# How Data Scientists Use Causal Inference for Business Decisions Page: https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-use-causal-inference-for-business-decisions Text version: https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-use-causal-inference-for-business-decisions.md Podcast: [The Data Science Podcast with Fexingo: Analytics, Machine Learning, and Data-Driven Conversations](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831) Published: 2026-07-15T20:50:36+00:00 Episode link: https://audio.fexingo.com/business/the-data-science-podcast/episode-0112.mp3 Audio file: https://audio.fexingo.com/business/the-data-science-podcast/episode-0112.mp3 Processing state: not_requested JSON: https://stenobird.com/v1/public/podcasts/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/episodes/how-data-scientists-use-causal-inference-for-business-decisions Duration seconds: 544 ## Resource Causal inference is transforming how companies move from correlation to causation. In this episode, Lucas and Luna unpack a concrete example: how a major retailer used double machine learning to determine whether their loyalty program actually drove repeat purchases, or if members were just higher-spending customers to begin with. They walk through the core idea of conditional average treatment effects (CATE), why randomized A/B tests aren't always feasible, and how methods like causal forests and instrumental variables help data scientists answer 'what would have happened?' The hosts also discuss the pitfalls of relying on observational data and how modern tooling (DoWhy, EconML) makes causal analysis more accessible. By the end, you'll understand why causality is the next frontier for data-driven decision-making, and how one simple question—'Did X cause Y?'—can save companies millions. #CausalInference #DataScience #MachineLearning #CausalML #DoubleML #CausalForests #InstrumentalVariables #DoWhy #EconML #TreatmentEffects #ObservationalData #LoyaltyPrograms #RetailAnalytics #BusinessDecisions #Technology #FexingoBusiness #BusinessPodcast #TheDataSciencePodcast Keep every episode free: buymeacoffee.com/fexingo ## Actions - request_transcript: `POST https://stenobird.com/v1/public/podcasts/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/episodes/how-data-scientists-use-causal-inference-for-business-decisions/transcription-requests` — Idempotently request low-priority transcript generation for this episode. - read_markdown: `GET https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-use-causal-inference-for-business-decisions.md` — Read the agent-friendly Markdown representation of this episode resource. A page view does not enqueue transcription. Agents should invoke `request_transcript` explicitly when they need this episode processed. ## Transcript Full transcripts are not published on public pages unless there is a clear rights basis.