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Google Analytics
                      vs
Adobe/Omniture SiteCatalyst
                      vs
In-house Web analytics system




  Roman Zykov, Head of analytics at Wikimart.ru
                  11.11.2011
Content

•   Background
•   General comparison
•   Wikimart’s system overview
•   Online advertising analysis
•   Product analysis
•   Direct profit of web analytics data (data feeds)
•   Implementation and support
•   Conclusion
Background

2004 – 2009 Head of analytics at Ozon.ru
2010 - …. Head of analytics at Wikimart.ru
• Business intelligence
• Web analytics
• Data science
General comparison*
            Field              GA   SiteCatalyst &   Inhouse
                                      Discover

     Commerce metrics          1          4            5

   Campaign management         2          5            3

      Excel integration        2          4            5

      Product analytics        2          5            4

      Ad-hoc analytics         2          4            5

        Data export            1          3            5

        Data import            0          2            5

* For large e-commerce sites
Wikimart system: JS Counter
Wikimart system: Data flow




                          Team
               •   Product analytics manager
               •   Web analyst
               •   ETL developer
               •   OLAP developer
               •   2 junior analysts
Wikimart system: Users
Excel (OLAP)




                   E-mail


                             Interactive Web
Online advertising analysis
Google Analytics:
• utm tags - standart de-facto

Omniture SiteCatalyst:
• s.campaign – standart campaign variable
• Custom independent commerce variables
• Campaign manager interface (costs, groups, timings)
• Excel export/import (Site, FTP, …)
• Easy regrouping
• Disadvantage: Paid/Non-paid traffic reports

In-house webanalytics:
• Utm tags
• Easy regrouping
Product analysis
Google Analytics:
• Events
• Custom variables

Omniture SiteCatalyst:
• Events
• Custom Pathing variable
• Custom independent commerce variables
• Merchandising analysis
• Discover
• Form analysis plugins, etc
• Customizable ClickMap

In-house webanalytics:
• Events
• Merchandising analysis
• Row SQL analysis
Merchandising analysis
Merchandising - clicks
Merchandising - Commerce
Omniture Discover
Data export & feeds
Google Analytics:
• Google data API (aggregated)
• Non-native excel client (excellentanlytics.com)

Omniture SiteCatalyst:
• Recommendation engine
• Automated FTP export (semi-aggregated)
• Native Excel client

In-house webanalytics:
• XML feeds
• Recommendation engine (Hadoop)
• OLAP (Excel) & Web client
Implementation & Support
Google Analytics:
• ga_debug.js
• Outsource consultant
• Non-flexible user access

Omniture SiteCatalyst:
• 24x7 support (phone, chat, e-mail)
• Account manager
• Business consulting group
• Excellent debugging tools
• Flexible user access


Inhouse webanalytics:
• JS debugging tool
• Data access to raw data
• Flexible user access
Wikimart’s JS debugger
Best choice
Google Analytics:
• The 1st web-analytics system on site
• Debugging data for other counters

Omniture SiteCatalyst (& Discover):
• Deep product analysis
• Manage more than 100 000 marketing campaigns

In-house webanalytics:
• Deep product analysis
• Data feeds
• Integration with offline data
Thank you

       E-mail: rzykov@gmail.com

              Blog: KPIs.ru

http://www.webmetric.org/start_download.php

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Google Analytics vs Omniture SiteCatalyst vs In-ouse Webanalytics at iMetrics

  • 1. Google Analytics vs Adobe/Omniture SiteCatalyst vs In-house Web analytics system Roman Zykov, Head of analytics at Wikimart.ru 11.11.2011
  • 2. Content • Background • General comparison • Wikimart’s system overview • Online advertising analysis • Product analysis • Direct profit of web analytics data (data feeds) • Implementation and support • Conclusion
  • 3. Background 2004 – 2009 Head of analytics at Ozon.ru 2010 - …. Head of analytics at Wikimart.ru • Business intelligence • Web analytics • Data science
  • 4. General comparison* Field GA SiteCatalyst & Inhouse Discover Commerce metrics 1 4 5 Campaign management 2 5 3 Excel integration 2 4 5 Product analytics 2 5 4 Ad-hoc analytics 2 4 5 Data export 1 3 5 Data import 0 2 5 * For large e-commerce sites
  • 6. Wikimart system: Data flow Team • Product analytics manager • Web analyst • ETL developer • OLAP developer • 2 junior analysts
  • 7. Wikimart system: Users Excel (OLAP) E-mail Interactive Web
  • 8. Online advertising analysis Google Analytics: • utm tags - standart de-facto Omniture SiteCatalyst: • s.campaign – standart campaign variable • Custom independent commerce variables • Campaign manager interface (costs, groups, timings) • Excel export/import (Site, FTP, …) • Easy regrouping • Disadvantage: Paid/Non-paid traffic reports In-house webanalytics: • Utm tags • Easy regrouping
  • 9. Product analysis Google Analytics: • Events • Custom variables Omniture SiteCatalyst: • Events • Custom Pathing variable • Custom independent commerce variables • Merchandising analysis • Discover • Form analysis plugins, etc • Customizable ClickMap In-house webanalytics: • Events • Merchandising analysis • Row SQL analysis
  • 14. Data export & feeds Google Analytics: • Google data API (aggregated) • Non-native excel client (excellentanlytics.com) Omniture SiteCatalyst: • Recommendation engine • Automated FTP export (semi-aggregated) • Native Excel client In-house webanalytics: • XML feeds • Recommendation engine (Hadoop) • OLAP (Excel) & Web client
  • 15. Implementation & Support Google Analytics: • ga_debug.js • Outsource consultant • Non-flexible user access Omniture SiteCatalyst: • 24x7 support (phone, chat, e-mail) • Account manager • Business consulting group • Excellent debugging tools • Flexible user access Inhouse webanalytics: • JS debugging tool • Data access to raw data • Flexible user access
  • 17. Best choice Google Analytics: • The 1st web-analytics system on site • Debugging data for other counters Omniture SiteCatalyst (& Discover): • Deep product analysis • Manage more than 100 000 marketing campaigns In-house webanalytics: • Deep product analysis • Data feeds • Integration with offline data
  • 18. Thank you E-mail: rzykov@gmail.com Blog: KPIs.ru http://www.webmetric.org/start_download.php