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Webanalytics with Microsoft BI

Google Analytics is the most popular web analytics system. Almost every webpage, whether it’s a private blog or large e-commerce site, uses Google Analytics. This session will cover essential information about Google Analytics and its API guidelines, competitors, and most important, how you can use the data from such offerings together with your ERP, CRM, and other OLTP systems. You will see how to load Google Analytics data using SQL Server Integration Services, for example, and merge that data with your local data. In addition, we will walk through a demonstration of important web analytics KPIs and how you can analyze them using Microsoft Business Intelligence tools

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Webanalytics with Microsoft BI

  1. 1. Web Analytics with Microsoft BI Oliver Engels Tillmann Eitelberg
  2. 2. About us… 6/14/2014 | Footer Goes Here2 |  CEO of oh22data AG  PASS Regional Mentor Germany  President PASS Germany  Chapter Leader Frankfurt, Germany  Microsoft MVP  Microsoft vTSP Oliver Engels Tillmann Eitelberg  CTO of oh22information services GmbH  PASS Regional Mentor Germany  Vice-president PASS Germany  Chapter Leader Cologne/Bonn, Germany  Microsoft MVP
  3. 3. PASS Germany – 27. - 28.06.2014
  4. 4. Agenda • Why Web Analytics? • Google Analytics – an overview • Additional Web Analytic Systems • Google Analytics API • Google Analytics and SSIS • Metrics for Web Controlling • Merging Google Analytics with your DWH • What’s coming next 6/14/20144 |
  5. 5. Take aways • What is the benefit of Web Analytics • Know the key player in the market • Understand the capabilities of Google API • See how to integrate into the MS BI Stack with SSIS • Get an overview on metrics for Webcontrolling • See how MS Power BI Tools work with Web Analytics data
  6. 6. Why Web Analytics? How are visitors using my site? Where and why are visitors abandoning my shopping cart? How can I make my marketing campaigns more effective? Am I creating effective content? How do I improve site interaction?
  7. 7. Why Web Analytics? • Web analytics provides valuable insight on your visitors • Make decisions based on actions by real people, rather than blind speculation • Track and measure results – fine tune your strategy, do more of what works, stop doing what doesn't work • Test different options to improve ROI
  8. 8. Why Web Analytics? – Some Examples • Which keywords are the most searched/most competitive in your sector? • Which Adwords campaigns are actually converting profitably? • Are people finding the information on my site that they’re looking for? • Do visitors click on the things that you want/expect them to? • Have your key competitors got better inbound links than you? • How do people find your website? • Which pages on your site encourage conversation? • How do your competitors get higher rankings in the search engines?
  9. 9. Google (Universal) Analytics
  10. 10. Google Analytics DEMO
  11. 11. Additional Web Analytic Systems • Bing ( • Piwik • AWStats • Open Web Analytics
  12. 12. Bing Webmaster
  13. 13. Piwik
  14. 14. PIWIK DEMO
  15. 15. AWStats
  16. 16. Open Web Analytics - Dashboard
  17. 17. Open Web Analytics – Click Heatmap
  18. 18. Open Web Analytics – Geo.location
  19. 19. Woopra - Real-time Analytics
  20. 20. Real-time Analytics DEMO
  21. 21. Top 10 Traffic Analysis Tools / May 05, 2014 If a website use a traffic analysis tool, more then 80% will use Google Analytics
  22. 22. Traffic Analysis Tools Market Share
  23. 23. Google Analytics API • Core Reporting API V2 • Core Reporting API V3 • Core Management API V3 • Dimension & Metrics • Limits and Quotas • Upload Cost Data
  24. 24. Management API - Conceptual Overview
  25. 25. Management API oh22data AG Account Property Profile
  26. 26. Core Reporting API • query the Core Reporting API for Google Analytics report data • requires a view (profile) ID, a start and end date, and at least one metric • additional query parameters • Dimensions • Filters • Segments
  27. 27. Understanding filter • Filtered queries restrict the rows that do (or do not) get included in the result • Supply a dimension or metric on which to filter • Each row in the result is tested against the filter • You can filter for a dimension or metric that is not part of your query
