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analytics presentation

  1. 1. Web Analytics & Customer Analysis By Jean-François (JF) Bélisle, MSc, PhD© Jean-François Bélisle, 2012 ©
  2. 2. Who are you man? Director – Consulting Services @ K3 MediaB.Sc. Economics, Université de MontréalM.Sc. Marketing, HEC MontréalAward of Achievement, Web Analytics, University of British ColumbiaPh.D. Studies, Marketing & Computational Stats, McGill UniversityExecutive training in Customer Analytics, University of Pennsylvania (Wharton)10/2/2012 Jean-François Bélisle, 2012 © 2
  3. 3. For which companies have you worked man?10/2/2012 Jean-François Bélisle, 2012 © 3
  4. 4. … and some clients of K3?10/2/2012 Jean-François Bélisle, 2012 © 4
  5. 5. K3 Certifications Pay-Per-Click Programming Design Analytics (SEM) 5 4 2 1210/2/2012 Jean-François Bélisle, 2012 © 5
  6. 6. K3 Strategic Alliances10/2/2012 Jean-François Bélisle, 2012 © 6
  7. 7. Game Plan1. Analytics Quick Intro2. Web Analytics: Getting Started3. Data Gathering4. Key Terms in Web Analytics5. KPIs6. Strategic Issues7. Other Methods8. Some Resources10/2/2012 Jean-François Bélisle, 2012 © 7
  8. 8. Section 1 – Analytics Quick Intro10/2/2012 Jean-François Bélisle, 2012 © 8
  9. 9. 1.1 Analytics - What is it? AnalyticsThe application of computer technology, operational research, and statistics to solve problems in business and industry.10/2/2012 Jean-François Bélisle, 2012 © 9
  10. 10. 1.2 Analytics – in 1990 In 1990, what came to people’s mind when someone said analytics? Boring UglyGeeky Useless Incomprehensible Hard Worthless10/2/2012 Jean-François Bélisle, 2012 © 10
  11. 11. 1.3 Analytics – in 2012In 2012, what comes to people’s mind when someone says analytics? Cool SexyCommon Useful Understandable Accessible Gold10/2/2012 Jean-François Bélisle, 2012 © 11
  12. 12. 1.4 Analytics & « Moneyball »10/2/2012 Jean-François Bélisle, 2012 © 12
  13. 13. 1.5 Analytics & Data10/2/2012 Jean-François Bélisle, 2012 © 13
  14. 14. 1.6 Data = Analytics?Companies have lots and lots of data…The problemhow to make sense of these data?10/2/2012 Jean-François Bélisle, 2012 © 14
  15. 15. 1.7 Analytics - Managerially You can’t manage what you can’t measure!10/2/2012 Jean-François Bélisle, 2012 © 15
  16. 16. 1.8 Analytics – Managerially (2) You can’t manage what you don’t measure!10/2/2012 Jean-François Bélisle, 2012 © 16
  17. 17. 1.9 Analytics -> Managerial Insights? Garbage In, Garbage Out10/2/2012 Jean-François Bélisle, 2012 © 17
  18. 18. 1.10 How Data Becomes Managerial Insights? Objectives Data Analytics (e.g. KPIs) Decision10/2/2012 Jean-François Bélisle, 2012 © 18
  19. 19. Section 2 – Web Analytics: Getting Started10/2/2012 Jean-François Bélisle, 2012 © 19
  20. 20. 2.1 Big Names in Web analyticsInternational:• Avinash Kaushik• Bryan Eisenberg• Jim Sterne• Eric Peterson• Jim Novo• Alex LangshurQuebec:• Stéphane Hamel• Jacques Warren10/2/2012 Jean-François Bélisle, 2012 © 20
  21. 21. 2.2 Web Analytics Tools Ranking10/2/2012 Jean-François Bélisle, 2012 © 21
  22. 22. 2.3 Google Analytics or IBM Coremetrics Free vs. Pay (8K to 12K per yr, base) Public (Google Server) vs. Private data (Own Server) No service vs. Dedicated service Basic Features vs. Advanced Features Aggregated data vs. Individual data No Integration vs. Multiple integrations10/2/2012 Jean-François Bélisle, 2012 © 22
  23. 23. 2.4 Google Analytics Premium or IBM Coremetrics Or10/2/2012 Jean-François Bélisle, 2012 © 23
  24. 24. Section 3 – Data Gathering10/2/2012 Jean-François Bélisle, 2012 © 24
  25. 25. 3.1 CookiesCookies: “A cookie is a piece of text that a Web server can store on a users hard disk. Cookies allow a website to store information on a users machine (computer, smartphone, console) and later retrieve it. The pieces of information are stored as name-value pairs.” (Marshall Brain, www.HowStuffworks.com)10/2/2012 Jean-François Bélisle, 2012 © 25
  26. 26. 3.2 Cookies & Google AnalyticsGoogle Analytics ->"page tag“ = Google Analytics Tracking Code (GATC)GATC: Snippet of JavaScript code that the user adds onto every page of his or her website. This code collects visitor data and sends it to a Google data collection server as part of a request for a web beacon (Taken from wikipedia.org).In addition to transmitting information to a Google server, the GATC sets first party cookies on each visitors computer.10/2/2012 Jean-François Bélisle, 2012 © 26
