Step-by-step guide to HW3b 1. The goal is to determine (a) the effectiveness of marketing mix...
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Step-by-step guide to HW3b 1. The goal is to determine (a) the effectiveness of marketing mix activities and (b) the optimal budget and its allocation. 2. To this end, we use the data posted on the canvas. Download multi_media_data.xlsx file to your desktop. The data set presents 104 weeks of observations on the five marketing mix activities, which led to "prospects" (which refers to prospective customers). We denote the marketing mix activities and prospects as follows: X1 National Cable X2 National Network (Syndicated Programs) X3 = National Network (Other Programs) X4 = Local TV X5 = Local Radio Y = Prospects. 3. We first incorporate the concept of diminishing returns. Diminishing returns means the incremental effect of an activity decreases as you spend more on it. For example, the enjoyment from an additional slice of pizza decreases as one eats more slices. To capture diminishing returns in a model, we use a square root function. Specifically, we create new variables Z1 = X1, Z2 = X2, and so on for all the five X-variables. 4. Then, to estimate the effectiveness, we use the following model: YtYt-1+B1Z1t + B2Z2t + 3Z3t+B4Z4t+B5Z5t + intercept + Et where t denotes the week, a measures the carryover effects from the past outcomes (Lagged Y), and B captures the effectiveness of an activity i (i = 1,2,..., 5). 5. Next, we apply the above-mentioned transformations. a. Create the lagged Y variable. In SPSS, click Transform Compute Variable assign name in left-hand side box and write "Lag(Prospects)" in the right hand side formula box. Click OK. A new variable will be added to the data set with a missing value in the first cell followed by the same entries in the column for Prospects; verify that. b. Transform X variables to create new Z variables. Click Transform Compute Variable Z1 = sqrt(X1) and so on for all 5 x-variables. 6. Now, we can apply stepwise regression in SPSS. Select Analyze Regression Linear. Enter Prospects as the dependent variable. Select Stepwise method (instead of Enter) for variable selection. Click OK. 7. Attribution Results. Based on the unstandardized coefficients and t-values in the output table, state what you learn about the effectiveness of various marketing activities. Step-by-step guide to HW3b 1. The goal is to determine (a) the effectiveness of marketing mix activities and (b) the optimal budget and its allocation. 2. To this end, we use the data posted on the canvas. Download multi_media_data.xlsx file to your desktop. The data set presents 104 weeks of observations on the five marketing mix activities, which led to "prospects" (which refers to prospective customers). We denote the marketing mix activities and prospects as follows: X1 National Cable X2 National Network (Syndicated Programs) X3 = National Network (Other Programs) X4 = Local TV X5 = Local Radio Y = Prospects. 3. We first incorporate the concept of diminishing returns. Diminishing returns means the incremental effect of an activity decreases as you spend more on it. For example, the enjoyment from an additional slice of pizza decreases as one eats more slices. To capture diminishing returns in a model, we use a square root function. Specifically, we create new variables Z1 = X1, Z2 = X2, and so on for all the five X-variables. 4. Then, to estimate the effectiveness, we use the following model: YtYt-1+B1Z1t + B2Z2t + 3Z3t+B4Z4t+B5Z5t + intercept + Et where t denotes the week, a measures the carryover effects from the past outcomes (Lagged Y), and B captures the effectiveness of an activity i (i = 1,2,..., 5). 5. Next, we apply the above-mentioned transformations. a. Create the lagged Y variable. In SPSS, click Transform Compute Variable assign name in left-hand side box and write "Lag(Prospects)" in the right hand side formula box. Click OK. A new variable will be added to the data set with a missing value in the first cell followed by the same entries in the column for Prospects; verify that. b. Transform X variables to create new Z variables. Click Transform Compute Variable Z1 = sqrt(X1) and so on for all 5 x-variables. 6. Now, we can apply stepwise regression in SPSS. Select Analyze Regression Linear. Enter Prospects as the dependent variable. Select Stepwise method (instead of Enter) for variable selection. Click OK. 7. Attribution Results. Based on the unstandardized coefficients and t-values in the output table, state what you learn about the effectiveness of various marketing activities.
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Income Tax Fundamentals 2013
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31st Edition
Authors: Gerald E. Whittenburg, Martha Altus Buller, Steven L Gill
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