Practical Web Analytics for User Experience : How Analytics Can Help You Understand Your Users.

Format:

Book

Author/Creator:

Beasley, Michael.

Language:

English

Subjects (All):

Web site development.

Physical Description:

1 online resource (251 pages)

Edition:

1st ed.

Place of Publication:

San Diego : Elsevier Science & Technology, 2013.

Contents:

Front Cover

Practical Web Analytics for User Experience

Copyright Page

Contents

Acknowledgments

About the Author

1 Introduction

What Is Web Analytics?

User Experience and Web Analytics Questions

Web Analytics and User Experience: A Perfect Fit

About This Book

Part 1: Introduction to Web Analytics

Part 2: Learning About Users through Web Analytics

Part 3: Advanced Topics

Google Analytics

1 Introduction to Web Analytics

2 Web Analytics Approach

Introduction

Get To Know Your Website

A Model of Analysis

Pose The Question

Gather Data

Transform Data

Analyze

Answer the Question

Balancing Time and the Need for Certainty

Showing Your Work

Context Matters

Data Over Time

Proportion is Key

Sometimes The Data Contradict You

Sometimes the Answer is "No"

Make Your Findings Repeatable

Key Takeaways

3 How Web Analytics Works

Log File Analysis

Page Tagging

Cookies

Accuracy

Accounts and Profiles

Click Analytics

Metrics and Dimensions

Visits

Unique Visitors (Metric)

Pageviews (Metric)

Pages/Visit (Metric)

Average Visit Duration

Bounce Rate (Metric)

% New Visits (Metric)

Using These Metrics

Interacting With Data In Google Analytics

Plot Rows

Secondary Dimension

Sort Type

Search

Beyond Tables

Percentage

Performance

Comparison

Term Cloud

Pivot

4 Goals

What Are Goals and Conversions?

Unfortunate Colliding Terms

All Websites Should Have Goals

Why Do Goals Matter for User Experience?

Conversion Rate

Goal Reports In Google Analytics

Goal URLs

Reverse Goal Path

Funnel Visualization Report

Goal Flow

E-commerce

Multichannel Funnels

When Do You Use These Reports?.

Finding The Right Things To Measure As Key Performance Indicators

What Should You Measure?

What Is the Purpose of the Company/Organization?

How Does the Website Fit in with This Purpose?

What Does the Company/Organization Want Users To Do on the Website?

What Specific, Measurable Behavior Shows that Users Took that Action?

Do Users Want To Do These Things?

What Can You Measure On a Website That Can Constitute A Goal?

Reaching a Specific Page

Funnel Transactions

Destination Only

On-Page Action

Engagement

Going Beyond The Website

Tying It Together

2 Learning about Users through Web Analytics

5 Learning about Users

Visitor Analysis

Demographics-Location

Behavior-New vs. Returning

Behavior-Frequency &amp

Recency

Behavior-Engagement

Technology-Browser &amp

OS

Mobile-Overview

Custom (As in Custom Variables)

6 Traffic Analysis: Learning How Users Got to Your Website

Source and Medium (Dimensions)

Organic Search

Why Analyze Keywords?

Search Query Analysis

Exporting the Data

Create Candidate Categories

Processing the Data

Analyzing the Data Again

Basic Keyword Analysis

Export the Data

Categorize the Keywords

Compare Metrics

Referral Traffic

Direct Traffic

Paid Search Keywords

7 Analyzing How People Use Your Content

Website Content Reports

High Pageviews/Low Pageviews

Pageviews are Much Higher than Unique Pageviews

Low Time on Page

High Time on Page

High Entrances to Unique Pageviews Ratio

High Bounce Rate

High % Exit

Page Value

Comparing Page Metrics to Similar Pages

More Reports

"Landing Page" Report

"Exit Pages" Report

"Content Drilldown" Report

"Site Speed" Report.

"In-Page Analytics" Report

8 Click-Path Analysis

Focus on Relationships between Pages

Navigation Summary

"Visitors Flow" Report

Analyzing How Users Move from One Page Type to Another

An Example: AwesomePetToys.com

9 Segmentation

Why Segment Data?

How To Segment Data

Google Analytics' Advanced Segments

What are the Ways You Can Segment Data?

AND, OR, and Sequence of Filters

Metrics

Dimensions

Useful Ways To Segment For UX Questions

Segmenting According to a Page

Example 1

Example 2

Segmenting According to User Traits

Segmenting According to Information Need

Whether or Not Users Completed a Goal

What Pages Users Landed On

What Pages Users Viewed/Didn't View

The Tip of the Iceberg

10 Pairing Analytics Data with UX Methods

Personas

Segmenting Based on Personas

Segmenting According to Technology

Segmenting According to Demographic Aspects

Segmenting According to Behavior

What Can You Do with Segmentation?

Building Better Personas

Usability Testing

Test Planning

Using Goals

Prioritizing Tasks

Identifying Potential Problem Areas

Test Analysis

What if You Find Out Something isn't a Common Problem?

Usability Test Reports

Usability Inspection

Identifying Potential Problems

Evidence for Problems

Design and Design Objectives

How Much Will You Improve a Number?

11 Measuring the Effects of Changes

Reframe As a Rate

Choose What to Measure

Choose When to Measure

Types of Changes

Other Rates

Redirect Traffic

Did Users Reach a Single Page from Any Other Page?

Did Users Reach a Single Page from a Specific Page?.

Did Users Reach Any of a Group of Pages from Any Other Page?

More Variations

Time on Page and Other Continuous Metrics

Changing Many Things at Once

Reporting

New Designs Don't Always Work

3 Advanced Topics

12 Measuring Behavior within Pages

Google Analytics In-Page Analytics

Click Analytics Tools

Making Clicks Measureable In Page Tagging Analytics Tools

Defining Events

Example 1: What Videos Did Users Watch?

Example 2: Where Did Users Click on a Page?

Example 3: Did Users Get Any Search Results?

Putting It Together

Analyzing Event Data

Pages and Events-What Happened Where?

On What Pages Did an Event Happen?

What Events Happened on the Page?

Making Rates

Segmentation

Virtual Pageviews

13 A/B Testing

Designing An Experiment

Select a Page That You Wish to Improve

Determine a Metric for Judging Improvement

Design One or More Alternatives

Tracking Code

Tools

Google Content Experiments

Specialized Tools

Estimating the Length of a Test

Monitoring and "Winning"

Ending a Test Early

14 Analytics Profiles

Profiles

What are Profile Filters?

Making URLs Easier to Read

Easier Click-path Analysis by Combining Pages

A Profile for UX Data

15 Regular Reporting and Talking to Stakeholders

Reporting Culture

Why You Report Analytics Data

Why You Monitor Analytics Data

Choosing Metrics to Report

Reporting Frequency

Keep It Concise

Making The Case for Usability Activities

Making the Case for Design Changes

Making the Case for User Research

16 Web Analytics in the Near Future

Mobile Application Analytics

Cross-Device Measurement.

Better Measurement of On-Page Behavior

Connecting to Other Data Sources

The Continuing Dominance of Google

Things Will Keep Changing

Index.

Notes:

Description based on publisher supplied metadata and other sources.

Other Format:

Print version: Beasley, Michael Practical Web Analytics for User Experience

ISBN:

9780124046948

OCLC:

851153798