Developing Effective Marketing Strategies for Agritourism: Targeting Visitor Segments

Martha Sullins, Drew Moxon, and Dawn Thilmany McFadden

In Colorado, agritourism shows the potential to benefit agricultural producers and rural communities by generating additional income from consumers who are willing to pay for rural and agriculturally related experiences. This study uses a survey of Colorado agritourists to identify five distinct groups of visitors using demographics, attitudes, expenditures, and activity types. The visitor clusters are significantly different when considering types of travel planning and transportation, agritourism participation, and importance of agritourism to the travel party’s visit, among other behaviors. We conclude with a discussion of the marketing and joint planning implications for agritourism providers, the tourism industry, and Colorado communities.

Key Words: agritourism, cluster analysis, consumer segmentation, marketing, regional economic development

Agritourism is a recreational sector that appears to be gaining ground in terms of traveler awareness, media exposure, and adoption by agriculturalists looking for diversified income streams. Agritourism is defined as “a commercial enterprise at a working farm, ranch, or agricultural plant conducted for the enjoyment of visitors that generates supplemental income for the owner” (UC-Davis Small Farm Center, 1999, p. 3). Colorado’s agricultural communities, with their rich natural amenities, are particularly well-suited to growing this sector to the benefit of the greater state economy. Recent data prove these opportunities are, in fact, being recognized in Colorado. According to the 2007 Census of Agriculture, of those Colorado farms that offer agritourism products and services, the average farm went from earning less than $14,000 per year from agritourism and recreation in 2002 to over $48,000 per year from such activities in 2007 [U.S. Department of Agriculture (USDA), 2007]. The role of agritourism in generating income is recognized, but it is less clear how the sector is viewed by local tourism organizations or community leaders. —————————————— Martha Sullins is research associate, Drew Moxon is graduate research assistant, and Dawn Thilmany McFadden is professor, all with Colorado State University Extension and the Department of Agricultural and Resource Economics. The authors wish to acknowledge support for this study from the Colorado Department of Agriculture and the Colorado Agricultural Experiment Station. State funds for this project were matched with Federal funds under the Federal-State Marketing Improvement Program of the Agricultural Marketing Service, U.S. Department of Agriculture. Additional funding was provided under a Western Region Sustainable Agriculture Research and Education Professional Development Program grant.

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County-level officials, particularly in rural, farm-based counties, have begun to look at the economic impacts of agritourism. Veeck, Che, and Veeck (2006) suggest that beyond the obvious wage and employment benefits provided by agritourism, an expansion of the local tax base is also likely. Similar to the smoothing of revenue flows for farmers, the increased tax base could provide benefits for local governments during recessionary periods where tourists tend to favor lower- cost tourism activities such as agritourism over more costly travel. Although there is little research documenting agritourism’s exact role in tourism during economic downturns, Colorado Tourism Office (2010) data show that the numbers of overnight touring trips, country resort trips, special event trips, and day trips to and within Colorado all increased from 2008 to 2009 (a documented recessionary period), but total expenditures on such travel decreased over this same period, suggesting travelers chose lower-cost travel options. In fact, there are already recognized spillover effects in agricultural economies proximate to urban areas. In the northeast and Atlantic states, early recognition of the community economic benefits of agritourism has resulted in state-level support and promotion in the form of information networks and conferences on agritourism. For example, the state of New York’s Department of Agriculture and Markets published a guide in collaboration with AMTRAK to promote agritourism trips throughout the state. The New Jersey Department of Agriculture has developed a web site that consumers can use to search for agritourism products and events by location and activity. “HandgrownHomemade” is a collaboration among four North Carolina organizations, including the North Carolina Arts Council, North Carolina Cooperative Extension, HandMade in America, and Golden Leaf, to promote rural farm destinations across the state by creating trails and driving tours. Finally, Pennsylvania’s Center for Rural Pennsylvania published a 2006 study and guide on agritourism (online at http://www.rural.palegislature. us/agritourism2006.pdf ). In addition, tourism commissions are beginning to focus on agritourism as a relatively untapped sector of the market. McGehee (2007) examines the relationship between agritourism providers, tourism agencies (destination marketing organizations, or DMOs), and the agritourists themselves. She finds that DMOs can educate agritourism providers who are not accustomed to the tourism industry. She also reports that less than 10% of small farm families offering agritourism are using any type of regional DMO. As the relative impacts of agritourism continue to grow, the sector is likely to garner more attention from the broader tourism community. However, new resources will be invested and used effectively only if the sector can be defined and understood as well as other potentially competing sectors (e.g., skiing, camping, golf ). Perhaps some of the disconnect relates to the lack of understanding of the “who, why, and how” of agritourism. As a starting point to bridge this informational gap, we use a statistical cluster analysis applied to a 2006 survey of Colorado agritourists to identify five distinct groups of visitors who are then defined using demographics, attitudes, expenditures, and their reported types of agritourism activity.

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The goals and intended outcomes of this cluster analysis are to provide more specific information on likely visitors to agritourism enterprises in Colorado as a means to help operators plan for and target appropriate visitors. If agritourism operators identify their intended customer base and use their business development resources in a more efficient manner, their operations and surrounding communities will benefit (e.g., marketing through channels already used by target customers or improving access to community activities that are appealing to those customers might encourage them to stay longer or increase their expenditures on agritourism activities). The remainder of the paper proceeds as follows. First, we discuss the background research that informed this study, followed by a summary of the data and methodology used. An overview of our findings is then provided, including the cluster analysis and tests for significance across groupings of travelers. The last two sections discuss the possible implications for agritourism businesses and rural communities in Colorado and other regions with similar characteristics, as well as future research directions.

