This section describes the collection and analysis of customer, retail, competitive, and General Mills data.  All of the tools required will be described in detail or have been covered in Market Intelligence.  A brief summary of each is offered here.  Copies of articles or chapters/pages from books are linked on the project website.  Feel free to scout out other tools and frameworks that might be helpful. 


Customer Data

These data include behavioral, perceptual, and psychographic data related to customers.


Consumer Behavior Data

These data and techniques examine actual consumer behavior in the focal or related domains.

Nielsen Scanner Data

  These national data run from 8/11/00 to 8/11/01.  The data reflect a cross-sectional view of consumer purchase behavior, the incidence and effect of promotion, and distribution levels. 


Nielsen Scanner Data Link

Nielsen Scanner Data Dictionary

Julie Beattie (Fuqua ’01) made a presentation about the nature and use of scanner data for Market Intelligence. I am attaching her presentation for your information.  Note that she discusses more metrics than General Mills has made available to us.


Nielsen Panel Data

These data follow a sample or panel of consumer for one year ending 12/23/00.  The data are organized so that each competitor is a column.  Consumer, retail, and promotional data are offered. 


Nielsen Panel Data Link

Nielsen Panel Data Dictionary/Presentation


Usage Data

These data examine how consumers actually use products.  This includes frequency and usage context (where, when).  Often researchers will examine “why” usage as well because context and motivation are usually linked in important ways. 

Pam Murtaugh’s presentation on 11/7 will discuss consumer experiences.  In addition, your interviews and focus groups can provide information about consumer usage behaviors.  You may be able to find some syndicated or published data in the business or popular press on usage.  The links below will be a useful start in explaining the importance of usage situation.   


Mowen, John (1995), Consumer Behavior, pp. 580-584.

Sheth, Jagdish, Banwari Mittal, and Bruce Newman (1999), Consumer Behavior and Beyond, pp. 438-440.

Hoyer, Wayne and Deborah McInnis (1997), Consumer Behavior, pp. 4-5.

Pam Murtaugh’s business prospectus


 Loyalty Data

Marketers study both attitudinal and behavioral loyalty data.  Attitudinal data would provide information about a consumer’s commitment to the brand – do they feel loyalty.  Behavioral loyalty would measure loyalty by examining a consumer’s actual purchase and/usage behaviors. 

Behavioral loyalty information is contained in the Nielsen Panel Data in the “Share of Requirements” metric.  Share of requirements is the percent of a buyers’ total category volume accounted for by the specified item. 


Consumer Perceptual Data 

These data examine consumer beliefs, goals, and other critical cognitive elements affecting choice. 

Attribute Importance Data

  Data provides information regarding what attributes consumers’ value in current and hypothetical products.  This type of information can be gleaned from depth interviews (see below), focus groups (see below), surveys (see Market Intelligence), a conjoint analysis study (see Market Intelligence), or an experiment (see Market Intelligence).  In the case of a conjoint study or an experiment, the basic approach would be to vary the attributes in an offering and determine how this affects preference for that alternative.  Conjoint is a sophisticated analytic tool that decomposes alternatives into attribute weights.  An experiment would involve your manipulation of actual products or product profiles to determine impact on preferences. 

All of these sources were used in Market Intelligence

Conjoint analysis: 
Dolan, “Conjoint Analysis: A Manager’s Guide
Wyner, Gordon A., “Uses and Limitations of Conjoint Analysis, Part 1

Other online conjoint tools: -- Online version of Adaptive Conjoint Analysis
Purina Dog Selector -- Powered by ActiveBuyersGuide

Lands' End Personal Shopper -- Powered by
Memetrics -- Personalization technology using conjoint-based choice modeling

Kumar, Aaker, and Day (1999), “Chapter 12 – Experimentation,” in Essentials of Marketing Research.



Means-End Chains

Marketers try to understand consumers’ knowledge structures by plotting means-end chains.  A means-end chain is a knowledge structure that links a consumer’s knowledge about product attributes with their knowledge about consequences and values.  The means-end perspective suggests that consumers think about product attributes subjectively in terms of personal consequences.  Marketers use direct elicitation, free-sort tasks, triad tasks, and laddering to construct means-end chains


Peter, J. Paul and Jerry C. Olson (1996), Consumer Behavior and Marketing Strategy, pp. 73-78.


Consumer Psychographic Data

These data and techniques focus on consumer attitudes, interests, opinions, and lifestyle trends. 

