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All lessons in Digital and Web Analytics Lesson 1.2 of 32

Module 1: Introduction to Digital Analytics

  1. 1.1What is digital analytics?
  2. 1.2The four types of analytics
  3. 1.3Connecting analytics to business objectives and KPIs

Module 2: Analytics Data and Measurement Planning

  1. 2.1How to build a measurement plan
  2. 2.2Key metrics for each marketing channel
  3. 2.3Data sources, collection, and data quality
  4. 2.4Segmentation and personalization

Module 3: Web Analytics Fundamentals

  1. 3.1Users, sessions, page views, and events
  2. 3.2Traffic sources, channels, and UTM parameters
  3. 3.3Landing pages and user behavior
  4. 3.4Engagement metrics and conversion metrics
  5. 3.5Reading reports, trends, and anomalies

Module 4: Analytics Tools and Platforms

  1. 4.1Google Analytics 4 fundamentals
  2. 4.2Google Search Console performance data
  3. 4.3Adobe Analytics overview
  4. 4.4Tag management and tracking implementation
  5. 4.5Connecting tools and choosing the right stack

Module 5: Conversion Funnels and Optimization

  1. 5.1What is a conversion?
  2. 5.2Conversion funnels and drop-off points
  3. 5.3How to calculate conversion rate
  4. 5.4Prioritizing conversion improvements
  5. 5.5Introduction to A/B testing

Module 6: Digital Marketing Performance Analysis

  1. 6.1Measuring SEO and paid advertising performance
  2. 6.2Social, content, and landing page performance
  3. 6.3Comparing acquisition channels
  4. 6.4Evaluating campaigns and avoiding vanity metrics

Module 7: Reporting, Visualization, and Insights

  1. 7.1Building a marketing performance report
  2. 7.2Data visualization and dashboards
  3. 7.3Comparing periods and benchmarking
  4. 7.4Turning data into actionable recommendations

Module 8: Analytics Projects and Practical Assessment

  1. 8.1Analytics case study: Isla Coffee Co.
  2. 8.2Final assessment: digital analytics case study

The four types of analytics

Covered here

  • The four types of analytics and the question each answers
  • Where most beginner analysis sits
  • How to move from what happened to what to do

Short answer

There are four types of analytics. Descriptive tells you what happened. Diagnostic explains why it happened. Predictive estimates what is likely to happen next. Prescriptive recommends what you should do. Most beginners start with descriptive and diagnostic work, and value grows as you move toward prediction and clear recommendations.

The four types

  1. Descriptive: what happened? The site had 12,000 sessions last month.
  2. Diagnostic: why did it happen? Sessions fell because a top-ranking page dropped in Google.
  3. Predictive: what is likely to happen? Based on past seasons, traffic should rise 30% in December.
  4. Prescriptive: what should we do? Raise holiday ad budget two weeks early to catch rising demand.

Try it: sort the questions

Sort each item into the right group.

  • How many orders did we get in September?

  • Why did mobile sales drop last week?

  • How many visitors should we expect during 11.11?

  • Should we move budget from Facebook to Google Ads?

  • Which page had the most views?

  • Why did the email campaign get fewer clicks?

Quick quiz

1. "Why did traffic fall?" is which type?
2. Which type recommends an action?

Your action

Key terms

Descriptive analytics
Summarizes what happened.
Diagnostic analytics
Explains why it happened.
Predictive analytics
Estimates what will likely happen.
Prescriptive analytics
Recommends what action to take.

Questions beginners ask

Do small businesses need predictive analytics?

Not at first. Simple seasonal comparisons, like last December vs. this December, already work as basic prediction.

Which type should I learn first?

Descriptive, then diagnostic. You cannot explain a change you have not measured.

Related lessons

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