Metrics for Performance Measurement in E-Commerce

MARK 3030 – Week 10

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

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…

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.

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

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

Site Traffic Analysis - 2Hits: 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

Site Usage (spatial)

Top Entry Pages

Top Exit Pages

Most Visited Pages

Least Visited Pages

Single Visit Pages

Paths within Site

Site Usage (temporal)

Traffic breakdown by Month

Traffic breakdown by Week

Traffic breakdown by Day of Week

Traffic breakdown by Hour

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)

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

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

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 addressGaining GREATER importance with the arrival of ‘Geo-Targeting’ and ‘Geo-Location’ technologies associated with the rise in mobility in society. Foursquare

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

Shopping Basket Analysis

Is the analysis of the items purchased during an individual transaction

Itemsets are sets of items that appear together in many transactionsKnowledge of itemsets and their frequency can be used to improve product placement or for cross-sell, up-sell and bundles.

Financial Metrics

Revenue

Expenses

ROI

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

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

Other Performance Metrics

Network/system availabilitySystem response timeTransaction processing Accuracy Timeliness

Help desk responsivenessSecurity incidentsCustomer satisfactionetc.

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

Example of a Balanced Scorecard for an E-Business

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

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

Illustrative Example

Add high value customers

Increase revenue per customer

Reduce cost per customer

Financial Rev by product Rev by cust

Cost per customer

Customer # of new customers

Cust satisfaction

Cust attrition rate

Internal Process Cust claims re: errors

Availability Response time

Acquisition cost per cust

Learning & Growth

Quality of new employees

Help desk training

# Self-service innovations