Background Research

Colorado’s tourism industry as a whole grew over 20% from the early 1980s to the late 1990s (Wilson, Thilmany, and Sullins, 2006). More specifically, the authors note that recreational activities contributed 13% to farm income for producers in 2002, which had increased to nearly 18% as of the 2007 Census of Agriculture. Some of the growth may be driven by the amenities available on Western ranches and farms. In the broader Western region, Wilson, Thilmany, and Watson (2006) found that Conservation and Wetland Reserve Conservation programs have a positive relationship with recreational income in rural Western counties, but only when investments are made in sufficiently large tracts within those counties. As public lands open to hunting and fishing become more scarce and crowded, demand for these types of services on private land should continue to increase, especially since some private lands are managed specifically to improve habitat for small or large game hunting species. This dynamic is common to the Western United States. However, the Midwest and Eastern areas of the country have more limited public land resources for recreation; thus, there is already significant demand for private land access. Tchetchik, Fleischer, and Finkelshtain (2008) evaluated trends in the Israeli rural tourism market with regard to producers and the role government policy could play in encouraging synergy between agritourism and farming. They proceed to show that there are technological synergies on the supply side to support the argument for adding “rural tourism” services to the portfolio of traditional farm products and services. This type of additional income and productivity gain has represented a new opportunity for farmers to smooth revenue volatility caused by changes in market prices for their product. By offering a farm tour or providing

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lodging in dude ranch cabins, farmers are now able to reach a new segment of the population that was previously unaware of rural tourism experiences. Despite the seemingly stronger demand for these services, few studies have been conducted to identify the specific characteristics of agritourism participants—information which would vastly improve business-level and regional marketing efforts. A study by Jolly and Reynolds (2005) reveals demographic profiles, as well as consumer preferences and motivations of participants in Cali- fornia agritourism. The authors conclude that consumers are indeed willing to pay for various on-farm experiences, but the experiences they desire differ depending on whether the participant is an urban-based or rural-based visitor to the agritourism site. Jolly and Reynolds note that understanding consumer motivations and expectations and identifying specific market segments enables agritourism operators to develop their scopes of business and target their marketing efforts more effectively. Carpio, Wohlgenant, and Boonsaeng (2008) use data from the 2000 National Survey on Recreation and the Environment to estimate participation in agritourism based on visitor characteristics (such as education, race, gender, age, employment, and income), as well as trip characteristics (distance traveled, trip cost, and importance placed on a rural landscape). According to their findings, race, location of residence, income, and number of children all positively influence the decision to participate in agritourism (denoted as “visit a farm” or “do not visit a farm”). While their research provides broad demographic information on potential agritourists, it does not identify specific target groups beyond families with children. The authors do find that consumers gain a significant economic benefit from the rural landscape, which provides additional justification for the protection of working farms.

Data and Methodology

Tourism research can serve a number of purposes, and the broader project under- pinning this study included economic impact analysis, regional studies of Colorado agritourism, and travel behavior (Gascoigne, Sullins, and Thilmany McFadden, 2008; Thilmany, Sullins, and Ansteth, 2007). The objective of this study—to provide market research that would help agritourism operators better understand their potential customer base and relevant travel behaviors—was accomplished by grouping travelers with similar behaviors into clusters. Travelers were segmented into populations who plan, travel, and recreate similarly when in Colorado as a way to understand and target different types of travelers with specific marketing and promotion programs and activity packages. In order to build profiles of consumers who participate in agritourism in Colo- rado, the consumer survey was developed to assess traveler information about recent trips to Colorado, planning resources, demographics, and plans for future travel. As one major criterion to determine our survey sample and segment the travel population, we asked respondents to identify whether they traveled from

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out of state into Colorado for agritourism, or if they were residents who traveled in-state, yet outside of the city in which they lived, to participate in agritourism activities. We then used the data to conduct a cluster analysis to statistically classify consumers into five clusters in order to identify differences in trip expenditures, demographics, and travel behavior among clusters of visitors. In 2007, Colorado State University (CSU) contracted with National Family Opinion (NFO; http://www.tns-us.com/) to implement a web-based survey targeted at travelers to and within Colorado during 2005 and 2006. NFO distributed the survey to individuals already taking part in their established panel, but filtered the samples to include only those who had visited Colorado during the 2005/2006 time frame. These samples were then stratified according to certain demographic characteristics such as age, income, race, and education to ensure they were representative of the broader U.S. population. Respondents who met these criteria were invited by NFO to participate in the survey, and they received “reward” points from NFO for completing the survey (through an incentive program NFO maintains). NFO managed the sampling process according to CSU’s research specifications and continued contacting potential respondents until a balanced sample was achieved. Of 1,003 total survey respondents, 503 were from Colorado and 500 were from targeted metro areas in adjacent states (hereafter referred to as out-of-state). Overall, there was a 38% response rate to the web survey. The targeted out-of- state areas were Salt Lake City, Utah; Albuquerque/Santa Fe, New Mexico; and Phoenix, Arizona—chosen because the Colorado Tourism Office (2007) reported that the incidence of travel to Colorado from these metro areas was high and representative of a large share of out-of-state travelers. A national sample would have been even more representative, but budget constraints required us to narrow the geographical scope of the survey. Consequently, a fairly representative sample of visitors to Colorado was obtained, except for light representation of respondents reporting Hispanic ethnicity (a challenge faced by many surveys). Individuals were presented with a nested question in which they were first asked if they had traveled to Colorado in 2005 or 2006. If they responded “yes,” they were then eligible to take the survey. Subsequently, questions were posed about the respondents’ agritourism experiences. Agritourism was defined for them as a variety of recreational, educational, and other leisure activities and services provided by farmers and ranchers that could take place on or off the farm or ranch. A list of activities was provided—including wildlife, culinary, educational tours, ranch/farm stays, heritage agriculture/cowboy/pioneer activities, and agritainment (mazes, pumpkin patches, festivals). Respondents could refer to this definition during the course of the survey. The set of questions regarding agritourism expenditures referred to the respondents’ most recent trip to Colorado during the 2005/06 time period. To effectively market to the range of travelers who plan and carry out their trips in different ways, it is important to understand their behavior. The five groupings were separated using the k-means clustering technique in STATA (STATA Press,

