Cookbook Modeling Data for Marketing 11 pptx

Cookbook Modeling Data for Marketing_3 pptx

Cookbook Modeling Data for Marketing_3 pptx

... the robustness of the model or its ability to perform on other prospect data. The code is the same as for the model data decile analysis except for the (where=( splitwgt = .)) option. This accesses ... different names for the predictors for each model. proc sort data= acqmod.out_rsp2 out=acqmod.validrsp (where=( splitwgt = .) rename=(pred=predrsp)); by pros_id; run; proc...

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Cookbook Modeling Data for Marketing_8 pptx

Cookbook Modeling Data for Marketing_8 pptx

... variable prefixes and suffixes. Recall that the data set, ch11.scored, is an output data set from PROC LOGISITIC, shown previously. data ch11.scored; set ch11.scored(keep= pred attrite splitwgt records ... build a churn model. Bon appetit! Page 266 Figure 11. 4 Logistic output for average balance on FRUTs. data ch11.rowan; set ch11.rowan; city = (popdens = 'C&ap...

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Cookbook Modeling Data for Marketing_11 pptx

Cookbook Modeling Data for Marketing_11 pptx

... models ASCII files, 52 access log and, 307 codes for, 52, 53 fixed format, 52–53 variable format, 53 Attitudinal data, 26 – 27 Attrition, 4, 10 11. See also Modeling churn case example of, 42 credit ... complete understanding of the recipes in Data Mining Cookbook. The spreadsheets contain all formulas used to create the tables and charts in Data Mining Cookbook. Page 3...

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Cookbook Modeling Data for Marketing_1 doc

Cookbook Modeling Data for Marketing_1 doc

... model — activate|response. Page 60 Cleaning the Data I now have the complete data set for modeling. The next step is to examine the data for errors, outliers, and missing values. This is ... important step in the data preparation process. Luckily there are some effective techniques for managing this process. First, I describe some techniques for cleaning and repairing...

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Cookbook Modeling Data for Marketing_4 potx

Cookbook Modeling Data for Marketing_4 potx

... sent out for scoring by the data vendor or service bureau. In either case, you need to ensure that the data being scored is similar to the data on which the model was developed by performing ... variable transformations for inferred age (infd_ag). This step is repeated for all continuous variables in the model. PROC UNIVARIATE creates the decile value (age10) needed for the bi...

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Cookbook Modeling Data for Marketing_5 docx

Cookbook Modeling Data for Marketing_5 docx

... Obtain data from the various sources you've identified for the sample you've selected. The analytical database may contain transactional data, survey data, and geo-demographic data. Data ... appended data, make sure that the data is clean. This is more difficult because you may not be as familiar with it. Ask for ranges of values for each field and for the mean s...

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Cookbook Modeling Data for Marketing_9 doc

Cookbook Modeling Data for Marketing_9 doc

... experience. Preparing Web Data Preparing Web data for analysis also presents unique challenges for the data miner or modeler. Devyani details some of the issues and methods for getting the Web data into a form that ... not - so - familiar tools for Web mining and modeling: While most techniques used in Web data mining originate from the fields of data mining, database...

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Cookbook Modeling Data for Marketing_10 pdf

Cookbook Modeling Data for Marketing_10 pdf

... are enabling companies to gather information, perform data mining and modeling, and design offers in real time, thus reaching the goal of true one-to-one marketing. Tom Kehler, president and ... transactional data, and demographic information and therefore can greatly contribute to the development of highly effective marketing strategies. Market basket analysis is a clustering techn...

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Cookbook Modeling Data for Marketing_12 pot

Cookbook Modeling Data for Marketing_12 pot

... 103, 105, 109 110 comparing methods, 121–123 one model method, 108 114 , 115 119 preliminary evaluation, 117 – 119 score selection method, 103, 105, 110 , 111 , 112 splitting the data, 103–104, ... 26–27 validation, 152–155 Data errors and outliers, 60 , 62 – 64, 69 Data marts, 31 Data mining software classification trees, 98 Data preparation for modeling. See Prepar...

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John wiley sons data mining techniques for marketing sales_20 pptx

John wiley sons data mining techniques for marketing sales_20 pptx

... binary outcome, 119 customer longevity, predicting, 119 –120 EBCF (existing base churn forecast), 469 expected, 118 forced attrition, 118 importance of, 117 118 involuntary, 118 119 , 521 recognizing, ... exposure to, 113 114 crossover, generic algorithms, 430 cross-selling opportunities affinity grouping, 11 customer relationships, 467 marketing campaigns, 111 , 115...

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