Web Analytics: An Hour a Day
暫譯: 網路分析:每天一小時
Avinash Kaushik
- 出版商: Sybex
- 出版日期: 2007-06-05
- 售價: $1,300
- 貴賓價: 9.5 折 $1,235
- 語言: 英文
- 頁數: 480
- 裝訂: Paperback
- ISBN: 0470130652
- ISBN-13: 9780470130650
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商品描述
Description
Web Analytics: An Hour A Day is the first book by an in-the-trenches practitioner of web analytics. It provides a unique insider’s perspective of the challenges and opportunities that web analytics presents to each person who touches the Web in your organization. Rather than spamming you with metrics and definitions, Web Analytics: An Hour A Day will enhance your mindset and teach you how to fish for yourself.Avinash Kaushik is a expert in web analytics and author of the top-rated blog Occam’s Razor (http://www.kaushik.net/avinash). In this book, he goes beyond web analytics concepts and definitions to provide a step-by-step guide to implementing a successful web analytics strategy. His revolutionary approach to web analytics challenges prevalent thinking about the field and guides readers to a solution that will provide truly informed and actionable insights.
In Part I, Avinash explains why traditional web analytics is dead and introduces the Trinity mindset and strategic approach for web analytics. He then details the data collection options at your disposal for robust analytics and the pros and cons of each methodology (such as clickstream, outcomes, research, and competitive data). He concludes Part I with a deep dive into qualitative data and its critical role in any web analytics program.
In Part II, Avinash provides insights that will challenge your knowledge of what it takes to create a successful web analytics program. He covers customer centricity, optimal organizational structure, how to identify great analysts, and his (now famous) 10/90 rule of web analytics. From his experience, he outlines radical strategies for how you should select the right tool for your company (while saving money and peace of mind) and identify truly valuable metrics with his "three layers of So What?" test. He concludes Part II by providing a fresh perspective on some of the most common web analytics reports that you'll never look at in the same way again.
In Part III, Avinash guides readers to a successful web analytics strategy and implementation month by month, day by day, and hour by hour. A customized quick-start guide for different businesses (including blogs) is followed by increasingly advanced and crucial analytics topics, such as search analytics (SEO, SEM/PPC and internal site search) and multi-channel marketing analytics. That's followed by the revelation of the key ingredients of a great experimentation and testing platform, performing competitive intelligence analysis, and Web 2.0 analytics.
Avinash then discusses the three secrets behind making web analytics actionable and, in his clever, engaging, and thought-provoking style, debunks leading myths—about path analysis, conversion analysis, and real-time data, for example.
Finally, Avinash highlights seven specific steps you can take to create a data-driven decision-making culture in your company and then discusses such advanced analytics concepts as statistical significance, SEM and PPC analysis, the power of segmentation, complex yet insightful pan-session metrics, and conversion rate best practices.
Sprinkled throughout the book are real-world examples drawn from Avinash’s experiences as an analytics professional at Intuit, DirecTV, Silicon Graphics Inc., and DHL.
The book includes an innovative CD that includes more than five hours of insightful audio podcasts, a 45-minute video, PowerPoint presentations, and other useful web analytics resources. Web Analytics: An Hour a Day is the ultimate resource for anyone needing a step-by-step, task-based guide to creating and maintaining a modern web analytics strategy and framework.
Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.
Table of Contents
Foreword.Introduction.
Chapter 1 Web Analytics—Present and Future.
A Brief History of Web Analytics.
Current Landscape and Challenges.
Traditional Web Analytics Is Dead.
What Web Analytics Should Be.
Chapter 2 Data Collection—Importance and Options.
Understanding the Data Landscape.
Clickstream Data.
Outcomes Data.
Research Data.
Competitive Data.
Chapter 3 Overview of Qualitative Analysis.
The Essence of Customer Centricity.
Lab Usability Testing.
Heuristic Evaluations.
Site Visits (Follow-Me-Home Studies).
Surveys (Questionnaires).
Summary.
Chapter 4 Critical Components of a Successful Web Analytics Strategy?
Focus on Customer Centricity.
Solve for Business Questions.
Follow the 10/90 Rule.
Hire Great Web Analysts.
Identify Optimal Organizational Structure and Responsibilities.
Chapter 5 Web Analytics Fundamentals.
Capturing Data: Web Logs or JavaScript tags?
Selecting Your Optimal Web Analytics Tool.
Understanding Clickstream Data Quality.
Implementing Best Practices.
Apply the “Three Layers of So What” Test.
Chapter 6 Month 1: Diving Deep into Core Web Analytics Concepts.
Week 1: Preparing to Understand the Basics.
Week 2: Revisiting Foundational Metrics.
Week 3: Understanding Standard Reports.
Week 4: Using Website Content Quality and Navigation Reports.
Chapter 7 Month 2: Jump-Start Your Web Data Analysis.
Prerequisites and Framing.