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2001). This analysis is similar to one presented in Thilmany, Umberger, and Ziehl (2006) where clusters of consumers were identified based on their perceptions of, and expenditures on, natural beef products which were differentiated by varying production protocols and other meat attributes. The k-means technique employs a statistical segmentation process that assembles like-minded consumers into distinct, non-overlapping groups using their similar perceptions and responses. In any iteration, if an observation is closer to the “center” of one cluster, with respect to all other clusters, then the observation is made a member of the cluster to which the mean value is closest. This process is repeated until all observations are reassigned to a cluster.

Travel Clusters: Results from the Survey of Tourists

Results of the consumer survey are shown in table 1, which describes the average traveler to Colorado in 2005/2006. This consumer was a parent with an average income within the $75,000–$125,000 range who was traveling by car. Other characteristics of this average traveler and his/her travel party were as follows: ■ Their trip planning was based on past experience, but agritourism was an unplanned activity. ■ They traveled less than 500 miles to reach their destination and spent more than four days there. ■ They are repeat travelers and plan on visiting Colorado again within the next six months. ■ They base their trip planning mostly on previous experiences. Because there is such great diversity, however, there is probably little value in defining the average agritourism traveler and tourist. The clustering technique allowed us to refine this analysis and identify five distinct groups with relatively similar behavior within traveler groups, but with significant differences relative to the other clusters. When developing these clusters, we used variables that were identified in one of two ways: either by feedback from agritourism operators and other stakeholders or through statistical factor analysis which defined those variables that expressed the greatest variability among travelers. After separating the sample into clusters, it was necessary to conduct several additional steps in order to make the clusters useful to those who will benefit from such market research. First, we tested the means of the variables of each cluster for significance against the means of these same variables for each of the other clusters. The logic behind this step is that it is not really informative to define a group of travelers as unique or different if they do not spend, plan, travel, or participate in agritourism in any way that is different from any other set of travelers. It is these differences that allow for the differentiation used by operators to position their enterprises in the growing niche tourism sector.

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Table 1. Characteristics of Travelers to Colorado in 2005/2006

Average/ Average/ % of % of Variable Respondents Variable Respondents Lifestage of Visitors Distance Traveled to Destination Single 17.7% Nearby 7.6% Older, no kids 15.7% 50–99 miles 9.0% Middle age, no kids 27.1% 100–499 miles 20.1% Parents 39.5% 500–999 miles 9.5% Income Bracket of Visitors Over 1,000 miles 2.2% Under $25,000 15.4% Methods of Activity Planning & Research $25,000–$49,999 23.0% Past experience 58.6% $50,000–$74,999 26.0% Arranged by hotel 4.9% $75,000–$125,000 27.5% Travel website 12.6% Over $125,000 8.1% Personal web search 17.2% Methods of Transportation Travel agency 0.8% Own car 76.7% Colorado Tourism Office 9.0% Rental 13.0% Welcome center 5.8% Tour bus 1.0% Magazines 3.6% Plane 12.4% Mailing 1.0% Borrowed 3.2% Signage 1.2% Importance of Agritourism to Visit Travel association 9.5% Primary focus 17.1% Park brochures 7.0% Secondary 8.0% Regional website 4.9% Unplanned 23.3% Regional brochure 1.4% Timing of Next Visit Recommendations 20.7% No plans 8.0% Other 2.6% 6 months 26.1% During 2007 15.8% Days on trip 4.36 days After 2007 1.2% Agritourism trips in last year 1.97 trips On wish list 3.7% Share of trips in Colorado 50% –74% Type of Agritourism Visited Frequency of activity vs. 2 yrs. ago about the same Food / Culinary 21.2% Number in party 3.18 people Heritage 13.6% Use of outfitter or travel agent 3.0% Ag Education Experience 33.3% Recreational Experience 23.3%

Table 2 represents a cross-sectional analysis of those variables that were different among the different traveler groups defined by the statistical approach. Tables 3 and 4 feature the exact responses by these clusters that, when combined with table 2, identify which cluster is more or less likely to exhibit a particular behavior. For example, the fourth column of row 1 in table 2 shows Colorado Enthusiasts were more likely to use camping (rather than hotels or vacation homes) and travel in their own cars or rental cars (instead of planes, which makes sense because they are traveling in their home state) compared to Activity Seekers.

