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

1. Web Analytics with Microsoft BI
Oliver Engels
Tillmann Eitelberg

2. About us…
6/14/2014
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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. PASS Germany – 27. - 28.06.2014

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. 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. 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. 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. 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. Google (Universal) Analytics

10. Google Analytics
DEMO

11. Additional Web Analytic Systems
• Bing
https://ssl.bing.com/webmaster
(http://msdn.microsoft.com/en-us/library/hh969349)
• Piwik
http://piwik.org/
• AWStats
http://awstats.sourceforge.net/
• Open Web Analytics
http://www.openwebanalytics.com/

12. Bing Webmaster

13. Piwik

14. PIWIK
DEMO

15. AWStats

16. Open Web Analytics - Dashboard

17. Open Web Analytics – Click Heatmap

18. Open Web Analytics – Geo.location

19. Woopra - Real-time Analytics

20. Real-time Analytics
DEMO

21. Top 10 Traffic Analysis Tools
http://w3techs.com/technologies/overview/traffic_analysis/all / May 05, 2014
If a website use a traffic
analysis tool, more then
80% will use Google Analytics

22. Traffic Analysis Tools Market Share

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. Management API - Conceptual Overview
https://developers.google.com/analytics/devguides/config/mgmt/v3/

25. Management API
oh22data AG
www.oh22.net www.oh22.is
service.oh22.net customer.oh22.net dqs.oh22.is
Account
Property
Profile

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. 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. 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. 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. Understanding segments

31. Understanding segments

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. Google Analytics Query Explorer 2

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. SSIS Google Analytics Source

36. SSIS Google Analytics Source

37. SSIS Google Analytics Source
Metrics Dimensions

38. SSIS Google Analytics Source

39. SSIS Google Analytics Source

40. SSIS Google Analytics Source
DEMOCombine different Google Analytics Profiles

41. SSIS Google Analytics Source
Iterate through months and years
Iterate through GA profiles

42. SSIS Google Analytics Source
DEMOUsing Microsoft Data Quality Services to standardize data stream

43. SSIS Google Analytics Source
Cleaning up the "Source"
dimension for better analysis

44. SSIS Google Analytics Source

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. 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. SSIS Google Analytics Source
DEMOLeverage Google Analytics Data
with Microsoft Power Map

48. Leverage Google Analytics with Microsoft Power Map

49. Leverage Google Analytics with Microsoft Power Map

50. Leverage Google Analytics with Microsoft Power Map

51. Leverage Google Analytics with Microsoft Power Map

52. Metrics for Web Controlling
Information
Transaction
Communication
Integration
Value for business
Complexity

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. SSIS Google Analytics Source
DEMOLeverage Google Analytics Data with Power View

55. Leverage Google Analytics Data with Power View

56. Leverage Google Analytics Data with Power View

57. Leverage Google Analytics Data with Power View

58. Leverage Google Analytics Data with Power View

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. 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