  27. 27. 3.3 Cookies & Google Analytics (2) CTRL + U on Chrome or Firefox10/2/2012 Jean-François Bélisle, 2012 © 27
  28. 28. 3.4 Cookies’ UsefulnessThrough cookies, a company can know:  How many visitors came;  How many new visitors vs. returning visitors;  How many times a visitor has visited the website.10/2/2012 Jean-François Bélisle, 2012 © 28
  29. 29. 3.5 Problems with Cookies3 major problems with cookies:1. Many users may share a machine;2. Cookies can be erased;3. Many users connect to a website using different machines (iPhone, Desktop Computer, Laptop).10/2/2012 Jean-François Bélisle, 2012 © 29
  30. 30. Section 4 – Key Terms in Web Analytics10/2/2012 Jean-François Bélisle, 2012 © 30
  31. 31. 4.1 Basic Key TermsVisit or session: When a user views a page or a series of web pages viewed in sequence during a specified time.Unique visitors: A user or group of users who have the same IP address, which views a page or a consecutive series of web pages. The same visitor may visit more than once the same website, but it is always the same visitor.10/2/2012 Jean-François Bélisle, 2012 © 31
  32. 32. 4.2 Other Basic Key TermsPage views: Refers to the number of times a Web page is displayed in a web browser.Returning visitors: Refers to one or more users who visit a website for the second time or more, with the same IP address.10/2/2012 Jean-François Bélisle, 2012 © 32
  33. 33. 4.3 Keep On Going Man …10/2/2012 Jean-François Bélisle, 2012 © 33
  34. 34. 4.4 Last Batch of Key TermsHome page: Page you defined as the “root” of your website.Landing page: Page where users enter your website.Conversion: When a user reaches a target set by the company (e.g. the user buys your product, the user subscribes to your newsletter)10/2/2012 Jean-François Bélisle, 2012 © 34
  35. 35. Section 5 – Introduction to KPIs10/2/2012 Jean-François Bélisle, 2012 © 35
  36. 36. 5.1 KPIs – A definitionKPIs (Key Performance Indicators): Financial and nonfinancial measures or parameters used to help an organization define and measure their success in terms of progress towards achieving their objectives.How to proceed: Advocates the use of ratios, percentages and averages rather than raw data. Advocates the use as a lever of tachometers, thermometers and projections, rather than pie charts and bar graphs. Provides a temporal context and identifies the changes rather than presenting data tables. Influence the decisions of a company.10/2/2012 Jean-François Bélisle, 2012 © 36
  37. 37. 5.2 KPIs vs. Raw Data• 100 people have purchased products on your website last month.• So what? In which context?• 100 people on 10 000 visitors -> Conversion rate of 1%.• 100 people compared to the 200 of last month -> Decreased in the number of buyers by 50%.10/2/2012 Jean-François Bélisle, 2012 © 37
  38. 38. 5.3 Method by Objectives Type of website Objectives KPIs Decision10/2/2012 Jean-François Bélisle, 2012 © 38
  39. 39. 5.4 Types of WebsitesTypes of web sites1. Content2. Marketing3. Sales4. Support10/2/2012 Jean-François Bélisle, 2012 © 39
  40. 40. 5.5 ObjectivesKPIs should answer managerial objectives which are SMART.1. Specific2. Measurable3. Achievable4. Really Useful5. Time Dependent10/2/2012 Jean-François Bélisle, 2012 © 40
  41. 41. 5.6 KPIs Really useful? « Any KPI that, when it changes suddenly and unexpectedly, does not inspire someone to send an email, pick up the phone or take a quick walk to find help, is not a KPI worth reporting » – Eric T. Peterson –10/2/2012 Jean-François Bélisle, 2012 © 41
  42. 42. 5.7 One Objective, one KPITypes of objectives:1. Related to revenue sources2. Related to cost3. Related to loyalty4. Related to traffic5. Related to conversion funnel6. Etc …10/2/2012 Jean-François Bélisle, 2012 © 42
  43. 43. 5.8 Types of KPIsKPIs related to:1. Averages2. Percentages3. Ratio4. Rates10/2/2012 Jean-François Bélisle, 2012 © 43
  44. 44. 5.9 Some KPIsBrief selection:1. Bounce Rate2. Average Cost per Conversion3. Average Order Value4. Percent Revenue from New Returning Visitors and Customers5. Order Conversion Rate6. Order Conversion Rate per campaign7. Average Time to Respond to Email Inquiries8. Cart Completion Rate9. Checkout Start Rate10. Form Completion Rate10/2/2012 Jean-François Bélisle, 2012 © 44