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Table 2. Unique Characteristics Defining Groups of Travelers to Colorado in 2005/2006 (as determined by variables that differ from other clusters)

COMPARISON CLUSTER REFERENCE CLUSTER Activity Seekers In-State Explorers Colorado Enthusiasts

Activity Travel Method: Own Lodging: Camping*** Seekers — car***, Rental* Travel Method: Own car***, Timing of Next Visit: 6 Rental* months**

In-State Travel Method: Own car**, Lodging: Camping*** Explorers Rental***, Plane** — Type of Agritourism: > 1,000 miles traveled** Educational experience*, Recreational/active* Colorado Travel Method: Own car***, Type of Agritourism: Enthusiasts Rental***, Plane*** Educational experience** — > 1,000 miles traveled*

Agritourism Travel Method: Plane* Adventurers Used outfitter** — — Used travel website* More participation*** Accidental Travel Method: Rental* Higher agritourism Lodging: Camping*** Tourists Used CO Tourism Office* participation* Higher agritourism participation** Used travel agency* Higher share of trips in Higher share of CO trips** Importance of Agritourism to CO** More frequent agritourism vs. 2 Visit: Unplanned*** Importance of years ago* Distance from Destination: Agritourism to Visit: Importance of Agritourism to Nearby** Unplanned*** Visit: Primary***, Unplanned** 500–999 miles traveled*** 100–499 miles traveled* 50–99 miles**, 100–499 miles Type of Agritourism: Food/ Type of Agritourism: traveled*** culinary***, Heritage***, Food/culinary*** Type of Agritourism: Food/ Educational experience***, culinary***, Heritage***, Recreational/active** Educational experience***, Recreational/active***

Note: Single, double, and triple asterisks (*,**,***) denote statistical significance at the 10%, 5%, and 1% levels, respectively. ( extended . . . → )

After testing for these differences, the major differences became part of the criteria used to create labels or titles for the different types of travelers (see column headings for tables 2–4). These titles are somewhat arbitrary, but were developed considering the types of information that, again, allowed agritourism operators to categorize who they were targeting among specific traveler house- holds and why they would do so. As observed in the tables, method of travel to or around Colorado, type of lodging used during the trip, type of agritourism enterprise visited, and importance

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Table 2. Extended

COMPARISON CLUSTER (cont’d.) REFERENCE CLUSTER Agritourism Adventurers Accidental Tourists

Activity Travel Method: Own car***, Travel Method: Own car***, Seekers Rental* Rental* Less agritourism participation* Less frequent agritourism vs. 2 years ago** Out of state* Type of Agritourism: Food* In-State Lower share of trips in CO* Explorers — Less frequent agritourism vs. 2 years ago*

Colorado Less agritourism participation** Enthusiasts Share of trips in CO** — Less frequent agritourism vs. 2 years ago*** Type of Agritourism: Educational experience Agritourism Lower agritourism participation* Adventurers — More frequent agritourism vs. 2 years ago**

Accidental Higher share of trips in CO* Tourists Importance of Agritourism to Visit: Primary*, Unplanned*** 100–499 miles***, 500–999 miles traveled*** — Type of Agritourism: Food/ culinary***, Heritage***, Educational experience***, Recreational/active***

of agritourism to the travel party’s visit appear to be the most common variables that define our clusters as being different and unique. Clusters with different demographic characteristics, travel patterns, and preferences were developed, named, and classified as follows: 1. Out-of-State Activity Seekers (also denoted Activity Seekers and representing 4% of the sample). This cluster is generally made up of out-of-state visitors who are in the middle- to upper-middle income bracket and travel in small parties. They tend to enjoy active, recreational-type agritourism and they take longer trips where agritourism is often unplanned. They plan their travel mostly by internet and choose activities revolving around culinary events and, to a lesser degree,

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on-farm or heritage activities. Although they don’t represent a large proportion of total travel to and within Colorado, they may be an important group to target with any marketing that does occur at the regional or national levels, given their interest. 2. In-State Explorers (30% of the sample). The second largest share of travelers to Colorado is associated with this group, which mostly comprises Coloradans who tour the state in their own cars for long weekends or shorter trips (four days on average). They typically stay in hotels or with friends and family. In-State Explorers are predisposed to a variety of agritourism experiences, but most of these activities are unplanned. Generally, their planned trips are based on past experiences or recommendations from friends and family. They make 41% of their trips in winter, with the remainder primarily in spring and summer. 3. Loyal Colorado Enthusiasts (also called Colorado Enthusiasts and representing 13% of the sample). These visitors are primarily in-state travelers and are parents or couples who return often based on past experiences. They make up the highest share of participants in outdoor recreation on farms and ranches during the summer. This group is most likely to camp and shows significant interest in traveling throughout the state. These individuals plan to participate in a diverse set of agritourism activities and report more visits to agritourism enterprises relative to two years earlier. Most of their trip planning is based on past experiences and personal web searches, implying they tailor their trips specifically to their interests. 4. Family Ag Adventurers (also labeled Agritourism Adventurers and representing 17% of the sample). These agritourists travel the farthest (500 miles or more), mostly in the summer, and spend about five days in Colorado. Although most of their agritourism activities are unplanned, they enjoy half of these activities in Colorado and they pre-plan 25% of their activities based on past experiences and recommendations from others, as well as web-based information searches. They are middle income, willing to visit local enterprises, and will travel long distances to reach a variety of agritourism destinations. However, since these consumers appeared to plan for, or travel to, big family vacations, this group of travelers does not plan to visit Colorado again in the next several years. 5. Accidental Tourists. This cluster, representing more than one-third of all visitors to Colorado (36%), may include the least promising agritourism visitors from a marketing perspective. These individuals visit mostly in summer and winter, either by car or air, and stay mainly in hotels or with friends and family. They travel primarily without children or by themselves, and may be coming for nonrecreational business, or educational or convention activities. Since they are in the state for a few days with small windows of time for leisure, they may look for activities to occupy their free time. In short, however, they are not seeking agritourism activities, and a very low share of their total activities take place in Colorado. Still, they may represent a small opportunity for enterprises near or within the more highly traveled corridors of the state (e.g., the Front Range, along major transportation corridors, and mountain resort areas).