Week 1: Creating Foundational Reports.
E-commerce Website Jump-Start Guide.
Support Website Jump-Start Guide.
Blog Measurement Jump-Start Guide.
Week 4: Reflections and Wrap-Up.
Chapter 8 Month 3: Search Analytics—Internal Search, SEO, and PPC.
Week 1: Performing Internal Site Search Analytics.
Week 2: Beginning Search Engine Optimization.
Week 3: Measuring SEO Efforts.
Week 4: Analyzing Pay per Click Effectiveness.
Chapter 9 Month 4: Measuring Email and Multichannel Marketing.
Week 1: Email Marketing Fundamentals and a Bit More.
Week 2: Email Marketing—Advanced Tracking.
Weeks 3 and 4: Multichannel Marketing, Tracking, and Analysis.
Chapter 10 Month 5:Website Experimentation and Testing—Shifting the Power to Customers and Achieving Significant Outcomes.
Weeks 1 and 2: Why Test and What Are Your Options?
Week 3: What to Test—Specific Options and Ideas.
Week 4: Build a Great Experimentation and Testing Program.
Chapter 11 Month 6: Three Secrets Behind Making Web Analytics Actionable.
Week 1: Leveraging Benchmarks and Goals in Driving Action.
Week 2: Creating High Impact Executive Dashboards.
Week 3: Using Best Practices for Creating Effective Dashboard Programs.
Week 4: Applying Six Sigma or Process Excellence to Web Analytics.
Chapter 12 Month 7: Competitive Intelligence and Web 2.0 Analytics.
Competitive Intelligence Analytics.
Web 2.0 Analytics.
Chapter 13 Month 8 and Beyond: Shattering the Myths of Web Analytics.
Path Analysis: What Is It Good For? Absolutely Nothing.
Conversion Rate: An Unworthy Obsession.
Perfection: Perfection Is Dead, Long Live Perfection.
Real-Time Data: It’s Not Really Relevant, and It’s Expensive to Boot.
Standard KPIs: Less Relevant Than You Think.
Chapter 14 Advanced Analytics Concepts—Turbocharge Your Web Analytics.
Unlock the Power of Statistical Significance.
Use the Amazing Power of Segmentation.
Make Your Analysis and Reports “Connectable”.
Use Conversion Rate Best Practices.
Elevate Your Search Engine Marketing/Pay Per Click Analysis.
Measure the Adorable Site Abandonment Rate Metric.
Measure Days and Visits to Purchase.
Leverage Statistical Control Limits.
Measure the Real Size of Your Convertible “Opportunity Pie”.
Chapter 15 Creating a Data-Driven Culture—Practical Steps and Best Practices.
Key Skills to Look for in a Web Analytics Manager/Leader.
When and How to Hire Consultants or In-House Experts.
Seven Steps to Creating a Data-Driven Decision-Making Culture.
Index.
商品描述(中文翻譯)
**描述**
《網路分析:每天一小時》是一本由實際從事網路分析的專家所撰寫的首本書籍。它提供了獨特的內部視角,探討網路分析對於每一位在您組織中接觸網路的人所帶來的挑戰與機會。與其用指標和定義來轟炸您,《網路分析:每天一小時》將提升您的思維方式,並教您如何自我探索。
