Web Analytics 2.0: The Art of Online Accountability and Science of Customer Centricity

Web Analytics 2.0: The Art of Online Accountability and Science of Customer Centricity

Avinash Kaushik

Language: English

Pages: 475

ISBN: 0470529393

Format: PDF / Kindle (mobi) / ePub


Adeptly address today’s business challenges with this powerful new book from web analytics thought leader Avinash Kaushik. Web Analytics 2.0 presents a new framework that will permanently change how you think about analytics. It provides specific recommendations for creating an actionable strategy, applying analytical techniques correctly, solving challenges such as measuring social media and multichannel campaigns, achieving optimal success by leveraging experimentation, and employing tactics for truly listening to your customers. The book will help your organization become more data driven while you become a super analysis ninja!

Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.

Lean UX: Applying Lean Principles to Improve User Experience

A Web for Everyone: Designing Accessible User Experiences (1st Edition)

Adobe Creative Cloud Design Tools Digital Classroom

White Space is Not Your Enemy: A Beginner's Guide to Communicating Visually through Graphic, Web and Multimedia Design

Learning Responsive Web Design

White Space is Not Your Enemy: A Beginner's Guide to Communicating Visually through Graphic, Web and Multimedia Design

 

 

 

 

 

 

 

 

 

 

 

 

 

test to ensure you have diversity in your selection process. Now comes the exciting part! You’ll take the selection-process finalists and run a real, live pilot on your site, and then in a dramatic ceremony worthy of the TV show The Bachelor, you’ll present a rose (actually, your money) to your chosen partner. It is important to realize at the outset that the average time from implementing a vendor to recognizing your mistake to choosing to switch to and implement a new vendor is approximately

marketers, analysts as Marketing Productivity blog Marketing Profs organization Marketleap reports Marshall, John Mason, Neil match types in PPC analyses math skills for web analytics mathematical rigor by online survey providers Maxamine tool MeasureMap tool Medcraft, Steve media mix models rich-media tracking medium-sized businesses, Multiplicity elements in mental flexibility skills for analytics managers message amplification in Twitter @Messages metric metrics overview

webs run time sampling S salary prospects in web analytics Sales metric sample bias in panel data sampling in pilot tests for reconciliation scenarios SAS (software-as-a-service) model satisfaction computation Save Your Itinerary feature saving data SbKT (Search-based Keyword Tool) scalable listening. See surveys scale in behavior targeting video playback scale filters scorecards in Klout Screen Resolution metric screen-sharing applications search analysis audience

the cookies; in Google Analytics, it might have to be a customized JavaScript tag. Suffice it to say that setting up all these parameters is not a walk in the park. #8: The Hidden Angel: Data Sampling I covered data sampling earlier in this chapter. You can sample at the source (not collect data at all), or you can sample at run time (collect all data but sample sessions/Visits). You want to ensure that you are applying the same kind of data sampling in all your web analytics tools. The

people who were supposed to be watching the TV ad were in the bathroom and another 20 percent actually fast-forwarded the ad on TiVo. But why quibble? If you are Target, you know the cost of sending someone a weekly mailer, as well as how many people see it online and print the coupons. Use the offline numbers to compute the value of the online weekly mailer views. And don’t forget to compute the value of the people who sign up for the weekly exclusive email newsletters! You know how much it

Download sample

Download