Nestle Purina PetCare wanted to understand the impact of their online advertising and websites on offline sales. They analyzed online and offline panel data and found that (1) banner clickthrough was low at 0.06% but (2) 31% of subjects exposed to both online and offline ads mentioned Purina, and (3) those with high exposure mentioned Purina more. Companies are using vast amounts of online and offline data through marketing information systems and knowledge management to guide business decisions.

1. E-MARKETING, 6TH
EDITION
JUDY STRAUSS AND RAYMOND FROST
Chapter 6 – E-Marketing Research

2. The Purina Story
Nestle Purina PetCare Company wanted to know whether their
web sites and online advertising increased off-line behavior.
Nestle developed 3 research questions:
 Are our buyers using our branded Web sites?
 Should we invest in other Web sites?
 If so, where should we place the advertising?
They combined online and off-line shopping panel data and
found that:
 Banner clickthrough was low (0.06%).
 31% of subjects who were exposed to both online and off-line advertising
mentioned Purina.
 The high exposure group mentioned Purina more than the low exposure
group.
2

3. Data Drives Strategy
Organizations are drowning in data.
Survey results, internal records, private reports,
government reports.
Click stream data, web analytics, etc.
Marketing insight occurs somewhere between
information and knowledge.
Purina, for example, sorts through hundreds of
millions of pieces of data about 21.5 million
consumers to make decisions.

4. From Data to Decision: Purina

5. Marketing Knowledge Management
Knowledge management is the process of
managing the creation, use and dissemination of
knowledge.
Examples of the uses of knowledge
management can be found in Exhibit 6.4.

6. Uses of Knowledge Management
Wal-Mart
Kmart
Sears
Osco/Savon Drugs
Casino Supermarkets
W. H. Smith Books
Otto Versand Mail Order
Amazon.com
Scanner Check-Out Data Analysis
Sales Promotion Tracking
Inventory Analysis and Deployment
Price Reduction Modeling
Negotiating Leverage with Suppliers
Frequent-Buyer Program Management
Profitability Analysis
Product Selection for Markets
Representative FirmUse in the Retail Industry
AT&T
Ameritech
Belgacom
British Telecom
Telestra Australia
Telecom Ireland
Telecom Italia
Scanner Check-Out Data Analysis
Call Volume Analysis
Equipment Sales Analysis
Customer Profitability Analysis
Cost and Inventory Analysis
Purchasing Leverage with Suppliers
Frequent-Buyer Program Management
Representative FirmUse in the Telecom Industry

7. The Marketing Information System
Marketers manage knowledge through a
marketing information system (MIS).
Many firms store data in databases and data
warehouses.
The Internet and other technologies have
facilitated data collection.
Secondary data provides information about
competitors, consumers, the economic
environment, etc.
Marketers use the Net and other technologies to
collect primary data about consumers.

8. Soures of data: Internal records
Accounting, finance, production and marketing
personnel collect and analyze data.
Nonmarketing data, such as sales and advertising
spending
Sales force data
Conversion rate, ads effectiveness, tracking customer
behavior
Customer characteristics and behavior
Universal product codes
Tracking of user movements through web pages

9. Secondary data
Can be collected more quickly and less
expensively than primary data.
Secondary data may not meet e-marketer’s
information needs.
Data were gathered for a different purpose.
Quality of secondary data may be unknown.
Data may be old.
Marketers continually gather business
intelligence by scanning the environment.

10. Public and Private Data Sources
•Publicly generated data
• U.S. Patent Office
• American Marketing Association
• Social Media Database
•Privately generated data
• Well Known Expert’s Blog - Seth Godin’s Blog
• Forrester Research
• Nielsen/NetRatings
• Pew Research Center
•Online databases

11. Competitive Intelligence
 Analyzing the industry in which a firm operates as a
input to the firms' strategic positioning to
understand competitors vulnerability
 Sources
 Competitors press release
 New product launch
 New alliances
 Co-brands
 Trade show activity
 Social media conversations
 Web site logs
 Third-party industry specific sites

12. Information Quality
 Advise to be objective, especially before using
information on web pages
 Control for cultural differences
 Don’t get distracted by website design
 Discover the website’s author identity
 Try to determine whether the site author is an
authority is an authority on the web site topic
 Check to see when site was last updated
 Determine how comprehensive the site is
 Try to establish triangulation
 Check to site content for accuracy

13. NO SITE IS COMPETE
AND ACCURATE!!!

14. Primary Data
Two electronic sources of primary data
collection:
Internet
Real space
Primary data collection on the Net:
Experiments
Focus groups
In-depth interviews
Survey research
Real-space data collection refers to technology-
enabled gathering of information offline.

15. Primary Research Steps
Research Problem
Research Plan
Research Approach
Sample Design
Contact Method
Instrument Design
Data Collection
Data Analysis
Distribution of Findings

16. Online Research Advantages & Disadvantages
Advantages
Can be fast and inexpensive.
Surveys may reduce data entry errors.
Respondents may answer more honestly and
openly.
Disadvantages
Sample representativeness.
Measurement validity.
Respondent authenticity.
Researchers are using online panels to combat
sampling and response problems.

17. Other Technology-Enabled Approaches
•Client-side Data Collection
• Cookies
• Use PC meter with panel of users to track the user
clickstream.
•Server-side Data Collection
• Data log software
• Real-time profiling tracks users’ movements through
a web site.

18. Real-Space Data Collection, Storage, and Analysis
•Offline data collection may be combined with
online data.
•Transaction processing databases move data
from other databases to a data warehouse.
•Data collected can be analyzed to help make
marketing decisions.
• Data Mining
• Customer Profiling
• Recency, Frequency, Monetary (RFM) Analysis
• Report Generating