Minimizing Human Bias in Marketing Mix Models using Meta Open Source Robyn by Bernardo Lares & Igor Skokan Visit https://rstats.ai/nyr/ to learn more. Abstract: Robyn [https://facebookexperimental.github.io/Robyn/] is a semi-automated Marketing Mix Modelling (MMM) R package initially built by Meta’s Marketing Science team. It aims to reduce human bias by means of ridge regression and evolutionary algorithms, and allows ground-truth calibration to account for causation. In this talk we will focus on four specific main techniques for mitigating bias in model training and selection. Project Robyn, now in v.3.6+, being an open source and with the help of the international data science community keeps evolving a traditionally expensive and obfuscated modelling process, democratizing access to actionable MMM to a broader set of advertisers. Bio: Bernardo Lares is a Venezuelan Marketing Science Partner at Facebook, currently located in Colombia, passionate about data science, automation, data visualization, and R. He has mainly engaged in FinTech, Insurance, and Marketing projects, applying data science to real-world problems, and helping clients and consumers get the most out of the data available. Bernardo has an open-source R package called `lares` mainly designed to democratize AutoML with a plug-and-play approach to train Machine Learning models, ready to deploy. It also holds dozens of other functionalities to help analysts with their daily tasks. He likes to describe his package as a "shared side-kick that boosts your analytics." Currently, he is developing internal and external Marketing Science solutions at Facebook with R; one of the most impactful projects is Robyn, which helps empower mid-sized businesses to semi-automate their marketing mix models using open-source solutions. Bio: Igor [Iggy] is part of the global Marketing Science team at Facebook based in London, helping agencies and marketers find true business value through a range of solutions designed to measure audience, brand and sales outcomes. Nuclear scientist & mathematician by education, prior to joining Facebook, Igor held various senior analytical positions within Omnicom’s data, tech and analytics units in Dubai, London and Prague. Across his roles before and now, his focus is on intersection of different facets of marketing effectiveness from contemporary MMM, holistic attribution, RCTs/experimentation to media insights. Beyond his passion for numbers, he likes traveling, ultra-trail running and climbing (high) mountains. Twitter: https://twitter.com/LaresDJ Presented at the 2022 New York R Conference (June 9, 2022)