1. Metrics for Performance Measurement in E-Commerce MARK 3030 – Week 10

2. Sourced Materials: © 2006 Pearson Education Canada Inc. Agenda Why Measure? What to Measure? Traffic and Site Usage Metrics Marketing Metrics Financial Metrics Other Performance Metrics Multi-dimensional Scorecards Sources of Information

3. Why Measure? improving understanding of business model helping to communicate corporate strategy motivating performance analyzing actual performance increasing accountability “if you don't measure it, you cannot manage it” A key competency of the accounting profession, and a great opportunity to add value by…

4. Aligning Metrics with Business Objectives Maximize Traffic Maximize Sales Increase Market Share Minimize Transaction Costs Maximize Return on Investment Balance Multiple Competing/Conflicting Objectives A business may have different objectives at different times in its life.

5. Limitations of Metrics Strategies rapidly changing Online measures can be ambiguous e.g., is site stickiness good or bad? Measurement requires resources Vulnerable to integrity/confidentiality problems “In” Metrics rapidly changing hits>page views>conversion rates

6. Site Traffic Analysis Site Traffic General measurements of site’s activity Site Usage (Spatial) Traffic Breakdown by Section Site Usage (Temporal) Traffic Breakdown by Time Site Usage (Context) Traffic Breakdown by Platform, OS etc. Referrer Analysis Traffic Breakdown by Source

7. Site Traffic Analysis - 2 Hits: A request of an element (page, graphics element etc.) from the Web Server Page Views: A full page request by a single user, including all page’s elements Ad Views, Ad Impressions or Banner Impressions: The number of times a page with a banner ad is viewed. Ad Click-Throughs, Ad Conversions: The number of times a page with a banner ad is clicked on. Visit/User Session: A stream of page requests from a single user constitutes a “visit”. Unique Visitors: Non-repeating visitors in a specific timeframe

8. Site Usage (spatial) Top Entry Pages Top Exit Pages Most Visited Pages Least Visited Pages Single Visit Pages Paths within Site

9. Site Usage (temporal) Traffic breakdown by Month Traffic breakdown by Week Traffic breakdown by Day of Week Traffic breakdown by Hour

10. Site Usage (context) Other information that can be retrieved from log file: Most Used Browsers/Browser Versions Most Used Operating Systems/OS Versions Most Used Platforms (Apple, PC)

11. Marketing Metrics Referrer Analysis Location Analysis Visitor’s/shopper’s breakdown by geographical origin Customer Profile Analysis Visitor’s/shopper’s breakdown by profile attribute Shopping Basket Analysis Items purchased made in a sample transaction

12. Referrer Analysis Log file contains information about last visited URL Top referrer URLs indicate where traffic is coming from Useful to measure effectiveness of advertising campaigns

13. Location Analysis has great importance for marketing, since some promotions/advertising have regional reach. In absence of explicit data, rough location can be inferred by IP address Gaining GREATER importance with the arrival of ‘Geo-Targeting’ and ‘Geo-Location’ technologies associated with the rise in mobility in society. Foursquare

14. Customer Profile Analysis Explicit Information surrendered by the user when subscribing to a service, making a purchase, completing a survey form, etc; e.g. Name, Address, Marital Status Implicit (clickographic) Information inferred from the user’s actions and/or purchase history; e.g. Favorite Color, Age group, Preferred Topics

15. Shopping Basket Analysis Is the analysis of the items purchased during an individual transaction Itemsets are sets of items that appear together in many transactions Knowledge of itemsets and their frequency can be used to improve product placement or for cross-sell, up-sell and bundles.

16. Financial Metrics Revenue Expenses ROI

17. Revenue Streams Gross Margin on Sales: e.g.,5% to 50% Advertising: e.g., $5 to $40 CPM Affiliate Commission: e.g., 15% of clickthrough order

18. Revenue Metrics Global Sales Analysis Breakdown of Sales per period, Product Category, Referrer, Time of the day etc. Product Sales Analysis Top selling Products, Least Selling Products Shopper Analysis Sales by Shopper Profile, Demographics, Geographical Location etc. Advanced Analytics Product Clusters, Purchase Patterns, Prediction

19. Other Performance Metrics Network/system availability System response time Transaction processing Accuracy Timeliness Help desk responsiveness Security incidents Customer satisfaction etc.

20. Kaplan & Norton’s Balanced Score Card Customer Market share Traffic analysis Shopping analysis Acquisition cost Awareness Satisfaction/Loyalty Learning & Growth Employee capabilities Motivation Internal Process Innovation Operations system reliability Post sale service Financial Revenues ROI

21. Example of a Balanced Scorecard for an E-Business

22. Customers Are the Primary Source of Data Users Browsing Site Users Clicking on Ads Users Interacting with Surveys/Polls Users Open ‘Apps’ on mobile devices Shoppers Making Product Selections Users Filling Out Forms Shoppers Making Purchases Shoppers Contacting Customer Service Shoppers movements can be tracked via geo-location technologies

23. Server-Stored Data (cont’d) Transaction Database Contains a record of all transactions, including products purchased, amounts transferred, etc. User Profile Database Contains data about registered visitors and shoppers Explicit Data: data inserted by the user (through forms) Implicit Data: data inferred by analysis of user’s behavior

24. Illustrative Example Add high value customers Increase revenue per customer Reduce cost per customer FinancialRev by productRev by cust Cost per customer Customer# of new customers Cust satisfaction Cust attrition rate Internal ProcessCust claims re: errors Availability Response time Acquisition cost per cust Learning & Growth Quality of new employees Help desk training # Self-service innovations