December 1997 // Volume 35 // Number 6 // Feature Articles // 6FEA2

Previous Article Issue Contents Previous Article

Encouraging Marketing Research

Some business people are unfamiliar with the need for or the benefits from marketing research. One tool for communicating the value of marketing and marketing research is regional sales indices. These indices can help highlight market heterogeneity, illustrate marketing complexities, and encourage the use of regional events. They can also be used to help identify potential marketing partners, guide test market selection, and assist with volume forecasting. By including analyses of these sales development indices in presentations to business groups, greater interest in conducting marketing research and in supporting marketing programs may be generated.

Ronald B. Larson
Assistant Director, The Retail Food Industry Center
University of Minnesota
St. Paul, Minnesota
Internet Address:

One of the toughest audiences for Extension educators is a group of business people who have been successful without consciously using a new practice or technology. An example is convincing people who doubt that the value of marketing research to understand their buyers may generate higher returns than studies to improve yields and lower costs.

Those unfamiliar with marketing may believe that most people are similar to their friends, that everyone is aware of their product's value and availability, or that marketing research would only tell them what they already know. To develop effective marketing outreach efforts for these audiences, Extension educators need to develop analyses that producers find both persuasive and relevant.

For many years, food producer groups directed their financial resources toward production research and encouraged public support for similar projects. However, increased competition from highly-processed items lead some groups to study how to add more value to their products. The author developed presentations on the value of marketing for many regional, state, national, and international food and small business groups. These programs were intended to help the business people evaluate whether increased consumer marketing and marketing research could generate significant benefits.

Perceptions of high costs and limited benefits often restrict support for these projects. Fact-based examples were developed to show how inexpensive research could magnify the effectiveness of marketing efforts. The examples were very popular and appeared to overcome the skepticism that some had for marketing.

This paper highlights several examples from these presentations to help others who may speak to similar audiences. First, the sales development indices are described, examples showing regional variations are reviewed, and the importance of product form is illustrated. Then applications are discussed where the indices are used to identify possible promotion partners and to rank markets based on sales variation. The final section summarizes the conclusions. Although evaluations of the presentations were primarily qualitative (and quite positive), one group decided to conduct a national consumer survey to better understand sales trends after seeing this and other information.

Development of Marketing Research Examples

Many manufacturers segment their markets and target particular buyers or geographies with extra promotions. Skews in consumption patterns help them direct marketing efforts at heavy buyers or other segments with significant profit potential. For organizations and businesses without funds for national marketing programs, selecting the best regions to target is important. Examples of regional consumption patterns may help convince producers to study their category's patterns.

Arbitron/SAMI, a marketing information company, collected sales data from grocery warehouses and sold it to clients for more than 25 years. They provided very accurate sales estimates by using a near-census of warehouses and tabulating the sales when products were withdrawn from warehouses and transported to stores. Clients, both supermarkets and manufacturers, helped to define meaningful product categories and market areas. The company prepared an annual report that indexed each category's dollar sales per household by market to the U.S. average.

Their 54 Selling-Areas Marketing Inc. (SAMI) markets, listed in Table 1, covered more than 88 percent of the grocery sales in the lower 48 states. The 1990 sales development (dollar sales per household) indices for 126 food categories by SAMI market were analyzed to illustrate the potential gains from marketing research and from targeted promotions.

Table 1
SAMI Market Abbreviations and Market Names
DALDallas-Ft. WorthDENDenver
DETDetroitELPEl Paso-Albuquerque
GBYGreen BayGRNGreenville-Spartanburg, SC
G/KGrand Rapids-KalamazooHOUHouston
HRTHartford-New Haven, CTINDIndianapolis
JACJacksonville-Orlando-TampaKASKansas City
LOALos Angeles-San DiegoLVLLouisville-Lexington, KY
MEMMemphis-Little RockMIAMiami
MILMilwaukeeMINMinneapolis-St. Paul
NFKNorfolk-RichmondNORNew Orleans
NSHNashville-Knoxville, TNNYCNew York
OKLOklahoma CityOMHOmaha-Des Moines
PEOPeoria-Springfield, ILPHIPhiladelphia
PITPittsburghPMEPortland, ME
PORPortland, ORP/TPhoenix-Tucson
QUAQuad CitiesRALRaleigh-Greensboro
SCRScranton-Wilkes-Barre, PASEASeattle-Tacoma
SFRSan FranciscoSHVShreveport-Jackson
SLKSalt Lake City-BoiseSLOSt. Louis
SPKSpokane-Yakima, WASYRSyracuse
S/CSan Antonio-Corpus ChristiWCHWichita

Variations in Regional Consumption Patterns by Category

Table 2 shows the twelve SAMI markets with the highest and lowest sales development indices for six categories. In the Peanut Butter and Peanut Butter Combinations category, dollar sales per household in the Grand Rapids-Kalamazoo market were 72 percent higher than the national average in 1990. Shreveport- Jackson had the lowest category consumption per household, 42 percent below average.

