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SMU MK0017-SLM-Unit-05
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e-Marketing Unit 5
Sikkim Manipal University Page No. 84
Unit 5 e-Marketing Data Collection and Handling
Structure:
5.1 Introduction
Objectives
5.2 Types of Data in e-Marketing
User Entry Data / Profiles
Web Documents and Web Meta Data
Server and Cookie Data
5.3 Knowledge Management for e-Marketing
5.4 Marketing Information Systems for e-Marketing
5.5 Marketing Intelligence Systems
5.6 Managing Database Systems
Data Warehouse
Data Mining
5.7 Online Experimental Research and Survey
5.8 Web Analytics
Web Server Log File Analysis
Page Tagging
5.9 Knowledge Management Metrics
5.10 Summary
5.11 Glossary
5.12 Terminal Questions
5.13 Answers
5.14 Case-let
5.1 Introduction
After studying the previous units you must be familiar with the plans and
strategies adopted in e-marketing and how it they are implemented.
This unit takes you to the next step and helps you to understand how to
manage information in e-marketing, the types of data that are available, the
intelligence systems and information systems for e-marketing and also
database systems, which include data ware house and data mining. It also
explains the knowledge management metrics, Web analytics and online
experimental research and survey.
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Objectives:
After studying this unit, you should be able to:
list the types of data applicable in e-marketing
explain knowledge management, information and intelligence systems
describe various data base systems
analyse online experiments research and survey
explain the role of web analytics
evaluate knowledge management metrics
5.2 Types of Data in e-Marketing
Let us see the types of data used in e-marketing, which are discussed here -
5.2.1 User Entry Data / Profiles
Gathering of data from visitors over a website on online forms is a very
popular way of getting user information. Usually the website visitor has to fill
in into these forms information like name, address, contact number, lifestyle
information and user interests so on.
This information, which is directly stored into a data base, is used later for
data mining. However, for a user, it is often tedious and time consuming to
answer all these questions. Therefore, on-line forms and questionnaires
should be created in such a way that they do not take much of the user‟s
time and that the user is motivated to give all the required answers.
5.2.2 Web Documents and Web Meta Data
Web documents Hypertext Mark-up Language (HTML) contain information
such as text, images, video or audio, which allow the users to recognise the
title of the page, keywords, the author and the main body.
Web metadata gives us the topology of a website, which is generally stored
as a side-specific index table implemented as a directed graph. These meta
data needs to be manually specified by the website administrator, which
becomes a very difficult job when it comes to large websites. Hence,
methods to annotate these documents automatically have been developed
in the recent past.
5.2.3 Server and Cookie Data
The server automatically generates the web server logs when a user visits a
Uniform Resource Locator URL. The server registers the Internet Protocol
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(IP) address of the visitor, the time at which the user entered the website,
the time duration of the visit, the requested URL and the URL visited. From
this information, the path where the user is going on the website can be
generated. Web server logs provide important information that can help to
determine the behaviour of the user at the website. However, the IP address
stored in the server log does not always lead to the particular user, since the
address might have been changed by the proxy server. Therefore, cookie
logs might be more preferable.
Cookies are short text files that are generated by the server on the client site
while the client‟s browser is visiting the website. Cookies allow setting a
special identification number or a code for a particular user. This code helps
to identify the user each time the user visits the website. However, to set a
cookie one needs the permission of the user, which is not always the case.
Therefore, a combination of server logs and cookie log will serve to be a
good basis for data mining.
Activity 1
Search for the cookies file(s) on your hard drive, by using the find file
function on your Microsoft PC. Do you see sites that you have never
visited? Is Double Click on the list? If so, visit the Double Click site to see
why.
Self Assessment Questions
1. User entries could be taken as ___________.
2. ___________ contain information such as text, images, video or audio.
3. Short text files are called _____________.
4. A combination of _________ and ____________ will be a good basis
for data mining.
5.3 Knowledge Management for e-Marketing
Knowledge management is getting progressively critical for the success of
companies in this emerging era of e-marketing. As business activities
increasingly shift to the web, the challenge facing corporate management is
maintaining competitive advantage by building strong relations with
employees, customers, and upstream/downstream suppliers and partners.
