Meeting clientele needs has become increasingly difficult for Extension, as the audiences have increased and diversified. At the same time, resources have diminished (Smith & Swisher, 1986). Some systems have sought differing solutions to address these issues including building relationships with other service organizations (Martin-Milius, 1994). Studying customer satisfaction can establish how well these solutions work. It can provide a benchmark for future work (Radhakrishna, 2002).

Kansas counties have had strong Extension programming and maintained strong support in general from county boards. However, Kansas has seen increasing urbanization. In 2002, K-State Research and Extension realigned its areas, forming one of its five areas based not on geography but on population. This area is comprises the most populous counties in the state. Prior to the formation of this new area, ten of the most populous counties in the state decided to devise a marketing plan together and to collect data upon which to base that plan. The counties were different in many ways, but facing a common issue: a dramatically changing county population. Kansas population grew 8.5% from 1990 to 2000, but these counties saw growth of 10% on average, indicating that much of the increase in population came from these more populous counties. These counties tended to have higher percentages of ethnicity and Hispanics. The percent of people under 18 years old also is higher in these counties than in the state in general. Income and percent of people living in poverty is variable in these counties with some of the highest and lowest incomes and percentages in the state, further indicating the diversity in these counties. Despite growth in population, agriculture is still the highest land use in these areas (USDA Kansas Agricultural Statistics Service, 2001).

Purpose and Objectives

The purpose of this study was to guide county marketing and planning processes. The specific objectives were to compare Extension users and non-users in regard to their satisfaction with Extension, information sought, perceptions regarding importance of programming areas and communications channels, as well as demographic variable such as sex, and age. In addition, we sought information regarding the awareness of Extension from non-users. The results of this study will provide necessary information to assist the ten counties in making a marketing plan of their own that will meet the specific needs of their counties.

Methodology

Surveys were conducted with both users and non-users in late summer and fall 2002. Questionnaires were developed for both groups and based on prior work conducted with Johnson County. The instruments were tested when the work with Johnson County was conducted in 1996. County offices submitted mailing lists for their users. A random sample of 150 was drawn from each list, and those users were mailed questionnaires. The goal was to receive 50 to 100 responses. For the non-user contacts, a sampling company in Connecticut was contracted to draw random telephone numbers for the 10 counties. The random lists included 450 numbers per county. Again the goal was to receive responses from 50 to 100 people. The telephone survey was conducted by trained data collectors

Data were analyzed in the Department of Communications using the personal computer version of SPSS/PC+. Descriptive statistics were calculated on the findings.

Results

Data were collected from 1,466 known Extension users and 449 people who were randomly sampled from the same counties (referred to as non-users for this report). The summary data are presented here. For both samples, more women responded than men, although the percentage of men responding was not particularly low. In comparing users to non-users, users were generally older and had higher household income levels. More than 40% of non-users were younger than 45, while only 22% of users were under 45. Almost ¼ of non-users had incomes of less than $20,000 per year, while only 6% of users fell into the same category. Thirty-five percent of users had household incomes of $40,000 or less, while 53% of non-users earned $40,000 or less per year (Table 1).

Table 1. Demographic Summary of Users and Non-users

Variable % User % Non-user

Age

18-34 5 22

35-44 17 20

45-54 28 19

55-64 16 15

65-74 19 12

75+ 16 12

Gender

Male 43 32

Female 57 68

Income

<$20,000 6 24

$20,000-40,000 29 29

$41,000-60,000 27 24

$61,000-80,000 17 9

$81,000-100,000 12 8

>$100,000 9 6

____________________________________________

User N = 1466

Non-user N = 449

Among non-users there was significant recognition of the organization, much more so than in previous statewide surveys. Seventy percent had heard of the organization, and 56% correctly identified its affiliation with Kansas State University. Almost 40% indicated they had used the service at one time (Table 2).

Table 2. Non-user Familiarity with K-State Research and Extension

Variable %

Heard of Organization

Yes 70

No 30

Used Service

Yes 37

No 63

University Affiliation

K-State 56

KU 12

Don’t Know 23

No answer 9

Other university 3

___________________________

Both user and non-user groups indicated satisfaction with the services/materials they had received from K-State Research and Extension (Table 3). This question was asked only of the non-users who had indicated they had received information/services from the organization. Of the users, 95% indicated that they were very satisfied or satisfied, while 93% of non-users indicated the same.

