tech/topics/data-science.md>), [Shopify](<https://devfeed.tech/topics/shopify.md>)

Tags: [analysis](<https://devfeed.tech/tags/analysis.md>), [causal-inference](<https://devfeed.tech/tags/causal-inference.md>), [experiments](<https://devfeed.tech/tags/experiments.md>), [statistics](<https://devfeed.tech/tags/statistics.md>)

## AI overview

The Shopify Engineering article explains how A/B tests, quasi-experiments, and counterfactual estimation provide different levels of evidence for causal inference. It emphasizes that stronger causal conclusions require either sound experimental design or substantial statistical analysis and robustness checks.

## Source excerpt

A/B tests are not the only tool to understand causality: quasi-experiments and counterfactuals are powerful tools for causal inference if used right.