This is where a good knowledge management strategy comes into picture.
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Unfortunately, many companies use knowledge management technologies
that do not serve to solve the above challenge. Therefore, it is important to
understand and implement management programs that can help companies
to gain competitive advantage over others. However, most experts agree
that the biggest challenges of knowledge management are not technological
but human-based or behavioural challenges.
We will now see how companies can benefit by adopting strategies that
harness the potential of marketing knowledge management technologies to
transform their e-business activities.
First of all, let us know the definition of knowledge management and then try
to understand the driving and impeding forces that help and hinder proper
deployment of knowledge management strategies in e-marketing.
Why Knowledge Management?
70% of companies that participated in a research study said that their sales
growth strategy for the year will be focused on optimising the sales
progression. How would they do that? Allowing sales people to focus on
having conversations, rather than digging up the materials they need to
support the new relationships that they are building is one way of increasing
the efficiency. This is the area in which marketing and knowledge
management can assist.
Making sales is considered as a hard task. To be successful in sales, you‟ve
got to have a deep understanding of your products and services, keep track
of many relationships, understand market trends, and withstand a significant
amount of pressure. Added to this, many departments will be constantly
trying to interface directly with you, which can lead to an overwhelming
number of mixed messages. In response to this, salespeople often try to
cover up by selling the products that they are most comfortable with, which
is not necessarily good for the company or consistent with the larger
business strategy. Hence, a significant part of marketing comprises
empathising with the sales people (they are customers of marketing), and
trying to provide them with products and services that meet their needs and
make their lives better.
Knowledge management is one way to make the necessary preparations
quicker by keeping all the relevant assets in one place – for the use of the
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sales team. But, knowledge management is not just about making the
content accessible, it‟s about putting it in context, and improving its quality. It
is less about creating content and more about taking the collective
knowledge of the organisation and preparing it as a resource for the
organisation.
Self Assessment Questions
5. _____________ has become progressively more critical for the
success of companies in this emerging era of e-marketing.
6. A good knowledge management strategy can help in achieving the
organisational ______________.
7. Knowledge management is one way to make the necessary planning
________________.
5.4 Marketing Information Systems for e-Marketing
A Marketing Information System can be defined as 'a system in which
marketing information is formally gathered, stored, analysed and distributed
to managers in accordance with their informational needs on a regular basis'
(Jobber, 2007)
The system is created based on an understanding of the information needs
of marketing management. A Marketing Information System supplies all the
information that a marketing manager needs. The data is collected from the
marketing environment and transferred into the information system.
Marketing managers can use this information in their decision-making
processes.
A marketing information system has four components: the internal reporting
system, the marketing research system, the marketing intelligence system
and marketing models. Internal reports include orders received, inventory
records and sales invoices. Marketing research is a purposeful study –
either ad hoc or continuous. However, marketing intelligence is less specific
in its purposes, and is chiefly carried out in an informal manner. It is carried
out by managers themselves rather than by professional marketing
researchers.
Let us check out this definition of MIS -
"A marketing information system is a continuing and interacting structure of
people, equipment and procedures to gather, sort, analyse, evaluate, and
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distribute pertinent, timely and accurate information for use by marketing
decision makers to improve their marketing planning, implementation, and
control".
The main purpose of a Marketing Information System is to support
management decision making. You must be aware of the five distinct
functions of management – planning, organising, coordinating, decision
making and controlling. Each of these functions is supported by the MIS.
Figure 5.1 illustrates the major components of an MIS, the environmental
factors monitored by the system and the types of marketing decisions which
the MIS seeks to underpin.
As you can see in Figure 5.1, this model of MIS begins with a description of
each of its four main constituent parts: the internal reporting systems, the
marketing research system, the marketing intelligence system and the
marketing models. Though an MIS varies in its degree of sophistication due
to the fact that all the countries in the world are not extensively
computerised, it is recommended that a fully-fledged MIS has all the above
components.