Table 3. Satisfaction with K-State Research and Extension

Level of Satisfaction % Users % Non-users

Very Satisfied 64 71

Satisfied 31 22

Neutral 2 6

Dissatisfied 2 1

Very Dissatisfied 1 0

____________________________________________

Data on preferred methods of delivery for educational information are presented in Table 4. For this question, respondents were asked to rate each method on a scale of 1 to 5, with 1 being not very likely to use and 5 being very likely to use. The mean is the average of the ratings, while the standard deviation (s.d.) provides a measure of the dispersion of the data. The mode is the most frequently occurring category, and like the mean, is a measure of central tendency. The ranking based on means is presented as another way to compare the methods.

Among users, newsletters were the most highly rated method, followed by newspaper and classes/meetings. Television, which was not rated highly overall, received ratings of 5 from more than 20% of users, indicating that it is used highly by a portion of the group but not overall. Eighty-five percent of users indicated that they read the county Extension newsletter.

The non-user group rated the methods differently. Newspaper, television, and radio were rated the highest. Classes/meetings were rated lowest. The Internet was rated by 35% of non-users as not very likely to use, but 27% rated it as very likely to use, indicating that they either rely on it heavily or not at all.

Table 4. Preferred Methods of Educational Information Delivery

User Non-user

Method Mean s.d. Mode Rank Mean s.d. Mode Rank

Newsletter 4.35 1.11 5 1 2.94 1.43 2 4

Internet 2.65 1.55 1 6 2.92 1.64 1* 5

Newspaper 3.56 1.39 5 2 3.63 1.32 5 1

TV 2.86 1.48 1* 4 3.62 1.27 5 2

Radio 2.83 1.49 1 5 3.28 1.24 3 3

Classes/ 3.19 1.46 3/5 3 2.52 1.30 1 6

Meetings

__________________________________________________________________________

Scale: 1=not very likely to use, 5=very likely to use

*Next most frequently occurring category was 5

Note: Of users, 85% indicated reading the county newsletter

The remaining questions asked both groups about the importance of subject matter areas on which K-State Research and Extension provides information/expertise. The groups were asked to rate the subject areas based on their importance to the respondents as individuals (Table 5) and their importance to the community (Table 6).

Among users, most subject areas were rated as important, with six subjects with modes of great importance (5). The mode for community development was 3, while the mode for family skills was 4. Family skills might have been rated somewhat lower because the user group was older. While the farming/ranching mode was 5, the next most frequently occurring category was 1, indicating a split distribution. Responses for environmental preservation and family skills clustered around ratings of 3, 4, and 5.

Non-users also rated subject areas highly, with all but farming receiving a mode of 5. Farming/ranching had the lowest mean and mode.

When asked to describe the importance subject areas to their communities, both user and non-user groups showed greater agreement. Standard deviations for every subject area decreased when compared to the data related to importance on an individual basis. Thus, there was less variability and greater agreement exhibited in the data.

Users rated every subject area high for the importance in the community, with each having a mode of 5. Modes for non-users were 5 in each area, except lawn and gardening where they were equally split between 3 and 4. Interestingly, farming and ranching, which had a mode of 1 for individual importance to non-users, had a mode of 5 when the group viewed its importance to the community. This probably relates to the recognition of the economic value of agriculture to the community.

Table 5. Importance of Subject Matter to Individual

User Non-user

Subject Area Mean s.d. Mode Rank Mean s.d. Mode Rank

Farming/ranching 3.34 2.44 5* 6 2.60 1.59 1 7

Environmental 3.46 1.36 5** 4 3.70 1.32 5 4/5

preservation

Community 3.15 1.20 3 8 3.70 1.16 5 4/5

development

Family skills 3.33 1.38 4** 7 3.87 1.26 5 3

Health and safety*** 3.63 1.25 5 3 4.13 1.11 5 1

Youth development 3.43 1.46 5 5 3.88 1.25 5 2

Lawn/gardening 4.06 1.11 5 1 3.39 1.34 5 6

Food and nutrition 3.68 1.29 5 2

______________________________________________________________________

Scale: 1=little or no importance to you, 5=great importance to you

*Next most frequently occurring category was 1

**Categories of 3, 4, and 5 all with greater than 20 percent

***Included description of food and nutrition in phone survey

Table 6. Importance of Subject Matter to Community

User Non-user

Subject Area Mean s.d. Mode Rank Mean s.d. Mode Rank

Farming/ranching 3.83 1.35 5 6/7 3.47 1.45 5 6

Environmental 3.91 1.15 5 4/5/6 3.83 1.13 5 5

preservation

Community 3.91 1.16 5 4/5/6 4.09 1.04 5 2

development

Family skills 3.83 1.15 5 6/7 4.00 1.05 5 3

Health and safety* 3.91 1.14 5 4/5/6 4.20 0.96 5 1

Youth development 4.05 1.16 5 1 4.07 1.08 5 4

Lawn/gardening 4.00 1.08 5 2 3.41 1.18 3/4 7

Food and nutrition 3.98 1.12 5 3

______________________________________________________________________

Scale: 1=little or no importance to you, 5=great importance to you

*Included description of food and nutrition in phone survey

Conclusions

Among non-users there was strong awareness of K-State Research and Extension and recognition of the tie to Kansas State University. This indicates success of these identity awareness programs.

