Download Web Analytics for Dummies (ISBN - 0470098244) PDF

TitleWeb Analytics for Dummies (ISBN - 0470098244)
TagsFor Dummies
File Size11.1 MB
Total Pages386
Table of Contents
                            Web Analytics For Dummies
	About the Authors
	Authors’ Acknowledgments
	Contents at a Glance
	Table of Contents
		About This Book
		Foolish Assumptions
		How This Book Is Organized
		Icons Used in This Book
	Part I: Getting Started with Web Analytics
		Chapter 1: Understanding Web Analytics
			Web Analytics: Why Bother?
			Web Analytics 101
		Chapter 2: Steering Clear of Common Terminology Confusion
			Hitting the Terminology Targets
			The ABCs of Web Analytics
			Mastering Internet Marketing Lingo
			Defining Actionable Data
			Untangling Technical Terms
		Chapter 3: Getting Your Hands Dirty with Web Data
			Help! I Can’t Find My Stats!
			Taking a Sneak Peek at the Data
			Comprehending Conversion Rates
	Part II: Choosing the Right Web Analytics Solution
		Chapter 4: Web Analytics Tools You Can Use
			Before You Begin . . .
			Surveying Server-Side Software
			Discovering Desktop Applications
			Hooked on Hosted Solutions
			Getting the Best of All Worlds
		Chapter 5: Investing in Web Analytics Tools
			Before You Begin
			Don’t Forget the Freebies
			Low-Cost Solutions, High-End Returns
			Enterprise Analytics for the Data Hungry
		Chapter 6: Discovering Niche Solutions
			Web Analytics: A Boon for Bloggers
			Read All about It: RSS Analytics
			Analytics in a Pod
			Because You Are Paying Per Click
			People Watch with Live Analytics Tools
			Exploring A/B and Multivariate Testing Software
	Part III: Searching for Statistical Treasure
		Chapter 7: Taking Out the Trash
			Classifying Nonhuman Users
			Why Eliminate Nonhuman Users?
			The Danger of Referrer Spam
			Fighting Referrer Spam
			Ignoring Non– Mission-Critical Stats
		Chapter 8: Reviewing Site Referrers
			Revving Up for Referrers
			Discovering Your Traffic Partners
			Searching for Statistical Treasure
			Beyond Search Engines: Where Else Is My Traffic Coming From?
		Chapter 9: Getting to Know Your Visitors
			Gleaning from Your Visitors’ Past
			Searching for Significance
			Gleaning from Clickstreams and Labeling
			Wow! My Site Has Multinational Appeal!
			Betting on Browser Data
		Chapter 10: Identifying Your Most Important Pages
			It’s Not a Popularity Contest — Or Is It?
			Which Pages Drive Your Traffic?
			To Err Is Human, to Fix Is Divine
			Working with Dynamic Pages
		Chapter 11: Key Performance Indicators Insights
			KPIs: When Not Just Any Data Will Do
			The Granddaddy List of KPIs
			Which KPIs Are Right for You?
			Creating Your Own KPIs
	Part IV: Knowledge Is Power — Making Analytics Work for You
		Chapter 12: Sifting through Search Data
			Sifting Your Search Terms
			My Visitors Are Searching for What?!
			Cashing In on Common Misspellings
			Beyond Traffic to Conversions
			Flip-Flopping the 80/20 Rule
			Monitoring Internal Site Searches
			Searching for Accuracy and Relevancy
			Creating Targeted Landing Pages
			Your Search Yielded Zero Results . . .
		Chapter 13: Increasing Web Site Visibility
			Finding New Customers
			Milking Multichannel Sales
			Reach Out and Touch Your Referrers
			Understanding Strategic Alliances
		Chapter 14: Revisiting Your Online Advertising Strategy
			Many Ad Types, Many Analytics Tools
			Tracking Efforts with Tracking URLs
			Adding Campaign Analytics to the Mix
			Combating Click Fraud
			Evaluating E-mail Marketing Campaigns
			Tracking Offline Responses to Online Ads
			Ferreting Out Ad Stats that Don’t Work
			Unraveling Conversion Process Breakdowns
			Examining Google’s Conversion Funnel
			Employing Conversion Tracking Tools
			Optimizing Your Ad Campaigns
		Chapter 15: Chronicling Your Web Analytics History
			Name, Rank, and Serial Number
			Benchmarking Your Conversion Rate
			Benchmarking Your KPIs
			Benchmarking Times and Seasons
			Identifying Hidden Trends
			Many Tools, Many Benchmarks
			Access Log Files: To Save or Not to Save?
		Chapter 16: Fine-Tuning Your Web Site
			Understanding Optimization Strategies
			Optimizing Your Home Page
			What Sends Visitors Running?
			Optimizing Your Landing Pages
			Optimizing Product Pages
			Starting with a Clean Web Slate
			Determining Why Your Customers Abandon You
			Reducing Shopping Cart Abandonment
			Measuring the Effect of Site Changes
	Part V: The Part of Tens
		Chapter 17: Ten Web Analytics Myths, Mistakes, and Pitfalls
			Averages Are the Analytics Answer
			Monthly Visitor Trends Tell All
			Pinpoint Precision Is Paramount
			Unique Visitor Data Tells the Truth
			All Web Analytics Software Is Alike
			But Numbers Never Lie . . .
			A Picture Speaks a Thousand Words
			Popular Search Terms Hold the Key to More Traffic
			Funnel Vision Offers a Quick Fix
			Betting the Farm on Top 10 Lists
		Chapter 18: Ten Reasons Why Web Analytics Will Revolutionize E-Business
			Truly Develop a User-Oriented Web Site
			Make the Most of Online Marketing
			Save Money on Paid Search Campaigns
			Cross-Sell and Up-Sell Your Customers
			Realize Real-Time Opportunities
			Combating Controversial Click Fraud
			Closing the Delayed Conversion Loop
			Optimize Self-Support Functions
			Increase Results from E-Mail Campaigns
			Predict the Future Here and Now
		Chapter 19: Ten Web Analytics Best Practices
			Define Metrics That Matter
			Monitor Only Your Vital KPIs
			Segment Your Visitors’ Behavior
			Know Your Navigation Report
			Keep Up With Keyword Campaigns
			Optimize Your Landing Pages
			Calculate Visitor Conversion
			Save Your Historical Data
			Make Changes Gradually
			Commit to Continual Improvement
	Appendix: Web Analytics Glossary
Document Text Contents
Page 1

