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Business, Product, and Marketing Analytics Introduction

Business, Product, and Marketing Analytics

Introduction

Analytics becomes most valuable when it is tied to a real business decision. Different teams use similar methods but have different goals and metrics:

Team

Typical goal

Example metrics

SalesGrow revenue profitablyRevenue, AOV, win rate, margin
MarketingAcquire valuable customers efficientlyCAC, conversion rate, ROAS
ProductHelp users succeed with the productActivation, retention, feature adoption
OperationsDeliver reliably and efficientlyDelivery time, backlog, error rate, SLA
Customer successKeep customers happyChurn, NPS, resolution time

This module applies analytical thinking to revenue, retention, marketing funnels, product journeys, and operational efficiency. You will learn to define metrics clearly and avoid treating a single number as the whole story.

What you will learn in this module

  • How to analyse sales, revenue, and customer segments
  • How to calculate retention and churn in context
  • How to measure marketing funnel performance
  • How to use product metrics to find friction in a user journey
  • How to connect operational metrics to an actionable decision

Data Analytics Tutorial



Learn via Video Course

Data Analysis and Processing with Python using Pandas - Data Science Course Logo

Data Analysis and Processing with Python using Pandas - Data Science Course

5 hrs



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