You work for the strategy department at Bank of America. They have developed a new retirement...
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You work for the strategy department at Bank of America. They have developed a new retirement investment product and are trying to figure out the most cost effective way to encourage customers to sign up for the product. Before launching the campaign nation-wide, they run a relatively small test to compare the effectiveness of different marketing strategies: direct calls, direct mail, or emails. After the test is complete, you run a logistic regression model with the following data: enroll: equals 1 if the customer signed up for the retirement product, 0 otherwise call: equals 1 if the customer was called personally and explained the benefits of signing up, 0 otherwise directmail: equals 1 if the customer received a direct mail promotion, 0 otherwise email: equals 1 if the customer received an email about the promotion. 0 otherwise balance: in thousands of dollars, the current size of their equity portfolio age: age of the customer The logistic regression reults are here: ## ## Call: ## glm (formula enroll call + directmail +email+ balance + ## age email, family = binomial) ## ## Deviance Residuals: ## Min 1Q Median 3Q Max 2.7638 ## -1.3775 -0.6405 -0.4304 -0.2446 ## ## Coefficients: ## ## call Estimate Std. Error z value Pr(>1z1) ## (Intercept) -2.7271577 0.3447254 -7.911 2.55e-15 *** 1.1334537 0.1059625 10.697 <2e-16 *** 0.6175141 0.1036299 5.959 2.54e-09 *** -0.1047679 0.3709112 -0.282 ## directmail ## email ## balance ## age ## email: age ---## 0.7776 0.6565 -0.0002599 0.0005842 -0.445 -0.0131181 0.0056991 -2.302 0.0213 * 0.0314767 0.0066908 4.704 2.55e-06 *** ## Signif. codes: 0*** 0.001 0.01 0.05 0.1 1 ## ## (Dispersion parameter for binomial family taken to be 1) ## ## Null deviance: 2876.3 on 2999 degrees of freedom ## Residual deviance: 2453.4 on 2993 ## AIC: 2467.4 ## degrees of freedom ## Number of Fisher Scoring iterations: 5 7) What is the probability that a 45 year old customer with a $60,000 equity account enrolls in the program If they receive a call (and only a call)? 8) What is the marginal effect of a phone call for a 32 year old customer with $80,000 in equity who has already received an email (but no call and no direct mail)? Note: let's use the "technically correct" definition of the marginal effect, which is the slope of a tangential line evaluated at a given point on the probability curve. 9) For a 55 year old with $30,000 in equity, what is the marginal effect on the probability of response of direct mail? Assume they have not been called and did not receive an email or any direct mail yet. Again, let's use the "technically correct" definition of the marginal effect, which is the slope of a tangential line evaluated at a given point on the probability curve. 10) For a 60 year with a $25,000 balance and no marketing contact, how much does the log-odds change when an email is sent? You work for the strategy department at Bank of America. They have developed a new retirement investment product and are trying to figure out the most cost effective way to encourage customers to sign up for the product. Before launching the campaign nation-wide, they run a relatively small test to compare the effectiveness of different marketing strategies: direct calls, direct mail, or emails. After the test is complete, you run a logistic regression model with the following data: enroll: equals 1 if the customer signed up for the retirement product, 0 otherwise call: equals 1 if the customer was called personally and explained the benefits of signing up, 0 otherwise directmail: equals 1 if the customer received a direct mail promotion, 0 otherwise email: equals 1 if the customer received an email about the promotion. 0 otherwise balance: in thousands of dollars, the current size of their equity portfolio age: age of the customer The logistic regression reults are here: ## ## Call: ## glm (formula enroll call + directmail +email+ balance + ## age email, family = binomial) ## ## Deviance Residuals: ## Min 1Q Median 3Q Max 2.7638 ## -1.3775 -0.6405 -0.4304 -0.2446 ## ## Coefficients: ## ## call Estimate Std. Error z value Pr(>1z1) ## (Intercept) -2.7271577 0.3447254 -7.911 2.55e-15 *** 1.1334537 0.1059625 10.697 <2e-16 *** 0.6175141 0.1036299 5.959 2.54e-09 *** -0.1047679 0.3709112 -0.282 ## directmail ## email ## balance ## age ## email: age ---## 0.7776 0.6565 -0.0002599 0.0005842 -0.445 -0.0131181 0.0056991 -2.302 0.0213 * 0.0314767 0.0066908 4.704 2.55e-06 *** ## Signif. codes: 0*** 0.001 0.01 0.05 0.1 1 ## ## (Dispersion parameter for binomial family taken to be 1) ## ## Null deviance: 2876.3 on 2999 degrees of freedom ## Residual deviance: 2453.4 on 2993 ## AIC: 2467.4 ## degrees of freedom ## Number of Fisher Scoring iterations: 5 7) What is the probability that a 45 year old customer with a $60,000 equity account enrolls in the program If they receive a call (and only a call)? 8) What is the marginal effect of a phone call for a 32 year old customer with $80,000 in equity who has already received an email (but no call and no direct mail)? Note: let's use the "technically correct" definition of the marginal effect, which is the slope of a tangential line evaluated at a given point on the probability curve. 9) For a 55 year old with $30,000 in equity, what is the marginal effect on the probability of response of direct mail? Assume they have not been called and did not receive an email or any direct mail yet. Again, let's use the "technically correct" definition of the marginal effect, which is the slope of a tangential line evaluated at a given point on the probability curve. 10) For a 60 year with a $25,000 balance and no marketing contact, how much does the log-odds change when an email is sent?
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Related Book For
Computer Architecture A Quantitative Approach
ISBN: 978-0123704900
4th edition
Authors: John L. Hennessy, David A. Patterson
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