Lecture E-Commerce - Chapter 15: E-commerce marketing (part III)

CSC 330 E-Commerce
Teacher

Ahmed Mumtaz Mustehsan
GM-IT CIIT Islamabad

Virtual Campus, CIIT
COMSATS Institute of Information Technology

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E Commerce Marketing
Chapter-06
Part -III

For Lecture Material/Slides Thanks to: Copyright © 2010 Pearson Education, Inc

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The Revolution in Internet Marketing
Technologies
Internet marketing technologies:
1.Web Transaction logs
2.Tracking files
3.Databases, Data warehouses, Data mining
4.Customer Relationship Management systems (CRM)

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1. Web Transaction Logs
 Built

into Web server software
 Record user activity at Web site
 Webtrends: Leading log analysis tool
 Provides much marketing data, especially combined
with:

◦Registration forms: Gather personal data on name,
address, phone, zip, e-mail, and other optional
information on interest and tastes
◦Shopping cart database: captures all the item
selection, purchase and payment data)

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1. Web Transaction Logs
Transaction log coupled with Registration Forms and
shopping cart provides treasure of marketing information
leads to answer some interesting questions such as:
What are major patterns of interest and purchase?
After home page, where do users go first? Second?
What are the interest of specific individuals?
How can we improve the website, easier to use,
attractive design encourage visitors to purchase?
Where are visitors coming from? What they want?
How can we personalize our messages etc?

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2. Tracking Files
Under this technique user’s browsing activities are
tracked as they move from site to site
Different types of tracking files
Cookies
◦Small text file (1 kb) placed by Web site on visitor’s
machine.
◦Allows Web marketers to gather data stored in
cookies.
◦First-party cookies same domain name the user is
visiting.
◦Third-Part cookies serving or adware companies,
marketers or spyware.
◦Customers may delete cookies. Implement privacy;
Causing misleading analysis, wastage of efforts.
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2. Tracking Files
 Use Adobe

Flash software; creates cookies called
Flash Cookies set to never expire (5 MB).
 Used to recreate cookies deleted by user.
 Combined with web-bugs they can create cross-site
web profiles.
 Beacons (“bugs”; 1-pixel graphic files); embedded in
the e-mail messages.
 web-bugs send message to server that e-mail was
opened by the users. i.e. the user was at least
interested in subject message.
 1-pixel in size that contains the URL of the server
other that one served the page.

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3. Databases
Database:
 A software application that stores records and attributes
Database management system (DBMS):
Software application used by organizations to create,

maintain, and access databases
SQL (Structured Query Language):
An industry-standard database query and manipulation
language used in a relational database
Relational database:
Represents data as two-dimensional tables with records
organized in rows and attributes in columns; data within
different tables can be flexibly related as long as the
tables share a common data element
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Relational Database View of E-commerce Customer

In RDB the data generated from an e-commerce site is stored on the
HD and presented to the managers of the site in the form of
interrelated tables
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3. Data Warehouses and Data Mining

Data warehouse:
Is a database that collects firm’s
transactional/operational and customer data in single
location for offline analysis by marketers and site
managers
Data mining:
A set of analytical techniques to find patterns in data,
of database or in a data warehouse, or seek to model
behavior of customers, to develop customer profiles.
Four types of Data mining are:
◦Query-driven data mining
◦Model-driven data mining
◦Rule-based data mining
◦Collaborative filtering

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3. Data Warehouses and Data Mining
Customer Profile: A description of a typical behavior of a

customer or a group of customers at a web site.
Query-driven data mining: Simplest; hunch of marketers
who suspect a relationship in DB.
Data mining based upon specific query; e.g. what is
the relationship between time of day and purchase of
various products? Or rank top 10 products! Sold in ever
hour.
Model-driven data mining
Use of model that analyze key variables of interest to
decision makers.
Example: Based upon financial model of profitability,
remove unprofitable items from inventory to save
archiving cost.
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3. Data Warehouses and Data Mining
Rule-based data mining
Examines demographic and transactional data of
groups and individuals at a website and attempts to
derive general rules of behavior for visitors.
Example:
Marketers propose filters for different segments for
example travelling plans during vocational periods.

Female who spend on average $50 per visit at
website and also viewed travel article might be
shown vocational travel advertisement.