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Table 3. Trip Planning and Travel for Colorado Agritourism, 2005/2006

CLUSTERS: Mean / (Standard Deviation) 1 2 3 4 5 Activity In-State Colorado Agritourism Accidental Seekers Explorers Enthusiasts Adventurers Tourists Variable (n = 897) (4%) (30%) (13%) (17%) (36%) Lodging Camping 0.037 c 0.034 c 0.463 0.103 0.021 c (0.140) (0.175) (0.488) (0.298) (0.135) Friends 0.210 0.295 0.152 0.258 0.302 (0.367) (0.437) (0.336) (0.419) (0.449) Hotels 0.452 0.404 0.227 0.406 0.489 (0.458) (0.477) (0.394) (0.472) (0.486) Resorts 0.110 0.031 0.022 0.058 0.034 (0.281) (0.164) (0.136) (0.225) (0.181) Farms 0.000 0.000 0.007 0.007 0.000 (0.000) (0.000) (0.078) (0.081) (0.000) Bed and Breakfast 0.051 0.022 0.028 0.022 0.009 (0.189) (0.148) (0.160) (0.142) (0.096) Condo 0.082 0.077 0.028 0.066 0.046 (0.268) (0.258) (0.159) (0.250) (0.202) Second Home 0.059 0.027 0.015 0.026 0.032 (0.239) (0.157) (0.109) (0.156) (0.175) Number in Travel Party 2.794 3.157 3.289 3.351 3.142 (1.805) (3.418) (2.107) (2.848) (4.802) Travel Method Last Visit Own Car 0.059 b,c,d,e 0.873 a 0.901 a 0.828 0.676 (0.239) (0.334) (0.300) (0.379) (0.469) Rental 0.824 0.052 a 0.074 a 0.099 0.157 (0.387) (0.223) (0.263) (0.300) (0.365) Tour Bus 0.000 0.007 0.017 0.000 0.015 (0.000) (0.086) (0.128) (0.000) (0.123) Motorcycle 0.059 0.011 0.000 0.000 0.019 (0.239) (0.106) (0.000) (0.000) (0.135) Plane 0.676 0.090 a 0.025 a 0.066 0.157 (0.475) (0.287) (0.156) (0.250) (0.365) Train 0.000 0.000 0.000 0.013 0.003 (0.000) (0.000) (0.000) (0.115) (0.056) Borrowed 0.000 0.034 0.008 0.020 0.049 (0.000) (0.181) (0.091) (0.140) (0.217) Public Transportation 0.000 0.004 0.008 0.000 0.019 (0.000) (0.061) (0.091) (0.000) (0.135) Season of Visit Summer 0.324 0.236 0.686 0.563 0.352 (0.475) (0.425) (0.466) (0.498) (0.478) Fall 0.265 0.288 0.215 0.205 0.188 (0.448) (0.454) (0.412) (0.405) (0.392) Winter 0.294 0.408 0.066 0.093 0.333 (0.462) (0.492) (0.250) (0.291) (0.472) Spring 0.118 0.067 0.033 0.139 0.127 (0.327) (0.251) (0.180) (0.347) (0.333) ( continued . . . )

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Table 3. Continued

CLUSTERS: Mean / (Standard Deviation) 1 2 3 4 5 Activity In-State Colorado Agritourism Accidental Seekers Explorers Enthusiasts Adventurers Tourists Variable (n = 897) (4%) (30%) (13%) (17%) (36%) Method of Activity Planning Past Experience 0.353 0.640 0.760 0.556 0.515 (0.485) (0.481) (0.429) (0.498) (0.501) Arranged by Hotel 0.059 0.049 0.017 0.020 0.074 (0.239) (0.216) (0.128) (0.140) (0.262) Travel Website 0.500 0.135 0.041 0.073 0.136 (0.508) (0.342) (0.200) (0.261) (0.343) Personal Web Search 0.235 0.150 0.240 0.192 0.148 (0.431) (0.358) (0.429) (0.395) (0.356) Travel Agency 0.147 0.000 0.000 0.000 0.006 (0.359) (0.000) (0.000) (0.000) (0.078) Colorado Tourism Office 0.294 0.082 0.174 0.132 0.025 (0.462) (0.275) (0.380) (0.340) (0.155) Welcome Center 0.147 0.060 0.091 0.086 0.022 (0.359) (0.238) (0.289) (0.281) (0.146) Magazines 0.059 0.037 0.033 0.033 0.034 (0.239) (0.190) (0.180) (0.180) (0.181) Mailing 0.000 0.015 0.008 0.013 0.006 (0.000) (0.122) (0.091) (0.115) (0.078) Signage 0.000 0.019 0.033 0.007 0.003 (0.000) (0.136) (0.180) (0.081) (0.056) Travel Association 0.206 0.082 0.116 0.119 0.074 (0.410) (0.275) (0.321) (0.325) (0.262) Park Brochures 0.088 0.045 0.165 0.139 0.022 (0.288) (0.208) (0.373) (0.347) (0.146) Regional Website 0.088 0.056 0.066 0.073 0.022 (0.288) (0.231) (0.250) (0.261) (0.146) Regional Brochure 0.029 0.019 0.025 0.013 0.006 (0.171) (0.136) (0.156) (0.115) (0.078) Recommendations 0.206 0.221 0.174 0.305 0.164 (0.410) (0.416) (0.380) (0.462) (0.370) Other 0.029 0.037 0.008 0.007 0.031 (0.171) (0.190) (0.091) (0.081) (0.173) Used Outfitter 0.147 0.026 0.008 0.020 a 0.034 (0.359) (0.160) (0.091) (0.140) (0.181) Times per year participated 2.265 2.296 2.504 e 2.232 a 1.364 c in agritourism (0.511) (0.512) (0.565) (0.496) (0.559) Share of agritourism trips in 2.912 3.787 e 4.256 e 3.450 0.728 b,c Colorado † (1.545) (1.885) (1.519) (1.696) (1.460) Frequency of activity vs. 2 3.000 e 2.985 3.198 e 2.755 e 0.880 c years ago ‡ (0.853) (0.836) (0.872) (0.909) (1.381)

