Customer Data Analytics for Marketers

Coursera Courses ↗ · Coursera

Open Course on Coursera

Free to audit · Opens on Coursera

Customer Data Analytics for Marketers

Coursera · Beginner ·📊 Data Analytics & Business Intelligence ·1mo ago
This course introduces marketing data analytics, focusing on the crucial concepts of correlation and causality. Learners will explore statistical concepts and tools to analyze and interpret marketing data, leading to more informed and impactful marketing strategies. The course begins with core statistical concepts, such as standard deviation, variance, and normal distributions, in the context of marketing decisions. It shows how to visualize correlations and causal networks using techniques such as Structural Equation Modeling (SEM) and Path Analysis. The course discussions of analytics ethics, guiding participants to identify and avoid common pitfalls in data interpretation. This course is an invaluable resource for anyone looking to enhance their marketing strategies through trustworthy data-driven insights.
Watch on Coursera ↗ (saves to browser)
Sign in to unlock AI tutor explanation · ⚡30

Related AI Lessons

Modern businesses Data Analytics vs Data Science: Which Strategy Actually Drives Business Growth in…
Learn the difference between Data Analytics and Data Science to drive business growth
Medium · Data Science
Python for Data Science — Handling Missing Values in Pandas
Learn to handle missing values in Pandas for effective data science, a crucial skill for any data scientist
Medium · Programming
Roblox Data Engineering Interview Questions: Full DE Prep Guide
Prepare for Roblox data engineering interviews with a focus on text-heavy product telemetry and search-related questions
Dev.to · Gowtham Potureddi
Tesla Data Engineering Interview Questions: Full DE Prep Guide
Prepare for Tesla data engineering interviews with this comprehensive guide, covering key concepts and practice questions to help you succeed
Dev.to · Gowtham Potureddi
Up next
How Suntory Turns Data into Faster Decisions with Databricks
Databricks
Watch →