Marketing
Environment
Markets
channels
competitors
Political
Legal
Economy
Technology
Internal Report
System
Marketing
Research System
Marketing
Intelligence
Systems
Marketing
Models
Strategic
Decisions
Control
Decisions
Operational
Decisions
Data
Marketing decision and communications
Information
Figure 5.1: The Marketing Information System and its Subsystems
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Information systems have to be designed to meet the way in which
managers tend to work. Research suggests that a manager continually
addresses a large variety of tasks and is able to spend relatively brief
periods on each of these. Given the nature of the work, managers tend to
rely upon information that is timely and verbal (because this can be
assimilated quickly), even if this is likely to be less accurate than more
formal and complex information systems.
Managers need to continually address a large variety of tasks, and given the
time constraints, they end up spending relatively brief periods on each of
them. Based on the nature of the work, managers tend to rely upon
information that is timely, even if this is likely to be less accurate than more
formal and complex information systems. Hence an MIS should be created
in such a way that it meets the information needs of managers.
Managers play at least three separate roles: interpersonal, informational and
decisional. An MIS, in electronic form or otherwise, supports all the three
roles in varying degrees.
Decision making can be divided into three levels: strategic, control (or
tactical) and operational. Strategic decisions are typically one-off situations
that have implications for changing the structure of an organisation. Hence,
the MIS must provide information which is precise and accurate. Control
decisions deal with broad policy issues and operational decisions concern
the management of the organisation's marketing mix. An MIS has to support
all these three levels of decision making.
MIS in e-Marketing
In the past, marketers asked information technology or information systems
personnel what software they had on the shelf. Today, however,
e-marketing actually drives technology change. E-marketing has changed
the MIS landscape in several ways. First, many firms store electronic
marketing data in databases and data warehouses. These data warehouses
enable marketers to obtain valuable, appropriate, and tailored information –
day or night. Second, marketers can receive database information in Web
pages and e-mail on a number of appliances in addition to the desktop
computer: pagers, fax machines, PDAs such as the Palm Treo and even
cellular phones. Third, customers also have access to portions of the
database. For example, when customers visit Amason.com, they can query
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the product database for book titles and also receive information about their
account status and past book purchases. Customers, channel members,
and partners often have access to customer sales data to facilitate product
planning. Customer inquiries are usually automated, with personalised web
pages created instantaneously from customer databases. Most firms
recognise that data and information are useless, unless turned into
knowledge to increase profits. Therefore, cutting-edge firms make one
employee‟s project reports, proposals, and data analyses available to other
stakeholders in the MIS network.
The internet and other technologies greatly facilitate marketing data
collection. Internal records give marketing planners excellent insights about
sales and inventory movement. Secondary data helps marketers understand
competitors, consumers, the economic environment, political and legal
factors, technological forces, and other factors that affect an organisation.
Marketing planners use the internet, the telephone, product bar code
scanners, and other technologies to collect primary data about consumers.
Through online e-mail and Web surveys, online experiments, focus groups,
and observation of internet user discussions, marketers learn about both
current and prospective customers.
Self Assessment Questions
8. Following are the main MIS aspects once data is gathered EXCEPT -
a. Storing data c. Manipulating data
b. Distributing data d. Analysing data
9. _____________ enable marketers to obtain tailored information.
10. Marketing information systems are proposed to support management
________________.
5.5 Marketing Intelligence Systems
A Marketing Intelligence System is a set of procedures and practices
employed in analysing and assessing marketing information gathered
continually from sources inside and outside an organisation. The analysed
data provides the basis for decisions such as product development/
improvement, pricing, packaging, distribution, media selection and
promotion.
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A Market Intelligence System that is customised to the size of your business
helps you fulfill customers' needs very well, because it identifies their
profiles, purchasing habits and motives and their wants and needs.
Marketing managers gather marketing intelligence by reading books,
newspapers, and trade publications, talking to customers, suppliers, and
distributors, monitoring "Social Media" on the internet via online discussion
groups, e-mailing lists and blogs and meeting with other company
managers.
