Julian, JasonHeinemann, Matt2016-10-282016-10-282016-08Heinemann, M. (2016). <i>Leveraging data mining and market segmentation to gain conservation opportunity intelligence</i> (Unpublished thesis). Texas State University, San Marcos, Texas.https://hdl.handle.net/10877/6316Rural landowners are an important audience for conservation messages about natural resource management. On-going collaborations between scientists, academics, and practitioners are producing actionable intelligence related to reaching, engaging and influencing rural landowner messaging and program marketing. One goal of such collaborations is to improve conservation program enrollment. Recently, market research and market segmentation approaches have generated a better understanding of the drivers for natural resource management program participation. This pilot study demonstrates a proof of concept using analytic processes which can be effective for market segmentation. A cluster analysis, using a representative two county sample and an empirically based set of variables, was instrumental in identifying seven landowner types that explain interest or willingness to be program participants. Using these clusters, I generated maps of landowners who represent opportunity for engagement. Techniques for understanding the human dimensions of conservation in a priority resource area and the groups of landowners who may be receptive to program messages are explored and explained. Based on the success of this clustering method, other landowner engagement campaigns could consider following this approach to increase their predictive abilities and improve return on investment in direct response marketing campaigns.Text44 pages1 file (.pdf)enConservationHuman GeographyCluster AnalysisOpportunity MappingPrime ProspectConservation PlanningHuman Dimensions of Natural Resource ManagementNatural resources--Texas--ManagementData miningHuman geographyThesis