a Significantly different from Cluster 1 at the 5% level; b significantly different from Cluster 2 at the 5% level; c significantly different from Cluster 3 at the 5% level; d significantly different from Cluster 4 at the 5% level; and e significantly different from Cluster 5 at the 5% level. † Scaled where 1 = 0%, 2 = 25%–49%, 3 = 50%–74%, 4 = 75%–99%, and 5 = 100%. ‡ Scaled where 0 = a lot less, 1 = a little less, 2 = about the same, 3 = a little more, and 4 = a lot more.

Sullins, Moxon, and McFadden Developing Marketing Strategies for Agritourism 123

Table 4. How Travelers Accessed Colorado Agritourism, 2005/2006

CLUSTERS: Mean / (Standard Deviation) 1 2 3 4 5 Activity In-State Colorado Agritourism Accidental Seekers Explorers Enthusiasts Adventurers Tourists Variable (n = 897) (4%) (30%) (13%) (17%) (36%) Importance of Agritourism to Visit Primary Focus 0.118 0.124 0.579 0.265 0.019 c (0.327) (0.330) (0.496) (0.443) (0.135) Secondary 0.176 0.064 0.231 0.099 0.019 (0.387) (0.245) (0.423) (0.300) (0.135) Unplanned 0.647 a,b,c,,d 0.247 0.190 0.636 0.006 (0.485) (0.432) (0.394) (0.483) (0.078) Timing of Next Visit No Plans 0.000 0.090 0.017 0.000 0.142 (0.000) (0.287) (0.128) (0.000) (0.350) 6 Months 0.059 b 0.588 0.405 0.000 0.080 (0.239) (0.493) (0.493) (0.000) (0.272) During 2007 0.235 0.228 0.488 0.000 0.043 (0.431) (0.421) (0.502) (0.000) (0.204) After 2007 0.029 0.022 0.025 0.000 0.003 (0.171) (0.148) (0.156) (0.000) (0.056) On Wish List 0.029 0.071 0.041 0.000 0.025 (0.171) (0.258) (0.200) (0.000) (0.155) Out of State? 1.971 1.378 1.339 1.762 1.645 (0.171) (0.486) (0.475) (0.428) (0.479) Distance from Colorado Destination Nearby 0.235 a 0.064 0.124 0.159 0.012 (0.431) (0.245) (0.331) (0.367) (0.111) 50–99 miles 0.118 c 0.082 0.281 0.113 0.012 (0.327) (0.275) (0.451) (0.317) (0.111) 100–499 miles 0.118 c,d 0.202 0.512 0.371 0.012 (0.327) (0.402) (0.502) (0.485) (0.111) 500–999 miles 0.235 a,d 0.075 0.066 0.311 0.006 (0.431) (0.264) (0.250) (0.465) (0.078) Over 1,000 miles 0.235 0.011 a 0.017 0.046 0.000 (0.431) (0.106) (0.128) (0.211) (0.000) No. Days on Trip 5.882 4.019 4.868 5.086 3.966 (2.567) (2.587) (4.115) (3.938) (2.255) Type of Agritourism Visited Food/Culinary 0.765 a,b,c,d 0.221 0.388 0.371 0.006 (0.431) (0.416) (0.489) (0.485) (0.078) Heritage 0.235 a,c,d 0.116 0.314 0.285 0.006 (0.431) (0.321) (0.466) (0.453) (0.078) Educational Experience 0.500 a,c,d 0.206 0.917 b,e 0.728 0.019 (0.508) (0.405) (0.276) (0.446) (0.135) Active/Recreational 0.265 a,c,d 0.112 0.711 0.523 0.015 (0.448) (0.316) (0.455) (0.501) (0.123)

( continued . . . )