  45. 45. 5.10 Importance of Presentation Vs.10/2/2012 Jean-François Bélisle, 2012 © 45
  46. 46. 5.11 Some Tips for Presentation1. Run comparisons over time2. Use colors and arrows3. Always show the percentage change from one period to another4. Establish guidelines5. Set clear goals10/2/2012 Jean-François Bélisle, 2012 © 46
  47. 47. 5.12 Presentation Format Excel Sheets Or Dashboards10/2/2012 Jean-François Bélisle, 2012 © 47
  48. 48. 5.13 Conversion Funnels & GAConversion Funnels: Method for identifying each step closer to a user’s conversion on a website. http://www.youtube.com/watch?v=IibCs23EuiE10/2/2012 Jean-François Bélisle, 2012 © 48
  49. 49. 5.14 GA Multi-Channel Funnels http://www.youtube.com/user/googleanalytics#p/u/17/Cz4yHOKE5j810/2/2012 Jean-François Bélisle, 2012 © 49
  50. 50. 5.15 GA Segmentation http://www.youtube.com/watch?v=yvkvMjPJXmM10/2/2012 Jean-François Bélisle, 2012 © 50
  51. 51. Section 6 – Strategic Issues10/2/2012 Jean-François Bélisle, 2012 © 51
  52. 52. 6.1 HiPPOs Highest Paid Person’s Opinion10/2/2012 Jean-François Bélisle, 2012 © 52
  53. 53. 6.2 Number of KPIs for each type of strategistThe higher the person in the company’s hierarchy:• The less time he/she has;• The more interest is in KPIs related to ROI;• The more the number of KPIs presented should be lower.Number of KPIs for each type of strategist:• Senior strategists: 2 to 5• Middle Class strategists: 5 to 7• Tactical resources: 7 to 1010/2/2012 Jean-François Bélisle, 2012 © 53
  54. 54. Section 7 – Nirvana of Methods10/2/2012 Jean-François Bélisle, 2012 © 54
  55. 55. 7.1 Triangulation of MethodsThree methods to gather data1. Web Analytics2. A/B Testing3. Usability tests10/2/2012 Jean-François Bélisle, 2012 © 55
  56. 56. 7.2 A/B Testing: DefinitionWhen you test several different versions of a Web site (an advertisement, email, etc ...)… and you take the version that gives you the best results from your dependent variable perspective (i.e. conversion rates, registration rates, etc ...)10/2/2012 Jean-François Bélisle, 2012 © 56
  57. 57. 7.3 A/B Testing: An Example 1 2 Inscrivez-vous maintenant!10/2/2012 Jean-François Bélisle, 2012 © 57
  58. 58. 7.4 Multivariate Testing: DefinitionThe process by which more than one component of a website maybe tested in a live environment. It can be thought of in simple termsas numerous A/B tests performed on one page at the same time. A/Btests are usually performed to determine the better of two contentvariations; multivariate testing can theoretically test theeffectiveness of limitless combinations.10/2/2012 Jean-François Bélisle, 2012 © 58
  59. 59. 7.5 A/B Testing: Tools Google Analytics IBM Coremetrics Adobe Omniture Content experiments Marketing Center Test & Target module in module in Google module in Coremetrics Adobe Omniture Analytics10/2/2012 Jean-François Bélisle, 2012 © 59
  60. 60. 7.6 Usability Tools – Morae http://www.youtube.com/watch?v=gTfdeUGEc3E10/2/2012 Jean-François Bélisle, 2012 © 60
  61. 61. 7.7 Usability Testing: Tealeaf Tealeafs customer experience management (CEM) solutions empower companies to optimize ebusiness by eliminating the obstacles that block successful conversions or completion of business processes.10/2/2012 Jean-François Bélisle, 2010 © 61
  62. 62. 7.8 Usability Testing: Tealeaf (2)10/2/2012 Jean-François Bélisle, 2010 © 62
  63. 63. 7.9 Usability Testing: Tealeaf (3) http://www.tealeaf.com/products/customer-behavior-analysis- suite/cximpact.php (Watch CEM Overview)10/2/2012 Jean-François Bélisle, 2010 © 63
  64. 64. Section 8 – Some Resources10/2/2012 Jean-François Bélisle, 2012 © 64
  65. 65. 8.1 Some Readings Web Analytics Demystified (Free) & The Big Book of Key Performance Indicators (Free) By Eric T. Peterson http://www.webanalyticsdemystified.com/content/index.asp Web Analytics 2.0 By Avinash Kaushik10/2/2012 Jean-François Bélisle, 2012 © 65
  66. 66. 8.2 Some Readings (Cont’ed) Always be Testing By Bryan Eisenberg Advanced Web Metrics with Google Analytics By Brian Clifton10/2/2012 Jean-François Bélisle, 2012 © 66
  67. 67. Hope you Enjoyed and Have a Good Night Everyone! Jean-François Bélisle, MSc, PhD© LinkedIn: www.linkedin.com/in/jfbelisle Twitter: www.twitter.com/jfbelisle Website: http://jfbelisle.com10/2/2012 Jean-François Bélisle, 2012 © 67

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