How Uber Saved $35M on Ads скачать в хорошем качестве

How Uber Saved $35M on Ads

How do you save $35 million in ad spend without hurting growth? In this episode of Marketing Measurement Matters, we sit down with Sundar Swaminathan, former Global Head of Brand Data Science at Uber, to unpack the real story behind one of the boldest measurement decisions in tech: turning off Meta performance ads in the U.S. and Canada after discovering they were nearly non-incremental. If you’re in marketing analytics, MMM, MTA, or data strategy, this is a masterclass in measurement leadership, data culture, and operational courage. Highlights: 00:00-05:25 – Intro & Sundar’s background 05:26-07:30 – SQL vs. Python: The underrated stack 07:31-10:05 – Sundar’s first experience with incrementality & MMM 10:06-17:00 – The $35M ad cut: context, test design & what happened 17:01-22:00 – What the Uber team did after the test 22:01-26:00 – Why most teams fail to act on insights 26:01-31:00 – Saturation, retention, and making hard calls 31:01-34:00 – Why mobility and marketing data people go freelance 🙃 34:01-35:54 – Curious culture vs black-box vendors