Qualitative Focus Group Interview Data

Description:  Focus groups involve multiple consumers reflecting on products, concepts, the category, or underlying needs.


Richard Krueger (1994), Focus Groups, see pages 16-38 and 53-73.

Randazzo, Sal (1993), “Chapter 6: Building Your Brand’s Mythology: Information, Insight, and Ideas,” in Mythmaking on Madison Avenue, Chicago, Ill, 163-171.


Clinical Interviews

Involve one-on-one discussions that examine cultural forces, lifestyle factors and psychological needs.  These interviews are now gaining prestige within the marketing research community as offering depth of insight surrounding latent needs. 


Grant McCracken (1988) Chapters 2 and 3, The Long Interview.

Robert Weiss (1994), Chapters 1, 2, and 4, Learning from Strangers.

Thompson, Craig J., William B. Locander and Howard R. Pollio (1989), “Putting Consumer Experience Back Into Consumer Research: The Philosophy and Method of Existential-Phenomenology,” Journal of Consumer Research, 16 (September), 133-147.


Lifestyle Data

Description:  This data may come from published sources such as Statistical Abstract, from popular press sources such as USA Today, or from syndicated sources (see below).  This type of data is pervasive and yet often not used by marketers.  Talk shows, books, movie themes reveal lifestyle shifts.  Your focus can be broad to begin with but you must also consider lifestyle trends as they affect food purchasing, preparation, and consumption.  There is also a fair amount of academic literature associated lifestyle shifts.  I note several articles that I’m aware of but if you think this is useful, search further:


Popcorn, Faith and Lys Marigold (1996), Clicking : 16 trends to future fit your life, your work, and your business, New York:  HarperCollins.

Popcorn, Faith (2000), EVEolution : The Eight Truths of Marketing to Women, New York : Hyperion. 

World Future Society:  Social and technological forecasts and publisher of The Futurist.

Bureau of Labor Statistics:  Contains consumer expenditure data

National Survey of Families and Households at the Center for Demography and Ecology, University of Wisconsin – Madison. 

Center for Mature Consumer Studies at the University of Geogia. 

The Conference Board’s Consumer Research Center

Federal Reserve’s Survey of Consumer Finances

The Gallup Organization

Sales and Marketing Management’s Survey of Buying Power – (9/99), (9/00), and (9/01) (available in FSB library databases and in print)

American Demographics and also available on FSB library databases and in print

Thompson, Craig (1996) “Caring Consumers: Gendered Consumption Meanings and the Juggling Lifestyle,” Journal of Consumer Research, 22 (March), 388-407.

Schor, Juliet B. (1993), The Overworked American, (2000), Do Americans Shop Too Much?

Statistical Abstract (FSB data bases - see Statistical Abstract of the US, STAT USA)


Syndicated Lifestyle Data

This data are aggregated across consumers with the goal to provide general lifestyle information about different aspects of consumer attitudes, interests, and opinions.


The Lifestyle Analyst contains relevant information on the purchase behaviors and media patterns associated with certain lifestyle clusters.

MediaMark Research Inc. (MRI) and Simmons are media sources that provide information on lifestyle clusters and their media and product purchase behaviors.  This is general information about consumer usage behaviors embedded in this data. 

SRI International’s VALS information.   This approach segments the market on resource level (financial, material, health, education psychological) as well as self-orientation (principle-oriented, status-oriented, and action-oriented).  Eight segments result.  Although you will be unlikely to get VALS data on these customers, the VALS survey is online and will classify consumers taking the survey.  The framework may be a useful conceptual tool as well. 

Geodemographic sources that combine geographic data, psychographic data, media usage, and purchase data.  PRIZM is one tool that uses this data to create 62 lifestyle groups that are linked to zip codes.  They have some demo information (+) that might be interesting to examine.

Leisure Trends, Inc. for studies of how Americans spend their free time. 


Lifestyle “Tribe” or “Affinity Group” Data

There is an emerging sense that consumers affiliate more and more with others who share a lifestyle orientation that expresses life themes, deeply held values, and goals.  As Cova (1996, p. 19) explains, “Modern society was conceived as an ensemble of social groups:  socio-professional categories, social classes, and so on.  Postmodern society, in contrast, resembles a network of societal micro-groups in which people share strong emotional links, a common subculture, a vision of life.  In our times … occupational communities such as those of computer engineers or ballet dancers, and style conscious youths such as rastas or skinheads develop their own complexes of meanings and symbols and form more or less stable tribes that are invisible to the categories of modern sociology.  Each postmodern individual belongs to several tribes, in each of which s/he might play a different role and wear a specific mask…. ”


There are some recent accounts of such communities in the academic literature that may be useful. 

