Apply appropriate data-mining techniques to analyze the data
Lawn Care database provides data related to predicting the level of business (Usage Level) obtained Show more Lawn Care database provides data related to predicting the level of business (Usage Level) obtained from a third-party survey of purchasing managers of customers Performance Lawn Care. 8 The seven PLE attributes rated by each respondent are Delivery speedthe amount of time it takes to deliver the product once an order is confirmed Price levelthe perceived level of price charged by PLE Price flexibilitythe perceived willingness of PLE representatives to negotiate price on all types of purchases Manufacturing imagethe overall image of the manufacturer Overall servicethe overall level of service necessary for maintaining a satisfactory relationship between PLE and the purchaser Sales force imagethe overall image of the PLEs sales force Product qualityperceived level of quality Responses to these seven variables were obtained using a graphic rating scale where a 10-centimeter line was drawn between endpoints labeled poor and excellent. Respondents indicated their perceptions using a mark on the line which was measured from the left endpoint. The result was a scale from 0 to 10 rounded to one decimal place. Two measures were obtained that reflected the outcomes of the respondents purchase relationships with PLE: Usage levelhow much of the firms total product is purchased from PLE measured on a 100-point scale ranging from 0% to 100% Satisfaction levelhow satisfied the purchaser is with past purchases from PLE measured on the same graphic rating scale as perceptions 1 through 7 The data also include four characteristics of the responding firms: Size of firmsize relative to others in this market (0 = small; 1 = large) Purchasing structurethe purchasing method used in a particular company (1 = centralized procurement 0 = decentralized procurement) Industrythe industry classification of the purchaser [1 = retail (resale such as Home Depot) 0 = private (nonresale such as a landscaper)] Buying typea variable that has three categories (1 = new purchase 2 = modified rebuy 3 = straight rebuy) Elizabeth Burke would like to understand what she learned from these data. Apply appropriate data-mining techniques to analyze the data. For example can PLE segment customers into groups with similar perceptions about the company? Can cause-and-effect models provide insight about the drivers of satisfaction and usage level ( A business analytics question) Show less
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