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Table 4. Continued

CLUSTERS: Mean / (Standard Deviation) 1 2 3 4 5 Activity In-State Colorado Agritourism Accidental Seekers Explorers Enthusiasts Adventurers Tourists Variable (n = 897) (4%) (30%) (13%) (17%) (36%) Lifestage of Visitors Single 0.029 0.199 0.157 0.086 0.225 (0.171) (0.400) (0.365) (0.281) (0.418) Older, no kids 0.088 0.142 0.198 0.172 0.154 (0.288) (0.350) (0.400) (0.379) (0.362) Middle age, no kids 0.235 0.273 0.273 0.311 0.253 (0.431) (0.447) (0.447) (0.465) (0.435) Parents 0.647 0.386 0.372 0.430 0.367 (0.485) (0.488) (0.485) (0.497) (0.483) Income Bracket of Visitors Under $25,000 0.059 0.139 0.190 0.079 0.198 (0.239) (0.346) (0.394) (0.271) (0.399) $25,000–$49,999 0.088 0.206 0.240 0.238 0.256 (0.288) (0.405) (0.429) (0.428) (0.437) $50,000–$74,999 0.265 0.240 0.182 0.377 0.250 (0.448) (0.428) (0.387) (0.486) (0.434) $75,000–$125,000 0.500 0.345 0.298 0.252 0.198 (0.508) (0.476) (0.459) (0.435) (0.399) Over $125,000 0.088 0.071 0.091 0.053 0.099 (0.288) (0.258) (0.289) (0.225) (0.299)

Table 2 shows the Accidental Tourist cluster is well-defined through means testing on nearly all variables. For example, since most of these visitors traveled to Colorado for reasons other than leisure, and they did not plan to participate in agritourism, the variables Importance of Agritourism to Visit and Type of Agri- tourism Visited for the Accidental Tourists cluster are significantly different from every other cluster at the 1% level. As observed in figures 1 and 2, Accidental Tourists also display different preferences for agritourism activities and report that agritourism was of little importance to their visit. The low percentages represented in both of these figures probably stem from the fact that the participation in agritourism by Accidental Tourists is generally lower than any other cluster, and their information about agritourism appears to come from a hotel service or advertising they happen to see when they are in town. Thus, these travelers did not initially plan to participate in any agritourism activity on their trip. Based on data reported in table 3, means testing also illustrates that the Out- of-State Activity Seekers are significantly different from the other four clusters in

Sullins, Moxon, and McFadden Developing Marketing Strategies for Agritourism 125

100% Food/Culinary 92% Heritage 76% Educational/Experience 80% Active/Recreation 71% 73%

60% 52% 50%

39% 37% Share of Respondents of Share 40% 31% 26% 28% 24% 22% 21% 20% 12% 11%

1% 1% 2% 2% 0% Cluster 1: Out-of- Cluster 2: In-State Cluster 3: Loyal Cluster 4: Family Cluster 5: State Activity Explorers (30%) Colorado Ag Adventurers Accidental Tourists Seekers (4%) Enthusiasts (13%) (17%) (36%)

Figure 1. Participation in Colorado agritourism activities, 2005/2006

70% 65% 64% Primary Focus 58% 60% Secondary Unplanned

50%

40%

30% 26%

Share of Respondents of Share 25% 23% 18% 19% 20%

12% 12% 10% 10% 6% 2% 2% 1% 0% Cluster 1: Out-of- Cluster 2: In-State Cluster 3: Loyal Cluster 4: Family Cluster 5: State Activity Explorers (30%) Colorado Ag Adventurers Accidental Tourists Seekers (4%) Enthusiasts (13%) (17%) (36%)

Figure 2. The role of agritourism in travel to and around Colorado, 2005/2006

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100% 87% 90% Own Car Rental Plane Other 90% 82% 83% 80%

70% 68% 68%

60%

50%

40%

Share of Respondents 30% 16% 20% 16% 6% 9% 7% 10% 10% 5% 7% 4% 2% 1% 1% 0% 1% 0% Cluster 1: Out- Cluster 2: In- Cluster 3: Loyal Cluster 4: Cluster 5: of-State State Explorers Colorado Family Ag Accidental Activity Seekers (30%) Enthusiasts Adventurers Tourists (36%) (4%) (13%) (17%) Figure 3. How travelers reached their Colorado destinations in 2005/2006 travel method, as they arrive in Colorado primarily by plane and move around the state in rental cars (see figure 3 for a visual comparison of travel methods by cluster). In contrast, the Loyal Colorado Enthusiasts travel mostly by private vehicle (there is a significant difference between these two clusters at the 1% level). Activity Seekers also travel much farther than the Loyal Colorado Enthusiasts, with more than 90% of the latter traveling under 500 miles to their destinations. On the other hand, the travel method for Accidental Tourists is more evenly distributed among their own cars, rental cars, and plane travel when compared to the other clusters (since these accidental travelers come to Colorado for a variety of purposes). The Out-of-State Activity Seekers cluster is more likely to use an outfitter for planning outdoor recreation activities (primarily for taking guided hunting and fishing trips, which involve more advance planning and typically more expense) than the Family Ag Adventurers, at a 1% significance level. Members of this cluster also used travel websites more than other clusters for trip planning (50% compared to 13% for all clusters), the Colorado Tourism Office (29% compared to 9% for all clusters), and travel associations (21% compared to 10% for all clusters). In terms of lodging, the Loyal Colorado Enthusiasts were more likely to camp than those in any other clusters; this is especially notable when compared to the Out-of-State Activity Seekers and the In-State Explorers. The Family Ag Adven- turers and the In-State Explorers seemed to vary the least for any specific variable when compared to the other clusters.