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Data Warehouses and Data Mining
Collaborative filtering
Site visitors classify themselves into affinity groups
characterized by common interests; products are
then recommended based on what other people in
the group have recently purchased.
Example:
Marketers make filters on the basis of their own rule
of thumb; example query all people of the same
demographic group who purchase same products in
almost the same time period.
Extract lifestyle; opinion leaders or influencers.

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Data Mining and Personalization

SOURCE: Adomavicius and Tuzhilin, 2001b ©2001 IEEE.


4. Customer Relationship Management (CRM)
Systems
 Record

all contact that customer has with firm
 Generate customer profile available to everyone in firm
with need to “know the customer”
 Customer profiles can contain:
◦Map of the customer’s relationship with the firm
◦Product and usage summary data
◦Demographic and psychographic data
◦Profitability measures
◦Contact history
◦Marketing and sales information

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4.A Customer Relationship Management System

An example of CRM system for a financial services institution. System
capture customer info from all customer touch points and from other data
sources merge the data into a single aggregated database system. Applying
OLAP analyze the customer activities and behavior to determine profitable
or non profitable customer.
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Generic Market Entry Strategies


Figure 6-11, Page 391

Both new and traditional firms face a basic choice of click and bricks and
clicks when entering e-commerce marketplace

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Generic Market Entry Strategies
New Firms ; Quardent 1 & 2;
First Movers; started with the 1st Q; enjoyed monopoly;
(Amazo eBay etc.)
But for most of firms, it was short lived; due to limited
resources, lack of experience;
Successful big players done two things; 1. blocked the
competition 2. increased their audience.
Another possibility with new firms was to mixed play
(Q2) established bricks and clicks along with clicks.
most of the firms survived by establishing their joint
venture and alliance with already established big
traditional players offering them on-line presence.
Gained financial backing and experience.
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Generic Market Entry Strategies
Existing Firms ; Quardent 3 & 4;
Fast Followers; Traditional Firms having significan
cash flow and funds to support their e-commerce
venture. (Barnes & Noble, Rite Aid)
Followed the suits of successful first movers by
establishing their websites as independent firms making
use of their existing resources and experience.
The most common strategy of existing firms were to
extend their business online in addition to the traditional
firms from the very beginning. (Q4) (LL Beans, WalMart).
Today most firms are opening with mixed bricks-andclicks strategy with a hope of success.
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Establishing the Customer Relationship
Firm chooses a market entry; needs marketing strategy
for establishing relationship with customers:
Advertising networks
Ad server selects appropriate ad based on cookies,
Web bugs, backend user profile databases, user profile,
user behavior. Best known advertising network is

DoubleClick.com.
Big companies like Google and Microsoft are purchasing
these companies for further establishing their online
advertisement business. (Google purchased double click
$ 3.1 Billion
Advertising exchanges
Auction ad slots over many advertising networks, by
sharing the revenue with web sites usually called web
publishers. (Google, yahoo, eBay)
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How an Advertising Network
Such as DoubleClick Works

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Establishing the Customer Relationship
Permission marketing:
Market strategy in which companies obtain permission
from customers before sending them information or
promotional messages.
Affiliate marketing:
One website agrees to pay another website a
commission for new business opportunities it refers to the
site.
Amazon has more than 1 millions participants site called
associates which receive around 15% on sales their
referral generate.

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Establishing the Customer Relationship
Viral marketing
The process of getting customers to pass along the
company’s marketing messages to friends, family and
colleagues.
Blog marketing
Blogs are based upon personal opinion therefore
are ideal for viral marketing. Google AdSense is a

major Blog Marketers
Social network marketing
Driven by social e-commerce
◦Social sign-on
◦Collaborative shopping
◦Network notification
◦Social search (recommendation)
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Establishing the Customer Relationship
Social marketing and wisdom of crowds
Large aggregates produce better estimates and
judgments, e.g.,
◦“Like” button
◦Folksonomies
◦Social tagging
Mobile platform marketing
Local marketing
Brand leveraging
Using the power of an existing brand to acquire
new customers for a new product or service.

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Customer Retention
Mass marketing:
Based on national media messages aim at a single
national audience with a single national price.
Direct marketing:
which is based on direct mail or phone messages
and aimed at the segment of the market with little
price variations (special offer to loyal customers)
Micromarketing :
which is aimed at geographical units (neighborhood,
cities) or specialized market segment with the first
form of true database marketing.

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