Most strong markets were in the North and most weak markets were in the South (the thirty markets between the strongest and weakest markets are not shown). Three large markets, New York, Los Angeles-San Diego, and Baltimore-Washington had some of the lowest indices. The twelve low markets represented 29.9 percent of U.S. households. If consumption in these low markets could be raised to the level in Grand Rapids-Kalamazoo, national peanut butter sales would increase more than 30 percent.

Regional sales patterns varied by category. Sales indices for Canned Peaches ranged from 160 to 71. Most strong markets were in the Central region while the weak markets were geographically dispersed. If consumption in the 12 weakest markets could be increased 50 percent, national canned peach sales would grow by 15 percent. For Frozen Strawberries, most weak markets were in the East-Central part of the U.S. Strawberry growers could boost frozen strawberry sales by nearly 50 percent if they convinced East-Central residents to consume the product at the same rate as those in the strongest markets. Many food categories have even wider ranges in their sales development indices.

Table 2
Sales Development Indices Rankings for Six Categories
SAMI Market RankPeanut Butter & P.B. Combos Frozen Canned PeachesCanned StrawberriesFrozen Apple-sauce Apple JuiceShelf-Stable Apple Juice
43NOR- 86SLK- 92CIN- 85OKL- 70QUA- 53IND- 60
44CSV- 86GBY- 91CSV- 84DAL- 69IND- 51DEN- 60
45SLO- 86CHI- 90ATL- 81S/C- 57SLO- 49CLE- 57
46B/W- 85SFR- 88IND- 81MEM- 57CLE- 47NSH- 57
47LOA- 84LOA- 87NYC- 74HOU- 57CSV- 46SHV- 54
48S/C- 84PHI- 81NFK- 73ATL- 56MIA- 46LVL- 54
49NYC- 82NSH- 79C/H- 71CSV- 55ATL- 36MIN- 53
50HOU- 81DEN- 77CLE- 71ELP- 54BIR- 33CIN- 52
51NSH- 76SYR- 77LVL- 68BIR- 48NSH- 32GBY- 51
52ATL- 73BOS- 76SHV- 64NSH- 47LVL- 30PEO- 50
53MIA- 70B/W- 71NSH- 58NOR- 36SHV- 29C/H- 47
54SHV- 58ATL- 71B/W- 57SHV- 27C/H- 25QUA- 46

Variations in Regional Consumption Patterns by Product Form

Many factors contribute to regional sales variations. An example is the popularity of apple products varies by form. Residents of the Northeast bought the most Canned Applesauce while those in the South bought the least. Frozen Apple Juice/Cider is strongest in the Northwest and weakest in the South while Shelf-Stable Apple Juice is most popular in the Northeast and least popular in the Midwest. Differences in when and how the products are consumed along with demographics, tastes, and traditions may explain some regionality and suggest strategies for increasing sales. Failure to account for these differences could limit the effectiveness of marketing programs.

For some products with multiple forms, the popularity of the forms is inversely related across markets. For example, Frozen Peas are strongest in the North and weakest in the South while Canned Peas are the strongest in the South and weakest in the North. The correlation between the indices for Frozen Peas and Canned Peas is -0.48. This surprising result suggests that pea growers should consider product form when they conduct research and design marketing programs. A similar regional reversal did not appear for Frozen Corn and Canned Corn. The Southwest is the strongest region for both forms. The correlation between the indices is +0.53. To boost corn consumption, producers might study buying habits in the Southwest and try to increase purchase frequency. They could promote similar recipes to people in other areas. From these and other examples, producers can learn about the potential payoff from regional analysis and market segmentation by product form.

Identifying Possible Promotion Partners with Regional Data

Many organizations lack the funds to support complete national marketing plans and are interested in small programs with high returns. To increase the sales gains per dollar of marketing expense, marketers often target key geographies, customize promotions for local conditions, and find complementary products that can be marketed together.

The response to promotional events varies by market. Wittink, Addona, Hawkes & Porter (1987) found significant differences in the price elasticity and the promotional multipliers for tuna by market. Hoch, Kim, Montgomery & Porter (1995) found large differences in price and promotion elasticities between stores for one chain in the same city. Promotions judged to be successes in one area may not succeed in others. Events can often be enhanced by studying the barriers to sales growth in an area and adjusting the event using historical, market-level promotion efficiency information.

Searching the product universe for items with compatible buyer profiles may exceed the research budgets of producers. An option is to narrow the search for promotion partners to compare regional sales indices. If the goal is to find a partner whose sales are strong in the same markets as the producer's product (i.e., increase sales among current users), items with similar (positively correlated) regional indices may be good candidates. If the strategy is to increase sales among infrequent and non- users, items that are strong where the producer's product is weak may be better choices.