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Marketing Strategy Implications

Knowing your customer is key to any service-oriented business. Examining travel behavior and agritourism interest at this level provides important insights into the market potential, targeted promotion strategies that are based on identified opportunities, and effective partnering to enhance agritourism industry growth. For example, identifying these consumer clusters shows that while 23% of all visitors engaged in some planned agritourism activities on their last trip to Colorado (primarily the Out-of-State Activity Seekers, the Loyal Colorado Enthusiasts, and the Family Ag Adventurers), another 17% of all visitors indi- cated they participated in spur-of-the-moment, unplanned activities during their last trip. Thus, there is clearly an untapped opportunity to reach these consumers through the information channels they rely on most when planning their trips in advance or deciding on activities after arriving in Colorado (e.g., making more spontaneous decisions based on road signage, brochures placed in visitors’ centers, or referrals from other businesses). For instance, in order for agritourism operators to reach a large number of Family Ag Adventurers (who rely primarily on past experience and recommendations when planning their trips), they would want to consider referral programs from past satisfied visitors or advertise their family-friendly activities on a website or through Colorado Tourism Office (CTO) promotional materials. They may also benefit from establishing links back to their website from other more family-oriented businesses such as children’s museums or parks using community networks. However, Out-of-State Activity Seekers, who also tend to travel without children, rely on a more diverse set of planning materials such as personal web searches, travel associations, park brochures, and welcome centers for their travel information. To target this group, which engages in fewer active, on-farm educational and nature-based activities, agritourism operators would want to ensure they could co-promote with culinary or heritage-based operations (including chefs who may feature local foods) which are similarly appealing to this consumer segment. Most of the more active on-farm or ranch activities require advance trip planning in terms of purchasing hunting or fishing licenses, securing access to a recreational area, and either bringing or buying/renting recreational equipment. Therefore, visitors can rarely engage in those activities spontaneously, and agritourism operators promoting these types of businesses need to create a promotional strategy based on the informational materials used by the two groups most likely to participate in more active on-farm or ranch experiences (the Out-of-State Activity Seekers and the Loyal Colorado Enthusiasts), and supply them with a longer planning horizon so they can plan to engage in those activities in Colorado. In sum, relatively small, well-targeted investments in agritourism promotion could yield large returns for entrepreneurs and communities across Colorado and create a large field of repeat visitors to businesses associated with the agritourism sector.

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Partnerships with other travel-related organizations are key to increasing awareness of Colorado’s agritourism sector. Only 9% of all those traveling to Colorado used Colorado Tourism Office materials when planning their trips. However, the consumer segments most likely to participate in agritourism relied more heavily on CTO for information: Out-of-State Activity Seekers (19%), Loyal Colorado Enthusiasts (22%), and Family Ag Adventurers (16%). Further, magazine advertising played a role in attracting one group—Out-of-State Activity Seekers (12%)—while mailings were used by less than 1% of all other groups, except 8% of Out-of-State Activity Seekers. For agritourism operators seeking to leverage scarce advertising resources, investment in a functional, informative website (with referring links on other websites offering similar or complementary activities), and promotion through state welcome centers, park brochures, and travel associations will target the greatest number of interested consumer segments and engage both the planner and the spontaneous traveler. One outgrowth of this research has been increased awareness of agritourism as a business alternative for farmers and ranchers, and as a travel option for visitors to and around Colorado. To this end, the Colorado Tourism Office developed a state committee on agritourism to focus on marketing that would help agricultural producers attract more visitors to their operations, and promote Colorado agritourism to visitors from other states. A desirable outcome of state-level recognition of agritourism as a valid niche tourism sector would also include additional resources for research on the policy and business infrastructure that will assist producers in operating sustainable businesses in the rapidly changing tourism industry.

Conclusions and Future Research

Beyond Colorado, this research offers some interesting lessons for agritourism operators and any communities wanting to grow their agritourism sectors:

■ The 20% growth rate in agritourism (pre-recession) indicates a growing interest by travelers in exploring the natural resource, heritage, and food dimensions of their own regions and of destination regions.

■ There is room for a diverse set of agritourism operations; some travelers want fairly undeveloped sites to explore the wildlife and natural settings of rural areas, while others desire scheduled events, and still others prefer high-end accommodations and rural resort experiences. This diversity is encouraging for potential operators who wish to explore whether their fledgling idea has interest to travelers, but reinforces the notion that research to help target the right types of travelers is of great value.

■ Planning defines promotion for agritourism businesses. Understanding how different types of travelers plan their trips is paramount to developing appropriate marketing programs for agritourism operations or networks. The extensive

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use of recommendations and word of mouth would suggest that new social media tools (e.g., Twitter, Facebook, Foursquare) may be cost-effective measures to connect with potential visitors. ■ Some of these findings also suggest that more research, on a national level, would be valuable for agritourism operators. For example, further analysis of consumer spending habits and consumer attitudes toward agritourism, or case studies of successful agritourism enterprises are needed to help nascent operators determine viable and sustainable business development strategies beyond marketing.

References

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Veeck, G., D. Che, and A. Veeck. (2006). “America’s changing farmscape: A study of agricultural tourism in Michigan.” The Professional Geographer 58(3), 235– 246. Wilson, J., D. Thilmany, and M. Sullins. (2006, February). “Agritourism: A potential economic driver in the rural West.” Economic Development Report No. EDR 06- 01, Colorado State University Extension, Fort Collins. Wilson, J., D. Thilmany, and P. Watson. (2006). “The role of agritourism in Western states: Place-specific and policy factors influencing recreational income for producers.” Review of Regional Studies 36, 381–399.