Download E-Marketing/6E Chapter 6

E-Marketing Research
Chapter 6 Objectives
 After reading Chapter 6, you will be able to:
 Identify the three main sources of data that emarketers use to address research problems.
 Discuss how and why e-marketers need to
check the quality of research data gathered
online.
 Explain why the Internet is used as a contact
method for primary research and describe the
main Internet-based approaches to primary
research.
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Chapter 6 Objectives (Cont.)

Describe several ways to monitor the web for
gathering desired information.

Contrast client-side, server-side, and real-space
approaches to data collection.

Explain the concepts of big data and cloud computing.

Highlight four important methods of analysis that
e-marketers can apply to data warehouse
information.
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The Purina Story
 Nestle Purina PetCare wanted to know whether their
websites and online advertising increased off-line
behavior.
 http://www.purina.com
 Nestle Purina developed 3 research questions:
 Are our buyers using our branded websites?
 Should we invest beyond these branded Web sites in
online advertising?
 If so, where should we place the advertising?
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The Purina Story, Cont.
 Combined online and off-line shopping panel data
revealed:

Banner click-through rate was low (0.06%).

31% of subjects exposed to Purina ads mentioned the
Purina brand compared with 22% of the no-exposure
subjects.

Home/health and living sites received the most visits
from their customers.
 The information helped the firm decide where to place
banner ads.
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Data Drive Strategy

U.S. marketers spend $6.7B annually on marketing
research; global spend is $18.9B.
 E-marketers can generate a great deal of data by using
surveys, Web analytics, secondary data, social media
conversations, etc.
 Marketing insight occurs somewhere between
information and knowledge.
 Data without insight or application to inform
marketing strategy are worthless.
 Purina, for example, sorts through hundreds of millions
of pieces of data about 21.5 million consumers to make
decisions.
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Big Data
 Big data refers to huge data sets that are difficult
to manage and analyze.
 31% of marketers would like to collect Web data
daily.
 74% collect demographic data; 64% collect
transaction data; 35% monitor social media.
 Purina, for example, sorts through hundreds of
millions of pieces of data from about 21.5
million consumers to make marketing
decisions.
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From Data to Decision: Nestle Purina
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Marketing Knowledge Management
 Knowledge management is the process of managing
the creation, use, and dissemination of knowledge.
 Data, information, and knowledge are shared with
internal decision makers, partners, channel
members, and sometimes customers.
 A marketing knowledge database includes data about
customers, prospects and competitors.
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The Electronic MIS

A marketing information system (MIS) is the process by
which marketers manage knowledge.


Many firms store data in databases and data warehouses,
available 24/7 to e-marketers.
The Internet and other technologies facilitate data
collection.

Secondary data provide information about competitors,
consumers, the economic environment, etc.

Marketers use the internet and other technologies to
collect primary data about consumers.
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Most Common Data Collection Methods
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SOURCE 1: INTERNAL RECORDS
 Accounting, finance, production, and marketing
personnel collect and analyze data for marketing
planning.
 Sales data
 Customer characteristics and behavior



Universal product codes (UPCs)
Tracking of user movements through web pages
Web sites visited before and after the firm’s Web
site.
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SOURCE 2: SECONDARY DATA

Can be collected more quickly and less expensively than
primary data.
 Secondary data may not meet e-marketer’s information
needs.
 Data was gathered for a different purpose.
 Quality of secondary data may be unknown.
 Data may be old.
 Marketers continually scan the macroenvironment for
threats and opportunities, a procedure commonly called
business intelligence.
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Public & Private Data Sources
 Publicly generated data
 Privately generated data

U.S. Patent Office
 comScore

CIA World Factbook
 Forrester Research

American Marketing
Association (AMA)
 Nielsen/NetRatings

Wikipedia
 Euro monitor

Ministry of Economy
and Planning (www.mep.gov.sa)

The Patent Office of the
Cooperation Council for the
Arab States of the Gulf
(http://www.gccpo.org/)
 Commercial online databases
(http://www.euromonitor.com)
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Competitive Intelligence Example
 CI involves analyzing the industries in which a firm operates as input to
the firm’s strategic positioning and to understand competitor
weaknesses.
 CI can help firm’s analyze competition as well as assist in strategic
planning
 Intelligence cycles would include the following steps:
1. Define the intelligence requirements
2. Collect and organize information
3. Analyze by applying information to the specific purpose and
recommending action
4. Report and inform others of the finding
5. Evaluate the impact of intelligence use and suggest process
improvements
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Competitive Intelligence Example
(Cont.)