  28. 28. Understanding segments • Segments let you isolate and analyze subsets of visits and users • Visit data is confined to user behavior within a single visit • User data spans all visits within the date range you’re using, up to 90 days • You can create segments based on dimensions, metrics, visit date, and sequences of action • Cohorts (Date of First Visit option) are limited to maximum range of 31 days • Import Segments via Gallery
  29. 29. Understanding segments  Example: Specific users, all visits across a date range Filter users, no filters on visits Users whose cumulative revenue across all visits in a date range is greater than $1000 OR Only users who viewed a product page, then the shopping cart page, but not the confirmation page for having completed the order
  30. 30. Understanding segments
  31. 31. Understanding segments
  32. 32. Google Analytics Query Explorer 2 • play with the Core Reporting API • build queries to get data from your Google Analytics views (profiles) • use these queries in any of the client libraries
  33. 33. Google Analytics Query Explorer 2
  34. 34. SSIS Google Analytics Source  Why: • Need for advanced and customized analytics based on Google data • But: limited export functionalities (CSV, TXT, Excel) • Option for integrating Google data in your internal Business Intelligence systems Therefore:  Connector for Google Analytics as a data source for SQL Server Integration Services
  35. 35. SSIS Google Analytics Source
  36. 36. SSIS Google Analytics Source
  37. 37. SSIS Google Analytics Source Metrics Dimensions
  38. 38. SSIS Google Analytics Source
  39. 39. SSIS Google Analytics Source
  40. 40. SSIS Google Analytics Source DEMOCombine different Google Analytics Profiles
  41. 41. SSIS Google Analytics Source Iterate through months and years Iterate through GA profiles
  42. 42. SSIS Google Analytics Source DEMOUsing Microsoft Data Quality Services to standardize data stream
  43. 43. SSIS Google Analytics Source Cleaning up the "Source" dimension for better analysis
  44. 44. SSIS Google Analytics Source
  45. 45. SSIS Google Analytics Source Original Data Cleaned Data 0 50000 100000 150000 200000 250000 Visits new Visits 0 50000 100000 150000 200000 250000 Visits new Visits
  46. 46. SSIS Google Analytics Source Original Data Cleaned Data 0 500 1000 1500 2000 2500 3000 3500 Visits new Visits 0 500 1000 1500 2000 2500 3000 3500 4000 Visits new Visits
  47. 47. SSIS Google Analytics Source DEMOLeverage Google Analytics Data with Microsoft Power Map
  48. 48. Leverage Google Analytics with Microsoft Power Map
  49. 49. Leverage Google Analytics with Microsoft Power Map
  50. 50. Leverage Google Analytics with Microsoft Power Map
  51. 51. Leverage Google Analytics with Microsoft Power Map
  52. 52. Metrics for Web Controlling Information Transaction Communication Integration Value for business Complexity
  53. 53. Metrics for Web Controlling Pageviews Visits / Visitors Bounces Stickiness Time on page Visit time Depth of visit Frequency Recency Information Contacts & Request Registrations Comments Quality of comments Rating Searchterms Recommendations Reaction Communication Conversion-rate WS-to-Product-Page-rate Click-to-Basket-rate Basket-to-Buy-rate Order / ReOrder-rate Abandonment-rate New/First-Time Buyer Order recency / frequency Financials Transaction Prosumer Registrations Logins Integrators Personalisation Key Customers Relationship Integration Web Content Controlling Web Content Controlling >>>MaturityofeBusiness>>>
  54. 54. SSIS Google Analytics Source DEMOLeverage Google Analytics Data with Power View
  55. 55. Leverage Google Analytics Data with Power View
  56. 56. Leverage Google Analytics Data with Power View
  57. 57. Leverage Google Analytics Data with Power View
  58. 58. Leverage Google Analytics Data with Power View
  59. 59. Merging Google Analytics with your DWH • Do better analysis about online behavior and offline conversion • Tie long-term purchase history to online behavior • Create custom marketing segments • Include web funnel data from your website into the data warehouse • Get a complete picture of your user acquisition and retention
  60. 60. What's coming next • Google BigQuery • Real-time big data analytics in the cloud • Ad hoc queries on multi-terabyte datasets • Familiar SQL-like query syntax • Ability to JOIN enormous fact tables to most lookup tables • HTTP REST API • Easy integrate Google Analytics Premium data