Muniz and O’Guinn (2001), “Brand Community,” Journal of Consumer Research, 27 (March), 412-433.

Schouten and McAlexander (1995), “Subcultures of Consumption:  An Ethnography of the New Bikers,” Journal of Consumer Research, 22 (June), 43-61.

I have also attached tribe analyses of antique collectors and foreign travelers created by students.



Retail Data

These data focus on retailer as an institutional force that influences consumer and competitive behavior. 

Storewalk Data

An important tool that is used in many strategy development activities involves managers immersing themselves in the retail environment.  You can approach this in any way you think would be meaningful and useful.  We suggest the following activities: 

Examine a variety of stores, including grocery retailers (Foodlion, Harris Teeter, and Kroger) and superstore or discount retailers (WalMart, Kmart).  Bowl Appetit is in all of these environments. 

Examine the layout and structure of the focal and relevant competitive product categories in the store. 

Examine in-store consumer behavior related to these categories


In-store observation

In-store photos


Retail Trend Data

Description:  Provides insight on consumer, manufacturer, and retailer interactions relevant to strategy development


Progressive Grocer

The Food Marketing Institute


Nielsen Panel Data

These data follow a sample or panel of consumer for one year ending 12/23/00.  The data are organized so that each competitor is a column.  Consumer, retail, and promotional data are offered.  See the Dictionary for this data above


Nielsen Panel Data Link

Nielsen Scanner Data Dictionary



Competitive Data

These data focus on trends, firm-level analysis, and product-level analysis. 

Firm-level Analysis

Strategy development requires that you examine the presence of firm-wide resources and capabilities.  This information will be useful in determining what directions the firm can sustain in its strategy.  Firm information is listed by firm on the project website.  


Annual reports
: ConAgra, Hormel, Campbell's Soups, Inc., Nestle, General Mills

Analysts reports
: ConAgra, Hormel, Campbell's Soups, Inc., Nestle, General Mills, Kraft (available at MULTEX Investment & Industry Reports via FSB database).

Business press coverage: Classico (+), Bowl Appetit, Healthy Choice (+), Michelina (+) , Stouffer's


Industry-level Analysis

This data examines packaged food industry trends


Syndicated Industry data:

S&P Industry Survey

U.S. Industrial Outlook

Value Line

F&S Index
(on reserve in Fuqua library)

Predicasts Basebook (on reserve in Fuqua library)          

Euromonitor’s Global Marketing Reports

S&P Market Insight

Analysts Industry Reports


Product-level Analysis


Description:  This is data about the firm or business unit’s offerings in the focal category.  


Nutrition information:
Available on products in library, at the supermarket, and through a nutrition food count book (The Complete Book of Food Counts by Corrine T. Netzer) that I have put on reserve in the library. 

Taste data 
  I encourage you to perform taste tests of your own.  Taste data may be useful in understanding what consumers think about the taste of product offerings in this category.  

Consumer Reports evaluations of relevant food categories: (1) (2) (3)

Brand awareness, equity, and meaning ratings:

I encourage you to perform tests of your own.

Business Week evaluations of top brands 

Packaging data:
-          Examine packages in the store or on products in library

Promotion data:
TV advertisements: Betty Crocker -- Bowl Appetit!, Betty Crocker -- Bowl Appetit!, Ragu Express, Kraft Easy Mac, Chef Boyardee, Campbell's Soup to Go, Its Pasta Anytime, Uncle Ben's Rice Bowl and Noodle Bowl, Stouffers Mac & Cheese, Stouffers Lean Cuisine, Healthy Choice, Marie Callender's Bowls.
(Real Player Needed)

Nielsen Panel Data Link containing data on responsiveness to features and displays

Free-standing inserts
: Bowl Appetit (+), Kid's Kitchen, Lean Cuisine, Ragu Express (+), Stouffer's, Uncle Ben's Bowls (+)

In-store promotion photos

Distribution data:
Nielsen scanner data provides ACV data on distribution

Nielsen panel data contains information on percentage of buyers in different retail outlets. 

You should perform store checks at various traditional and nontraditional locations to determine the nature and intensity of distribution activities.



Company Data on General Mills and Its Offerings

The structure of this data corresponds to that used in the competitive data set.  See the project website for details.