Several steps to improve the quality of marketing intelligence:
Training and motivating the sales force to speck and report new
developments.
Motivating distributors, retailers, and other intermediates
External networking
Setting up a company advisory panel
Taking advantage of government data resources
Purchasing information from outside suppliers
Using online customer feedback systems to collect competitive
intelligence.
Self Assessment Questions
11. ____________ is gathered by reading books, newspapers, and trade
publications.
12. The quality of marketing intelligence is measured by ____________.
13. Use ____________ systems to collect competitive intelligence.
14. _____________ and _______________ the sales force makes them
collect and report new developments.
5.6 Managing Database Systems
Data collected from all customer touch points is stored in the data
warehouse knowledge management system, ready for analysis and
distribution to marketing decision makers.
Email programmes have address books with the capacity to store a variety
of information about each contact. In the initial stages of developing the list,
a company can use this capacity to build up information about contacts.
Using personalisation such as first names in emails increases response
rates.
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As the list grows, the company needs to consider how the contact and
response details should be stored – this is where a database becomes
useful. A database provides the extra flexibility in storing and managing the
contact details. However, if the number of contacts is very small, a spread-
sheet can also be used to track the contact details.
If the company is trying to manage a large contact database over time, a
CRM system (client relationship management system) will prove very useful.
This will not only allow the organisation to keep track of its contacts, but also
to keep track of the interactions with them and to target them specifically
according to the groupings created by the organisation. Civi-CRM is one of
the Open Source CRMs worth investigating. Civil Mail, the mass-mailing
component for Civi-CRM allows a company to engage its constituents with
personalised emails and newsletters. It can also work alongside Internet
Content Management Systems like Drupal and Joomla.
With Civi Mail, an organisation can:
Target mailings by including or excluding any number of CiviCRM groups, or
previous mail recipients.
Personalise the messages using mail-merge tokens.
Track when recipients open the message.
Track click-through.
5.6.1 Data Warehouse
Date warehouses are repositories for the entire organisation‟s historical data
(not just marketing data). They are designed specifically to support analyses
necessary for decision-making. In other words, marketers cannot apply the
data in product or customer databases to marketing problems as well as
they can apply information in a data warehouse. Sometimes, the data in a
warehouse is separated into more specific subject areas (called data marts)
and indexed for easy use. These concepts are important for marketers
because they use data warehouse information for planning purposes.
5.6.2 Data Mining
It is the process of extracting patterns from data. Data mining is becoming
an increasingly vital tool to transform data into information. It is generally
used in a wide range of profiling practices such as marketing, surveillance,
fraud detection and scientific discovery.
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Data mining can be used to reveal patterns in data, but is often carried out
only on samples of data. The mining process will not be effective if the
samples are not a good demonstration of the larger body of data. Data
mining cannot determine patterns that may be present in the larger body of
data if those patterns are not present in the sample being "mined". The
terms data dredging, data fishing and data snooping refer to the use of data
mining techniques to sample sizes that are very small for statistical
inferences to be made about the validity of any patterns discovered. You
can however, use data dredging to develop new hypothesis, which you must
validate with sufficiently large sample sets.
The following four classes of tasks are included in data mining:
Clustering - Clustering is the task of finding groups and structures in the
data that are in some way or the other “similar".
Classification – Classification is the task to generalise known structure to
apply to new data. For example, an email plan might attempt to classify an
email as genuine or spam. Common algorithms consist of decision tree
learning, nearest neighbour, naive Bayesian classification and neural
networks.
Regression – Regression attempts to find a task which models the data with
the least error.
Association rule learning – Association rule learning searches for
relationships between variables. For example, a supermarket might gather
data on customer purchasing practice. Using organisation rule learning, the
supermarket can determine which products are frequently bought together
and use this information for marketing purposes.
Self Assessment Questions
15. Data mining is a process for extracting patterns for data. (True/ False)
16. Regression is a type of _______________.
5.7 Online Experimental Research and Survey
Survey:1 It is a method of collecting information from a different number of
persons, known as a sample, in order to study something about the larger
population from which the sample is drawn. Even though surveys come in
1 www.activecampaign.com
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many forms, some surveys concentrate on opinion and attitudes while
others are more concerned with collecting and gathering accurate
information.
