Summarize the results of your analysis for all three models

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Reference no: EM131395048

Case - Bookbinders Book Club

1. Summarize the results of your analysis for all three models. Develop your models using the case data files and then assess them on the holdout data sample.

Linear Regression model for 1600 sample

Figure 1: Coefficients^a
Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.
Model		B	Std. Error	Beta	t	Sig.
1	(Constant)	.364	.031		11.848	.000
	Gender	-.131	.020	-.143	-6.536	.000
	Amount purchased	.000	.000	.060	2.464	.014
	Frequency	-.009	.002	-.165	-4.170	.000
	Last purchase	.097	.014	.678	7.156	.000
	First purchase	-.002	.002	-.075	-1.103	.270
	P_Child	-.126	.016	-.309	-7.698	.000
	P_Youth	-.096	.020	-.140	-4.792	.000
	P_Cook	-.141	.017	-.340	-8.520	.000
	P_DIY	-.135	.020	-.212	-6.834	.000
	P_Art	.118	.019	.200	6.061	.000
a. Dependent Variable: Choice (0/1)

Linear Regression for holdout sample

Figure 2: Coefficients^a
Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.
Model		B	Std. Error	Beta	t	Sig.
1	(Constant)	.183	.018		9.933	.000
	Gender	-.070	.012	-.114	-5.825	.000
	Amount purchased	8.682E-5	.000	.029	1.346	.179
	Frequency	-.007	.001	-.188	-5.037	.000
	Last purchase	.038	.009	.382	4.025	.000
	First purchase	.001	.001	.048	.793	.428
	P_Child	-.059	.011	-.211	-5.624	.000
	P_Youth	-.043	.013	-.096	-3.457	.001
	P_Cook	-.061	.010	-.229	-5.918	.000
	P_DIY	-.077	.012	-.192	-6.554	.000
	P_Art	.079	.013	.171	6.087	.000

Binary logit model for 1600 sample

Figure 3: Model Summary
Step	-2 Log likelihood				Cox & Snell R Square					Nagelkerke R Square
1	1392.159^a				.225					.333
a. Estimation terminated at iteration number 6 because parameter estimates changed by less than .001?
Figure 4: HosmerandLemeshowtest
Step	Chi-square			df				Sig.
1	3.061			8				.930
Figure 5: Variables in the Equation
							B				S.E.		Wald		df	Sig.	Exp(B)
Step 1^a			Gender				-.863				.137		39.443		1	.000	.422
			Amountpurchased				.002				.001		5.542		1	.019	1.002
			Frequency				-.076				.017		20.709		1	.000	.927
			Lastpurchase				.612				.094		42.526		1	.000	1.844
			Firstpurchase				-.015				.013		1.333		1	.248	.985
			P_Child				-.811				.117		48.319		1	.000	.444
			P_Youth				-.637				.143		19.741		1	.000	.529
			P_Cook				-.923				.119		59.677		1	.000	.397
			P_DIY				-.906				.144		39.738		1	.000	.404
			P_Art				.686				.127		29.178		1	.000	1.986
			Constant				-.352				.214		2.689		1	.101	.704
a. Variable(s) entered on step 1:Gender, Amountpurchase, Frequency, Lastpurchase, Firstpurchase, P_Child, P_Youth, P_Cook, P_DIY, P_Art
Figure 6: Classification Table^a
		Observed							Predicted
									Choice (0/1)					Percentage Correct
									0			1
Step 1		Choice (0/1)				0			1120			80		93.3
						1			240			160		40.0
		Overall percentage												80.0
a. The cut value is.500

Binary logit model for holdout sample

Figure 7: Model Summary
Step	-2 Log likelihood				Cox & Snell R Square					Nagelkerke R Square
1	1111.384^a				.109					.243
a. Estimation terminated at iteration number 6 because parameter estimates changed by less than .001?
Figure 8: HosmerandLemeshowtest
Step	Chi-square			df				Sig.
1	7.851			8				.448
Figure 9: Variables in the Equation
							B				S.E.		Wald		df	Sig	Exp(B)
Step 1^a			Gender				-.942				.164		33.164		1	.000	.390
			Amountpurchased				.001				.001		2.205		1	.138	1.001
			Frequency				-.112				.020		32.302		1	.000	.894
			Lastpurchase				.412				.115		12.759		1	.000	1.510
			Firstpurchase				.007				.014		.216		1	.642	1.007
			P_Child				-.679				.140		23.519		1	.000	.507
			P_Youth				-.479				.173		7.639		1	.006	.619
			P_Cook				-.724				.142		25.833		1	.000	.485
			P_DIY				-.953				.167		32.401		1	.000	.386
			P_Art				.804				.150		28.762		1	.000	2.234
			Constant				-1.150				.248		21.443		1	.000	.317
a. Variable(s) entered on step 1:Gender, Amountpurchase, Frequency, Lastpurchase, Firstpurchase, P_Child, P_Youth, P_Cook, P_DIY, P_Art
Figure 10: Classification Table^a
		Observed							Predicted
									Choice (0/1)					Percentage Correct
									0			1
Step 1		Choice (0/1)				0			2081			15		99.3
						1			177			27		13.2
		Overall Percentage												91.7
a. The cut value is.500

2. Interpret the results of these models. In particular, highlight which factors most influenced the customers' decision to buy or not to buy the book.

3. Bookbinders is considering a similar mail campaign in the Midwest where it has data for 50,000 customers. Such mailings typically promote several books. The allocated cost of the mailing is $0.65/addressee (including postage) for the art book, and the book costs Bookbinders $15 to purchase and mail. The company allocates overhead to each book at 45 percent of cost. The selling price of the book is $31.95. Based on the model, which customers should Bookbinders target? How much more profit would you expect the company to generate using these models as compared to sending the mail offer to the entire list?

4. Based on the insights you gained from this modeling exercise, summarize the advantages and limitations of each of the modeling approaches. Look at both similar and dissimilar results.

Attachment:- Case Assignment.rar

Reference no: EM131395048

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len1395048

2/15/2017 11:40:11 PM

Case Bookbinders Book Club answers By Gary L. Lilien & Arvind Rangaswamy, just need to answer question 1-4, and only using an ordinary linear regression model, and a binary logit model, no need RFM and make sure only question 1-4 and using an ordinary linear regression model, and a binary logit model no need RFM!

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