by Pedro Sostre
and Jennifer LeClaire

Web Analytics


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Page 2

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To Err Is Human, to Fix Is Divine
When a customer sees a broken image, stumbles onto a Page Cannot be
Found error, or clicks a link that is no longer active, your Web site’s credibil-
ity takes a nose dive. Put yourself in the visitor’s shoes: You’ve been scouring
the Web for the perfect venue (to buy shoes, to read about something, or to
find a consultant who can help you launch your new product). You finally find
a Web site that looks promising only to be met with error messages. Wouldn’t
you be frustrated, too? You are lucky if those visitors try again later.

Web analytics programs are designed to help you avoid these potentially
costly faux pas by alerting you to these errors. You can discover them in a
section of your Web analytics software, named something like HTTP Error
Codes or Error Log. We recommend becoming acquainted with this report
and to look at it at least once a month. Finding the errors is not enough,
though. You also need to know what the codes mean so you can fix them
in a hurry.

Deciphering error codes
If you’ve ever heard someone say she received a 404 code and wondered
what she meant, you are about to find out — and you need to know because
it could happen to you.

Figure 10-4:
The Google




173Chapter 10: Identifying Your Most Important Pages

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When a visitor requests a file, the Web server records an HTTP response code.
Some response codes are good, some are bad, and some are downright ugly.
The server goes through this process every single time a visitor requests a
file. Most Web analytics applications make reference to Web site errors by
their designated HTTP response code. Because these are common and
because even well-maintained sites are liable to throw errors from time
to time, wisdom dictates getting familiar with the errors you are likely to
encounter on the road to Web success.

Seeking success codes
Some people use the phrases response code and error codes interchangeably,
and these numerical distinctions don’t always bring bad news. Although
these success codes are reported in many Web analytics applications, the
user doesn’t generally see response codes that don’t indicate an error. They
occur behind the scenes while your browser continues to take you to the
requested file. Here is a list of non-error response codes, however, that you
might come across:

� 200 OK: The page was served successfully. No additional work required.

� 206 Partial Content: The page was loaded, but some of the content
might not have loaded properly. One common reason happens when a
user clicks the Stop button on his browser, which stops the server from
downloading the files in midstream. In most cases, the user might not even
realize that parts of the page didn’t load. This is an error you can ignore. If
you see this error occurring frequently, however, consider optimizing your
pages or contacting the person responsible for managing your Web server.
(That’s usually your hosting company or IT department.)

174 Part III: Searching for Statistical Treasure

Are you using the right tools?
Just like a doctor needs the right tools to
diagnose a patient, you need the right tools to
diagnose your Web site. In this chapter, we use
Google Analytics to check the pulse of top-
performing pages. However, this freebie tool
remains relatively silent when it comes to error
pages because it’s a hosted analytics tool.
Hosted tools rely on snippets of code placed on
your Web site pages to record individual visits.

Because broken images and missing pages
cannot be tagged, hosted applications tend to
leave you in the lurch. If you rely solely on a
hosted Web analytics tool, you might not find
out about errors on your site unless you stum-
ble upon them yourself — or unless a frustrated
customer e-mails you in the midnight hour. For a
full review of the pros and cons for the different
types of analytics tools, see Chapter 4.

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