Sources may include

press releases,

new products,

alliances and co-brands,

trade shows

third-party, industry-specific sites

user conversation in the social media Facebook.
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Information Quality



Secondary and primary sources have many limitations.
E-marketers should be wary of data, especially if it is secondary
data.
E-marketers should:







Discover the website’s author,
Try to determine if the site author is an authority on the Web site
topic,
Check to see when the site was last updated,
Determine how comprehensive the site is,
Try to validate the research data by finding similar information at
other sources on the internet or in hard copy at the library, and
Check the site content for accuracy.
What about Wikipedia, is it accurate?
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Source 3: Primary Data

When secondary data are not available, marketers may
collect their own information.
 Primary data are information gathered for the first time
to solve a particular problem.



More expensive and time consuming
Current, more relevant & exclusive
Primary data collection can be enhanced by the internet:





Online experiments
Online focus groups
Online observation
Content analysis
Online survey research
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Primary Research Steps
 The steps to conduct primary research are:
1. Define the research problem,
2. Develop a research plan,




Research approach
Sample design
Contact method
Instrument design
Collect data,
4. Analyze the data, and
5. Distribute results
3.
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Typical Research problems for EMarketers
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Source 3: Primary Data Collection
Methods
 In-depth interviews (IDI) are better done offline
 Primary data collection enhanced by the Internet

Online experiments

Online focus groups

Online observation

Online survey research

Web surveys

Online panels
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Advantages & disadvantages of
online survey research
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Online Panels
 Online panels include people who have agreed to
be subjects of marketing research.
 Participants are usually paid and often receive
free products.
 Panels can help combat sampling and response
problems, but can be more expensive than
traditional methods of sample generation.
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Ethics of Online Research

Companies conducting research on the web often give
respondents a gift or fee for participating.
 Other ethical concerns include:
 Respondents are increasingly upset at getting
unwelcomed e-mail requests for survey participation.
 “Harvesting” of e-mail addresses from newsgroups
without permission.
 “Surveys” used to build a database.
 Privacy of user data.
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Other Technology-Enabled Approaches
 Client-side Data Collection
 Cookies
 PC meter with panel of users to track the user
clickstream.
 Server-side Data Collection
 Site log software can generate reports on
number of users who view each page, location
of prior site visited, etc.
 Real-time profiling tracks users’ movements
through a website.
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Following the clickstream at FTC.gov
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Real-Space Approaches
 Real-space primary data collection: technology
enabled approaches to gather information offline.
 Data collection occurs at off-line points of purchase
and information is stored and used in marketing
databases.
 Real-space techniques include bar code scanners and
credit card terminals.
 Catalina Marketing uses the Universal Product Code
(UPC) for promotional purposes at grocery stores.
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REAL-SPACE DATA COLLECTION &
STORAGE EXAMPLE
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Marketing Databases & Data
Warehouses

Product databases hold information about product
features, prices, and inventory levels; customer databases
hold information about customer characteristics and
behaviors.

Data warehouses are storehouses for the entire
organization’s historical data, not just for marketing data.

Software vendors are attempting to solve the website
maintenance problem with content management systems.

The current trend in data storage is toward cloud
computing: a network of online Web servers used to store
and manage data.
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Cloud Computing
Mobile phone
Tablet
computer
Remote
servers
Data
content
Computer
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Company Web
server
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Data Analysis & Distribution
 Four important types of analysis for marketing
decision making include:
 Data mining
 Customer profiling
 RFM (recency, frequency, monetary value)
analysis
 Report generating
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Knowledge Management Metrics
 Two metrics are currently in widespread use for
online data storage:
 ROI: total cost savings divided by total cost of
the installation.
 Total Cost of Ownership (TCO): includes cost
of hardware, software, labor, and cost savings.
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photocopying, recording, or otherwise, without the prior written permission of the
publisher. Printed in the United States of America.
Copyright © 2014 Pearson Education, Inc.
Publishing as Prentice Hall
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