To illustrate this approach, Pearson correlation coefficients were generated using the market-level development indices for 126 of the larger Arbitron/SAMI food categories. Categories with significant store delivery (i.e., volume may not pass through warehouses) or with limited availability during part of the year were excluded. Products with the highest and lowest correlations are partner candidates. For Peanut Butter and Peanut Butter Combinations (Table 3), Canned Soup has the highest correlation, +0.86, indicating that their regional patterns are very similar. Canned Sardines, Dried Rice, and Frozen Sweet Goods have the largest negative correlations, suggesting that they might be good promotion partners to boost sales in areas with below average indices.

The categories with the highest correlations with Canned Peaches (Table 4) included Canned Green Beans (highest positive correlation) and Frozen Green and Wax Beans (highest negative correlation). This is another example that shows how important product form can be to marketers. By conducting research and forming partnerships with others who have complementary marketing goals, the efficiency of their promotional spending may be enhanced.

Table 3
Product Categories with the Highest Positive and Negative Correlations with the Peanut Butter & P. B. Combos Category
 Correlation Coefficient
Canned Soup+0.86
Brown Sugar+0.76
Low/Reduced Calorie Salad Dressings+0.75
Ready-to-Eat Cereal+0.75
Frozen Sweet Goods-0.27
Dried Rice-0.33
Canned Sardines-0.37

Table 4
Product Categories with the Highest Positive and Negative Correlations with the Canned Peaches Category
 Correlation Coefficient
Canned Green Beans+0.71
Canned Pineapple+0.64
Ready-to-Spread Frosting+0.61
Canned Pie Fillings+0.60
Frozen Italian Dishes-0.28
Shelf-Stable Blended Fruit Juice-0.33
Frozen Green & Wax Beans-0.36

Comparing Consumption Variations Between Markets

Some markets have higher sales indices or greater dispersion than others. Table 5 shows that many markets in the South and West had more variation in their indices while markets in the East and Midwest often had less. Differences in household sizes, income levels, product prices, preferences for pre-packaged foods, and tastes for home-cooked versus prepared meals could affect the index levels and dispersions.

If marketers test new products in only part of the country, these results suggest that projecting the research to the national level may be difficult. Sales in a Southern or Western market, even when adjusted by the number of households, may not be indicative of the product's performance in other markets. If food producers rely on volume data from the East or Midwest to forecast demand and capacity requirements as products enter new markets, they could underestimate their needs. Index means and variances may help forecasters adjust their volume estimates and be more accurate. Regionality of food consumption is an important variable that marketers should consider whenever they try to generalize about product performance or about promotion efficiency across markets.

Table 5
SAMI Markets with the Highest and Lowest Standard Deviations for their Sales Development Indices Across 126 Categories
Market RankSAMI MarketMean Sales Development Index Standard Deviation
1Salt Lake City-Boise126.1358.76
2Memphis-Little Rock124.2251.58
3Greenville-Spartanburg, SC106.7650.52
5San Antonio-Corpus Christi119.5450.05
6Portland, OR117.8349.75
7New Orleans118.3348.37
8El Paso-Albuquerque117.6446.67
9New York108.7946.27
10Spokane-Yakima, WA105.8045.86
12Grand Rapids-Kalamazoo119.0242.06
44Quad Cities74.6127.40
45Peoria-Springfield, IL85.8925.03
46St. Louis96.8225.03
49Nashville-Knoxville, TN68.5523.37


Until business people believe marketing research could generate returns as high as production research, few analyses on their buyers and markets will be done. When examples similar to those in this paper were shared with producers, they became more enthusiastic about marketing research. Although most understood that food preferences vary by region, they were surprised by large regional differences for basic foods. With this type of information, marketers can identify areas that may be good candidates for regional events. More work may be needed to understand the sales barriers and to select the best marketing tools for each area. However, the potential gains from targeting weak markets and raising their consumption rates stimulated considerable interest.

Another key for making these Extension presentations effective was that the empirical measures were easy to understand. Indexes, means, correlations, and variances can be explained to business people who do not have advanced statistical training. The sales development indices made it possible to illustrate the potential value of marketing research. Simple analyses of the indices can identify when product form is a key variable, can help find compatible promotion partners who could enhance the efficiency of marketing spending, and can suggest adjustments for forecasts based on sales from a small number of areas. Although producer groups and small businesses may never spend as much on marketing as some large consumer packaged goods firms, they can learn from marketing research and develop beneficial programs.


Hoch, S., Kim, B., Montgomery, A., & Rossi, P. (1995). Determinants of store-level price elasticity. Journal of Marketing Research. 32(1), February, 17-29.

Wittink, D., Addona, M. J., Hawkes, W. J. & Porter, J. C. (May 1987). SCAN-PRO: A model to measure short-term effects of promotional activities on brand sales, based on store-level scanner data. Cornell University Johnson Graduate School of Management Working Paper.