Avinash Kaushik 是網路分析的專家,也是評價最高的部落格《奧卡姆剃刀》(http://www.kaushik.net/avinash)的作者。在這本書中,他超越了網路分析的概念和定義,提供了一個逐步實施成功網路分析策略的指南。他對網路分析的革命性看法挑戰了對該領域的普遍認知,並引導讀者找到能提供真正有根據且可行見解的解決方案。
在第一部分中,Avinash 解釋了為什麼傳統的網路分析已經過時,並介紹了網路分析的三位一體思維模式和戰略方法。他接著詳細說明了可用於強大分析的數據收集選項,以及每種方法的優缺點(如點擊流、結果、研究和競爭數據)。他以深入探討質性數據及其在任何網路分析計劃中的關鍵角色作為第一部分的結尾。
在第二部分中,Avinash 提供了挑戰您對成功網路分析計劃所需知識的見解。他涵蓋了以客戶為中心的思維、最佳組織結構、如何識別優秀分析師,以及他(現在已成名的)網路分析 10/90 規則。根據他的經驗,他概述了選擇適合您公司的正確工具的激進策略(同時節省金錢和心靈的平靜),並通過他的「三層次的 So What?」測試來識別真正有價值的指標。他以提供對一些最常見的網路分析報告的新視角作為第二部分的結尾,讓您再也不會以同樣的方式看待它們。
在第三部分中,Avinash 引導讀者逐月、逐日、逐小時地實施成功的網路分析策略。針對不同業務(包括部落格)的定制快速入門指南,隨後是越來越高級和關鍵的分析主題,如搜索分析(SEO、SEM/PPC 和內部網站搜索)以及多渠道行銷分析。接著揭示了優秀實驗和測試平台的關鍵要素,進行競爭情報分析,以及 Web 2.0 分析。
Avinash 然後討論了使網路分析可行的三個秘密,並以他聰明、引人入勝且發人深省的風格揭穿了關於路徑分析、轉換分析和即時數據等的主要神話。
最後,Avinash 強調了您可以採取的七個具體步驟,以在您的公司中創建數據驅動的決策文化,然後討論了統計顯著性、SEM 和 PPC 分析、細分的力量、複雜但有見地的全會話指標以及轉換率最佳實踐等高級分析概念。
書中穿插了來自 Avinash 在 Intuit、DirecTV、Silicon Graphics Inc. 和 DHL 擔任分析專業人士的真實案例。
本書附有一張創新的 CD,包含超過五小時的深刻音頻播客、一段 45 分鐘的視頻、PowerPoint 簡報以及其他有用的網路分析資源。《網路分析:每天一小時》是任何需要逐步、基於任務的現代網路分析策略和框架創建與維護指南的終極資源。
**注意:** CD-ROM/DVD 和其他補充材料不包含在電子書文件中。
**目錄**
前言。
介紹。
**第一章 網路分析—現在與未來。**
網路分析的簡史。
當前的格局與挑戰。
傳統網路分析已死。
網路分析應該是什麼。
**第二章 數據收集—重要性與選項。**
理解數據格局。
點擊流數據。
結果數據。
研究數據。
競爭數據。
**第三章 質性分析概述。**
以客戶為中心的本質。
實驗室可用性測試。
啟發式評估。
網站訪問(跟隨我回家研究)。
調查(問卷)。
總結。
**第四章 成功網路分析策略的關鍵組成部分?**
專注於以客戶為中心。
解決商業問題。
遵循 10/90 規則。
聘請優秀的網路分析師。
識別最佳的組織結構和職責。
**第五章 網路分析基礎。**
捕捉數據:網路日誌還是 JavaScript 標籤?
選擇最佳的網路分析工具。
理解點擊流數據質量。
實施最佳實踐。
應用「三層次的 So What」測試。
**第六章 第 1 個月:深入核心網路分析概念。**
第 1 週:準備理解基礎。
第 2 週:重新審視基礎指標。
第 3 週:理解標準報告。
第 4 週:使用網站內容質量和導航報告。
**第七章 第 2 個月:啟動您的網路數據分析。**
前提和框架。
第 1 週:創建基礎報告。
電子商務網站啟動指南。
支持網站啟動指南。
部落格測量啟動指南。
第 4 週:反思與總結。
**第八章 第 3 個月:搜索分析—內部搜索、SEO 和 PPC。**
第 1 週:執行內部網站搜索分析。
第 2 週:開始搜索引擎優化。
第 3 週:衡量 SEO 成效。
第 4 週:分析每次點擊付費的有效性。
**第九章 第 4 個月:衡量電子郵件和多渠道行銷。**
第 1 週:電子郵件行銷基礎及更多。
第 2 週:電子郵件行銷—進階追蹤。
第 3 和第 4 週:多渠道行銷、追蹤和分析。
**第十章 第 5 個月:網站實驗與測試—將權力轉移給客戶並實現顯著成果。**
第 1 和第 2 週:為什麼要測試以及您的選擇是什麼?
第 3 週:測試什麼—具體選項和想法。
第 4 週:建立一個優秀的實驗和測試計劃。
**第十一章 第 6 個月:使網路分析可行的三個秘密。**
第 1 週:利用基準和目標推動行動。
第 2 週:創建高影響力的高管儀表板。
第 3 週:使用最佳實踐創建有效的儀表板計劃。
第 4 週:將六西格瑪或流程卓越應用於網路分析。
**第十二章 第 7 個月:競爭情報與 Web 2.0 分析。**
競爭情報分析。
Web 2.0 分析。
**第十三章 第 8 個月及以後:打破網路分析的神話。**
路徑分析:它有什麼用?絕對沒有。
轉換率:一種不值得的痴迷。
完美:完美已死,萬歲完美。
即時數據:它實際上不相關,而且還很貴。
標準 KPI:比您想的更不相關。
**第十四章 高級分析概念—提升您的網路分析。**
解鎖統計顯著性的力量。
利用細分的驚人力量。
使您的分析和報告「可連接」。
使用轉換率最佳實踐。
提升您的搜索引擎行銷/每次點擊付費分析。
衡量可愛的網站放棄率指標。
衡量購買的天數和訪問次數。
利用統計控制界限。
衡量您可轉換的「機會餅」的實際大小。
**第十五章 創建數據驅動的文化—實用步驟和最佳實踐。**
尋找網路分析經理/領導者的關鍵技能。
何時以及如何聘請顧問或內部專家。
創建數據驅動決策文化的七個步驟。
索引。