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Web Analytics & Site matrix
Web Analytics in e-Commerce 2 Web Analytics Overview 3 1 Reasonable but not Best Practice: KPIs 3 3
Web analytics  is the measurement, collection, analysis and reporting of internet data for purposes of understanding and optimizing web usage. ------WAA Web analytics  is the vehicle help us to improve website, enhance marketing performance based on massive data but not personal experiences, when you don’t have genius like Jobs,  史玉柱 . ------Dave  Visitors, Customers Web Analytics  (User Behavior & Experience) Output: Decision Supportable Info Web Analytics User Behavior Purchase Behavior
Governance Standards Data model Communications Process models Integration points Methodology Hire ”expert” Build virtual team Create RFP Choose vendor Tag content Promotion Change management Execute tests Instrumentation Research KPI’s Calibrate metrics Train users Customize reports Monitor process / data infrastructure Role tasks Metrics Privacy policy Business case Funding Segments Learn what and why Test and measure Interpret results Recommend and take action Measure ROI Business Objective Plan Build Operate Use Vision
Web Metrics Hits Top 10 pages Browser stats Referring links Top entry/exit Keywords Top spiders Capacity Security Where are you? Where do you need to be? Timeline: 1 year/level Level 1 (95%) Level 3 (40%) Level 4 (10%+) Behavior Optimization Path  navigation Multiple session view Funnel analysis A/B MV  testing Dashboards E-Marketing Merchandising Segmentation SEO Campaign optimization: keywords, banners, e-mail Personals KPI alerts CRM Multi-channel aggregation Cost-shifting analysis Lifetime value Personalization Analytics-based content serving Process analytics (decision support) Level 2 (30%) Level 5 (5%-) BI/Corporate Performance Management Multi-channel  sales reports Activity-based costing Balanced scorecards Strategic planning Percentages refer to subjective measures of enterprise maturity (Surveyed in Q1 2008) IT-driven, “feel good” information, few decisions minimal value  Business-driven, working on metrics accuracy and process Optimizing the channel  360-degree view of customer  Strategic web
Click Through Conversion Rate Click Stream Participate
 
Internal Search Search Success Search Fail Similar/De-active Item Conversion / Abandonment Conversion Rate Browsers/Visitors Last keywords? Navigation?
Design Product Location Impressions Click Through Rate Conversion Rate Sales
Metrics 3:  Shopping Cart Abandonment Rate Metrics 1:  % to checkout process Metrics 2:  Conversion Rate Abandonment Rate Attach Rate Path Analysis Click Stream/Through What you can do:  Cart -> * -> Cart Cart -> Checkout What you can do:  Entrance and Exit monitor Conversion Rate Analysis for Exits What you can do:  Monitor by category Remind visitors cart status before they leave What you can do:  For those that have recommendations
Visitor Browser Prospect Customer Repeat Shopping Cart Login Address Payment Order Funnel / Path Analysis % to next step CR
Thanks for your time! Blog:  http://hi.baidu.com/hpzheng1982 QQ:  19624038 MSN:  [email_address] Org.:  http://www.wachina.net Let’s enjoy the loneliness of analytics!   -----Amanda  In the land of ass-less  the half-ass is king.

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Web Analytics & Site matrix

  • 2. Web Analytics in e-Commerce 2 Web Analytics Overview 3 1 Reasonable but not Best Practice: KPIs 3 3
  • 3. Web analytics is the measurement, collection, analysis and reporting of internet data for purposes of understanding and optimizing web usage. ------WAA Web analytics is the vehicle help us to improve website, enhance marketing performance based on massive data but not personal experiences, when you don’t have genius like Jobs, 史玉柱 . ------Dave Visitors, Customers Web Analytics (User Behavior & Experience) Output: Decision Supportable Info Web Analytics User Behavior Purchase Behavior
  • 4. Governance Standards Data model Communications Process models Integration points Methodology Hire ”expert” Build virtual team Create RFP Choose vendor Tag content Promotion Change management Execute tests Instrumentation Research KPI’s Calibrate metrics Train users Customize reports Monitor process / data infrastructure Role tasks Metrics Privacy policy Business case Funding Segments Learn what and why Test and measure Interpret results Recommend and take action Measure ROI Business Objective Plan Build Operate Use Vision
  • 5. Web Metrics Hits Top 10 pages Browser stats Referring links Top entry/exit Keywords Top spiders Capacity Security Where are you? Where do you need to be? Timeline: 1 year/level Level 1 (95%) Level 3 (40%) Level 4 (10%+) Behavior Optimization Path navigation Multiple session view Funnel analysis A/B MV testing Dashboards E-Marketing Merchandising Segmentation SEO Campaign optimization: keywords, banners, e-mail Personals KPI alerts CRM Multi-channel aggregation Cost-shifting analysis Lifetime value Personalization Analytics-based content serving Process analytics (decision support) Level 2 (30%) Level 5 (5%-) BI/Corporate Performance Management Multi-channel sales reports Activity-based costing Balanced scorecards Strategic planning Percentages refer to subjective measures of enterprise maturity (Surveyed in Q1 2008) IT-driven, “feel good” information, few decisions minimal value Business-driven, working on metrics accuracy and process Optimizing the channel 360-degree view of customer Strategic web
  • 6. Click Through Conversion Rate Click Stream Participate
  • 7.  
  • 8. Internal Search Search Success Search Fail Similar/De-active Item Conversion / Abandonment Conversion Rate Browsers/Visitors Last keywords? Navigation?
  • 9. Design Product Location Impressions Click Through Rate Conversion Rate Sales
  • 10. Metrics 3: Shopping Cart Abandonment Rate Metrics 1: % to checkout process Metrics 2: Conversion Rate Abandonment Rate Attach Rate Path Analysis Click Stream/Through What you can do: Cart -> * -> Cart Cart -> Checkout What you can do: Entrance and Exit monitor Conversion Rate Analysis for Exits What you can do: Monitor by category Remind visitors cart status before they leave What you can do: For those that have recommendations
  • 11. Visitor Browser Prospect Customer Repeat Shopping Cart Login Address Payment Order Funnel / Path Analysis % to next step CR
  • 12. Thanks for your time! Blog: http://hi.baidu.com/hpzheng1982 QQ: 19624038 MSN: [email_address] Org.: http://www.wachina.net Let’s enjoy the loneliness of analytics! -----Amanda In the land of ass-less the half-ass is king.