Example: Many soap product companies conduct surveys to know where
exactly and how their product is running and how people feel about the
product. This is some times done on a door to door basis.
Experimental research is an efficient and scientific approach in which the
user or researcher manipulates controls and measures any change in the
variables. The input for the research is the survey findings.
The purpose of experimental research is to study the cause and effect
relationships.
An important characteristic of experimental research is active manipulation
of an independent variable. Here is an example of an experiment.
Table: 5.1: Experimental Data
Pre-test Treatment Post test
O1 XE O2
O1 XC O2
Where:
E stands for the experimental group (e.g., new teaching approach)
C stands for the control or comparison group (e.g., the old or standard
teaching approach)
The best way to make the two groups similar in the above research design
is to randomly assign the participants to the experimental and control
groups. Let‟s assume that we have a convenience sample of 50 people and
that we randomly assign them to the two groups in our experiment.
Here is the logic of this experiment. First, the groups are made
approximately the same at the start of the study by using a random
assignment (i.e., the groups are “equated”). Then, the participants are put
through pre-tests to see how much they know.
Using the new teaching approach with the experimental group and using the
old teaching approach for the control group, the independent variable is
manipulated.
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After the manipulation, the participants‟ knowledge is measured to see how
much they know after having participated in the experiment. Let‟s assume
that the people in the experimental group show more knowledge
improvement than those in the control group. What would be the
conclusion? In this case, it can be concluded that there is a causal
relationship between the independent variable – teaching method and the
dependent variable – knowledge, and it can be specifically concluded that
the new teaching approach is better than the old teaching approach.
Here are some merits and demerits of online experimental research and
survey.
Table 5.2: Merits and Demerits of Online Experimental Research and Survey
Merits Demerits
Online research and survey is faster.
Targeting audience with online survey is difficult
Data-entry accuracy
The internet might slow down due to overload, which makes online exchange of information delayed.
High Security
A system might crash or hang, due to which purchasing or selling might be delayed
Internet surveys enable much more control than do paper surveys.
Online surveys will have a cost advantage over telephonic surveys.
Have to keep gazing the net always for its ups and downs in rates.
Self Assessment Questions
17. The purpose of experimental research is to study ________ and
__________ relationships.
18. An important characteristic of experimental research is active
manipulation of ________________.
5.8 Web Analytics
It is the objective tracking, collection, measurement, reporting, and analysis
of quantitative internet data to optimise websites and web marketing
initiatives.
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Web analytics2 is not just a tool used for measuring website traffic, but also
a tool for business research and market research. Web analytic applications
can also help several companies to measure the results of traditional print
advertising campaigns. It helps to estimate how the traffic to the website has
been changed after the launch of a new advertising campaign. Web
analytics provide data on the number of visitors, page views, etc to gauge
the traffic and popularity trends which help in marketing research.
There are two categories of web analytics: off-site and on-site web analytics.
Off-site web analytics refers to web measurement and analysis irrespective
of whether you own or maintain a website. It includes the measurement of a
website‟s potential audience or opportunity, share of voice or visibility, and
buss or comments that are happening on the Internet.
On-site web analytics measure a visitor's journey on the website. This
includes its drivers and conversions. On-site web analytics measures the
performance of the website in a commercial context. This data is typically
compared with key performance indicators for performance and used to
improve a web site or the response of the audience to a marketing
campaign.
5.8.1 Web Server Log File Analysis
Web servers record some of their transactions in a log file. It was
recognised that these log files could be read by a program to provide data
on the popularity of the website. This gave rise to the web log analysis
software.
In the early 1990s, web site statistics consisted mainly of counting the
number of client requests made to the web server. Initially, each web site
often consisted of a single HTML file. However, in HTML and web sites
images that spanned multiple HTML files were introduced, and hence this
count became less useful. The first proper commercial Log Analyser was
released by IPRO in 1994.
