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E-Marketing Research
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?
©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 2
strauss_emktg6_ppt06_-_l_r.ppt
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.
©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 4
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.
6-5
©2014 PEARSON EDUCATION, INC.
PUBLISHING AS PRENTICE HALL
From Data to Decision: Nestle Purina
©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL
6
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.
©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 7
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.
©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 8
Most Common Data Collection Methods
©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 9
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.
©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL
10
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.
©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 11
Public & Private Data Sources
 Publicly generated data
 U.S. Patent Office
 CIA World Factbook
 American Marketing
Association (AMA)
 Wikipedia
 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/)
 Privately generated data
 comScore
 Forrester Research
 Nielsen/NetRatings
 Commercial online databases
 Euro monitor
(http://www.euromonitor.com)
©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 12
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?
©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 13
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
©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 14
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
3. Collect data,
4. Analyze the data, and
5. Distribute results
©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 15
Typical Research problems for E-
Marketers
©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 16
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
©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 17
Advantages & disadvantages of
online survey research
©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 18
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.
6-19
©2014 PEARSON EDUCATION, INC.
PUBLISHING AS PRENTICE HALL
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.
©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 20
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.
©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 21
Following the clickstream at FTC.gov
©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL
22
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.
©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 23
REAL-SPACE DATA COLLECTION &
STORAGE EXAMPLE
©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 24
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.
©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 25
Cloud Computing
©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 26
Company Web
server
Tablet
computer
Mobile phone
Computer
Remote
servers
Data
content
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
©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 27
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.
©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 28
strauss_emktg6_ppt06_-_l_r.ppt
6-30
All rights reserved. No part of this publication may be reproduced, stored in a retrieval
system, or transmitted, in any form or by any means, electronic, mechanical,
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
©2014 PEARSON EDUCATION, INC.
PUBLISHING AS PRENTICE HALL

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strauss_emktg6_ppt06_-_l_r.ppt

  • 2. 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? ©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 2
  • 4. 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. ©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 4
  • 5. 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. 6-5 ©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL
  • 6. From Data to Decision: Nestle Purina ©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 6
  • 7. 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. ©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 7
  • 8. 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. ©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 8
  • 9. Most Common Data Collection Methods ©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 9
  • 10. 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. ©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 10
  • 11. 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. ©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 11
  • 12. Public & Private Data Sources  Publicly generated data  U.S. Patent Office  CIA World Factbook  American Marketing Association (AMA)  Wikipedia  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/)  Privately generated data  comScore  Forrester Research  Nielsen/NetRatings  Commercial online databases  Euro monitor (http://www.euromonitor.com) ©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 12
  • 13. 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? ©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 13
  • 14. 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 ©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 14
  • 15. 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 3. Collect data, 4. Analyze the data, and 5. Distribute results ©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 15
  • 16. Typical Research problems for E- Marketers ©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 16
  • 17. 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 ©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 17
  • 18. Advantages & disadvantages of online survey research ©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 18
  • 19. 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. 6-19 ©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL
  • 20. 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. ©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 20
  • 21. 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. ©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 21
  • 22. Following the clickstream at FTC.gov ©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 22
  • 23. 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. ©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 23
  • 24. REAL-SPACE DATA COLLECTION & STORAGE EXAMPLE ©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 24
  • 25. 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. ©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 25
  • 26. Cloud Computing ©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 26 Company Web server Tablet computer Mobile phone Computer Remote servers Data content
  • 27. 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 ©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 27
  • 28. 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. ©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL 28
  • 30. 6-30 All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, 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 ©2014 PEARSON EDUCATION, INC. PUBLISHING AS PRENTICE HALL

Editor's Notes

  1. Identify the three main sources of data that e-marketers use to address research problems.
  2. Discuss how and why e-marketers need to check the quality of research data gathered online.