STUDY GUIDE SECOND EXAM

Transcription

1 STUDY GUIDE SECOND EXAM Customer lifetime value You should be able to explain the basic idea of customer lifetime value and distinguish it from other methods of valuing customers such as RFM, SOW, and PCV. You have to be able to explain the difference between a transactional and contractual setting, and the effect of the timing of payments (beginning of period, end of period) on the results of a CLV analysis. You have to be able to compute CLV for simple scenarios based on a certain discount rate and a certain rate of retention. You don t have to memorize any formulas, but you have to be able to do the calculations when given a formula. You have to understand the notion of a switching matrix when there are several customer segments in a CLV analysis. You have to be able to interpret the output from a CLV analysis using ME (similar to what we did in the Office Star illustration and the Northern Aero case). You have to know how to compute the ROI of marketing investments. Customer choice You have to be able to explain the basic idea of a customer choice model (either the binary choice model or the multinomial choice model). You also have to be able to explain the difference between the two. You don t have to memorize any formulas, but you have to understand the models conceptually. You have to be able to assess the fit of the choice model based on the confusion matrix and compute a hit rate. You also have to be able to construct a confusion matrix based on the observed choices and predicted choice probabilities or predicted choices. You have to be able to interpret the ME output under the segment tab. In particular, you have to be able to interpret the estimated coefficients, assess their significance, and interpret both the same-brand and other-brand choice elasticities. You should be able to explain how the customer choice model can be used in a market segmentation context, as in the ABB Electric case. Conjoint analysis You have to understand the difference between compositional and decompositional preference models.

2 You have to be able to explain the basic idea of conjoint analysis. You should be able to explain the different steps of a conjoint study. For example, what is the difference between a full factorial design and a fractional factorial design? You should be able to compute the part-worths and relative attribute importances in a simple example (similar to the laptop example discussed in class). You should also be able to compute the overall utility of an option based on the part-worths from a conjoint study. You have to know how to interpret the ME output from a part-worth analysis. You have to be able to explain how conjoint analysis can be used for market segmentation, in new product design, and for conducting trade-off analysis. In particular, you have to be able to show how much can be charged for introducing a new product feature when price is one of the features included in the conjoint study. You have to know how to simulate market shares based on a conjoint study. In this context, you have to understand the differences between the following choice rules: first choice, share of preference, and logit choice rule. Text analysis and search analytics You should be able to explain the process of conducting a text analysis, including how to construct a word cloud and how to do a sentiment analysis. You should be able to explain the basic idea of search analytics and what kind of information you can get from using Google Analytics. You should also be able to define the following terms: organic content vs. paid content, session, user, pageviews, bounce rate, impressions, CPM, CTR, CPC, and CPA.

3 Review of Material for Second Exam

4 Review: CLV A catalogue marketer groups its customers into two segments: premier and regular. There are 1000 customers of each type. The contribution margins of the two segments are $100 and $50, respectively. The retention rates of premier and regular customers are 60% and 50%, respectively. Each period 30% of premier customers become regular customers and 10% are lost forever. Also, 10% of regular customers become premier customers and 40% are lost forever.

5 Review: CLV

6 Review: CLV

7 Review: CLV

8 Computing the ROI of marketing investments Assume that without a certain marketing investment gross profit is $100,00, whereas with the investment it is $200,000 (where the investment of $50,000 has not been considered in the gross profit calculation): Marketing ROI = Incremental financial value Cost of marketing Cost of marketing Assume that without a certain marketing investment gross profit is $100,00, whereas with the investment it is $150,000 (where the investment of $50,000 has already been subtracted from the initial gross profit): Marketing ROI = Incremental financial value Cost of marketing

9 Review: Basic idea of the binary choice model What determines choice when there are two choice options? Assume we have two possible influences on the choice of a brand, (perceived) quality and price. The model is P Y = 1 = exp (α + β 1 Q + β 2 P) We can rewrite this equation as follows: log P Y = 1 1 P Y = 1 = α + β 1 Q + β 2 P

10 Assessing model fit in choice models Confusion Matrix on Estimation Sample Comparison of observed choices and predicted choices (based on MNL analysis). High values in the diagonal of the confusion matrix (in bold), compared to the non-diagonal values, indicate high convergence between observations and predictions. Analysis has been performed on the estimation dataset, and measures the goodness-of-fit of the model. Observed / Predicted Choice ABB GE Westinghouse Edison ABB GE Westinghouse Edison

11 Interpreting choice models Coefficient Estimates [segment 1] Coefficient estimates of the Choice model. Coefficients in bold are statistically significant. Variables / Coefficient estimates Coefficient estimates Standard deviation t-statistic Price Energy Loss Maintenance Warranty Spare Parts Ease of Install Prob Solver Quality Const Const Const Baseline n/a n/a

12 Interpreting choice models (cont d) Elasticities [segment 1] Elasticities of coefficients. Elasticities of Price ABB GE Westinghouse Edison ABB GE Westinghouse Edison Elasticities of Energy Loss ABB GE Westinghouse Edison ABB GE Westinghouse Edison

13 Estimated probabilities Estimation Sample Details Choice probabilities, predicted and observed choices, segment membership probabilities and predicted segment for the sample used to estimate the model. Respondents / Choice probabilities ABB probability GE probability Westing house probability Edison probability Predicted ABB Predicted GE Predicted Westinghouse Predicted Edison Observed ABB Observed GE Observed Westinghouse Observed Edison Customer Customer Customer Customer Customer

14 Conjoint analysis A conjoint study was conducted for LCD TV s, using three brands (LG, Samsung, and Sony), three screen sizes (46, 54, and 63 in.) and three price levels ($2,300; $2,800; and $3,600). The utility differences between the lowest and highest levels of each attribute were 3 for brand name, 2 for screen size, and 5 for price. Based on these findings, what are the relative importances of brand name, screen size, and price?

15 Conjoint analysis (cont d) Based on the conjoint study, LG management knows that a price increase from $2,300 to $2,800 leads to a decrease in utility of 3. If utility goes up by 1 when the screen size is increased from 46 to 54 inches, how much can LG charge for the TV set with the larger screen?

16 Consumer A Consumer B Attribute level Mean for level across all profiles Mean as deviation from zero Range on attribute Percentage importance Mean for level across all profiles Mean as deviation from zero Range on attribute Percentage importance Apple % % Dell HD % % 320HD RAM % % 4RAM in % % 15.4in $ % % $ $ =11.74

17 Part-worths Exceeds Exceeds 9% 5% Meets specific ations Short by 5% 6 months 9 months 12 months Installed, 15 months 600K 700K 800K 900K with 2-year warranty Installed, with 1-year warranty Installed, with service contract Chev TXU AEP Gen Mills Krispy Kreme Ave FOB, with service contract

18 Market Share Simulations Predicted market shares Market share predictions for different scenarios, using the First-Choice Rule. Scenario / Product profiles Wastewatch Thermatrix Advanced Air New Product Profile Predicted market shares 45% 4% 51%...with Servair DX 38% 2% 42%...with Premier DX 43% 1% 41%...with Base model 44% 4% 43% n/a 19% 14% 9%