Two units of measure were introduced in the mid 1990s to measure more
accurately the total human activity on web servers. These were page views
and visits. A page view is a request to the web server for a page as to
2 e-marketing by Judy Strauss and Raymond Frost.
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oppose a graphic. A visit is an order of requests from a uniquely identified
client that expired after a certain amount of inactivity, usually 30 minutes.
The page views and visits are still commonly displayed metrics. The
emergence of search engine spiders and robots in the late 1990s, along
with web proxies and dynamically assigned IP addresses for large
companies and Internet server providers, made it more difficult to identify
unique human visitors to a website. Log analysers responded by tracking
visits by cookies, and by ignoring requests from known spiders.
5.8.2 Page Tagging
Page tagging takes care of the accuracy of log file analysis in the presence
of caching. And the desire to be able to perform web analytics as an
outsourced service, led to the second data collection method, page tagging
or 'Web bugs'.
In early 1990s, Web counters were commonly seen. These were images
included in a web page that showed the number of times the image had
been requested, which was an estimation of the number of visits to that
page. In the late 1990s, this concept evolved to include a small invisible
image instead of a visible by using JavaScript, to pass along with the image
requesting certain information about the page and the visitor. This
information can then be processed remotely by a web analytics company
and extensive statistics generated.
The web analytics service manages the process of assigning a cookie to the
user, which helps in uniquely identifying the user during their first and
subsequent visits. Acceptance rates of cookies vary significantly between
web sites and may affect the quality of data gathered and reported.
Gathering web site data using a third party data collection server requires an
additional Domain Name system look up by the user's computer to
determine the IP address of the collection server. Occasionally, delays in
completing successful or failed DNS look-ups may result in data not being
collected.
Self Assessment Questions
19. ________ is used as a tool for business research and market research.
20. Page tagging is also known as ______________.
21. Page tagging tests the accuracy of _____________.
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5.9 Knowledge Management Metrics
Marketing research is not cheap. Marketers often weigh the cost of getting
additional information against the value of potential opportunities or the risk
of possible errors from decisions made with incomplete information. They
are also concerned about the storage cost of all those terabytes of data
coming from Web site logs, online surveys, Web registrations, and other
real-time and real-space approaches. The good news is that data storage
costs have declined steadily since 1998. Two metrics are currently in
widespread use:
ROI: Companies want to know why they should save all those data, how will
they be used, and will the benefits in additional revenues or lowered costs
return an acceptable rate on the storage space investment? For hardware
storage space, ROI usually means total cost savings divided by total cost of
the installation (Gruener, 2001). Notably, companies use ROI to justify the
value of other knowledge management systems as well.
Total Cost of Ownership (TCO): Generally a metric used by information
technology managers, TCO includes not only the cost of hardware,
software, and labour for data storage, but also other items such as cost
savings by reducing Web server downtime and labour requirements. For
example, Galileo International offers travel reservations and maintains 102
terabytes of data – schedule, fare and reservation information for 500
airlines, 47,000 hotels and 37 car rental companies (Radding, 2001) .The
Company booked 345 million reservations in 2000, sometimes handling
10,000 requests a second! Galileo‟s ROI is simple: according to its owner,
Frank Auer, every bit of the firm‟s $1.6 billion in revenue is a return on its
data storage system.
In another example, trucking company Schneider National had enough data
to fill ten 53-foot trailers with floppy disks. But it still could not easily figure
out why it cost $0.20 a pound to deliver cars to a Ford Dealership in Texas
and only $0.17 elsewhere. The firm spent an estimated $2 million to
purchase business intelligence software that allowed employees to get quick
answers to marketing problems and realised a $2.5 million return on that
investment within two years (25 %) (Brown, 2002).
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Self Assessment Questions
22. ROI is an example _____________________________.
23. ____________________________ is the technique largely used by
Information Technology Managers.
Activity 2
Assuming that you are starting an online marketing channel for electronic
razors, chart out an e-marketing strategy. Your strategy should include all
the details like the promotional channel, audience, type of tools to be
used for data mining, web analytics and so on.