Among those who had used K-State Research and Extension, there were high levels of satisfaction, both among users and non-users. Users differ from non-users in several important areas, and some of these are demonstrated by demographics. Users tended to be older and had higher incomes. They also preferred traditional methods of information delivery (newsletters and classes/meetings). Non-users were more oriented to mass media, which might be used to create more awareness and bring them to reliance on newsletters, etc. Among non-users, those who use the Internet rely on it for information but those who do not use the Internet did not value it as an information delivery method, a finding that demonstrates the digital divide.

Respondents rated Extension’s subject areas as important for almost every category. Among users, the overall rating of farming/ranching was high, but there was a split in those data, with many users indicating it was unimportant to them. Users also exhibited less agreement on environmental preservation and community development, perhaps because these are considered more societal goods than individual goods.

There was greater agreement about the importance of subject areas to the community, with high ratings to all subjects. These data can be interpreted as community values/benefits. As one writes key messages they may consider positioning messages as individual or community benefits.

From a marketing perspective, these data could be used to build strategies to reach key audiences and reach beyond traditional clientele groups. Mass media may be an important tool for reaching these non-users. Once they have greater awareness of the organization, they may become more reliant on more traditional informational tools, especially newsletters. Given the pace of lifestyles today, it is doubtful that classes/meetings will grow much in popularity, but may be more important for particular hands-on/interactive learning activities or for particular targeted groups. The Internet also holds potential here. It is important as well to remember to provide existing users with the information and informational tools that they value and to continue to serve their needs.

References

Boone, K.M., & Furbee, R. (1998). Are you being served? Gauging customer service. Journal of Applied Communications, 82 (3), 7-19.

Chapman-Novakofski, K., Boeckner, L.S., Canton, R., Clark, C.D., Keim, K., Britten, P., & McClelland, J. (1997). Evaluating evaluation -- What we’ve learned. Journal of Extension, 35(1). <http://www.joe.org/joe/1997february/rb2.html>

Greene, S.S. (1995). Cooperative Extension: The service challenge. Journal of Extension, 33(6). < http://www.joe.org/joe/1995december/comm1.html>

Martin-Milius, T. (1994). University to community and back: Creating a customer focused process. Paper presented at the Fifth Annual Conference on TQM in Colleges and Universities: Reengineering the University. Chicago, IL.

Radhakrishna, R. (2002). Measuring and benchmarking customer satisfaction: Implications for organizational and stakeholder accountability. Journal of Extension, 40(1). <http://www.joe.org/joe/2002february/rb2.html>

Rennekamp, R.A., Warner, P.D., Nall, M.A., Jacobs, C., & Maurer, R.C. (2001). An examination of customer satisfaction in the Kentucky Cooperative Extension Service. Journal of Extension, 39(2). < http://www.joe.org/joe/2001april/rb5.html>

Smith, M.F., & Swisher, M.E. (1986). The best little programming tool in Extension: Audience identification helps determine needs and justify programs. Journal of Extension, 24(3). <http://www.joe.org/joe/1986fall/a3.html>

U.S. Census (2001). State and county quick facts for Johnson County, Kansas. <http://quickfacts.census.gov/qfd/states/20/20091.html>

U.S. Department of Agriculture, Kansas Agricultural Statistics Service. (2001). 1997 Census of Agriculture County Profile, Johnson, Kansas. Available at <http://www.nass.usda.gov/census/census97/profiles/ks/ks.htm>

What Do They Want From Us?
Communications Programming Preferences Among Extension Users and Non-Users

Abstract

Methodology

References

Radhakrishna, R. (2002). Measuring and benchmarking customer satisfaction: Implications for organizational and stakeholder accountability. Journal of Extension, 40(1). <http://www.joe.org/joe/2002february/rb2.html>

What Do They Want From Us? Communications Programming Preferences Among Extension Users and Non-Users

Abstract

Methodology

References

Radhakrishna, R. (2002). Measuring and benchmarking customer satisfaction: Implications for organizational and stakeholder accountability. Journal of Extension, 40(1). <http://www.joe.org/joe/2002february/rb2.html>

What Do They Want From Us?
Communications Programming Preferences Among Extension Users and Non-Users