5.10 Summary
Let us recap what we studied in this unit.
E-Marketers need data to take decisions about creating and changing
marketing strategies. This data is collected from a number of sources,
filtered into databases and turned into marketing knowledge that is then
used to develop marketing strategies.
Knowledge management is the process of managing the creation, use, and
dissemination of knowledge.
The different types of data studied are user entry type or profile type, web
document and web Meta data and finally the server and cookie data.
A Marketing Information System (MIS) is the process by which marketers
manage knowledge, by using a system of assessing information needs,
gathering information, analysing it and disseminating it to decision makers.
Data warehouses are repositories for the organisation‟s historical data. Data
from all customer touch points are stored in the warehouse.
Data mining extracts hidden predictive information from the warehouse via
statistical analysis.
5.11 Glossary
Term Description
Caching Storing of web files for later re-use to facilitate quick access by the end user.
Strategy A plan of action designed to achieve a particular goal.
Algorithm Step by step procedure.
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5.12 Terminal Questions
1. Write short notes on user entry data and cookie data.
2. Why is knowledge management necessary?
3. What is a Marketing Information System? Explain its importance.
4. Discuss marketing intelligence systems and data based systems.
5. What do you understand by online experimental research and online
survey processes?
6. Briefly describe web analysis.
7. What is knowledge management metrics and how important is it to an
organisation?
5.13 Answers
Self Assessment Questions:
1. Data.
2. Web documents.
3. Cookies
4. Server log and cookie log.
5. Knowledge management.
6. Goal.
7. Planning quicker.
8. c. Manipulating data
9. Data warehouse
10. Decision making.
11. Marketing intelligence.
12. External networking.
13. Online customer feedback systems
14. Training and motivating.
15. True
16. Data mining
17. Cause and Effect
18. Independent variable
19. Web analysis
20. Web bugs
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21. Log files analysis
22. Knowledge management metrics
23. Total cost ownership (TCO)
Terminal Questions:
1. Refer section 5.2, Types of data in e-marketing
2. Refer section 5.3, Knowledge management for e-marketing
3. Refer sections 5.4, Marketing Information Systems for e-marketing
4. Refer section 5.5 and 5.6, Marketing Intelligence systems & Managing
database systems
5. Refer sections 5.7, Online experimental research and survey
6. Refer section 5.8, Web analytics
7. Refer section 5.9, Knowledge Management Metrics
5.14 Case-let
Invention and Knowledge
Mr. James invented the photocopy machine in 1934. He tried to sell his in
invention to MNC companies, but his efforts failed as the companies did
not believe that there was a major market for photocopiers. It was left to
the small Italy based company called Tyco to finally market a product that
later became vital for making multiple copies of documents. Modi crop
officially came into existence after which Tyco changed its name replicate
its core business. After decades the company diversified into a number of
businesses, some of those added values to its business model and others
which had to be liquidated.
In the mid of the year 1990‟s the company switched on itself as the
„Document Company‟, to reflect more on its core business. The
knowledge management movement of 1990s encouraged the company to
concentrate more on knowledge sharing initiatives. It started “Spec” which
captured the hints shared informally by the company‟s service
representatives and created a data base of hints that could be accessed
by councils all over the world.
Both internal and commercial also followed and Modi Corp was
recognised as one of the most admired knowledge Enterprise.
e-Marketing Unit 5
Sikkim Manipal University Page No. 103
Discussion Questions:
1. Why Mr. James failed in selling his invention?
2. What prompted the company to concentrate on knowledge sharing
initiatives? Do you think today it is easier to share knowledge and
information that help e-marketing as well?
This is adapted from the real life scenario on Chester Carlson‟s invention
of the photocopying machine.
References
Strauss Judy, Frost Raymond, E-marketing 2002 – 2nd edition, Free
Press
E-References
www.whatyouveheard.com/2010/07/global-data-warehouse-software-
market-in-retail-industry-2008-2012/
www.en.wikipedia.org/wiki/Web_analytics