- Part 1. Introduction to MM4XL
- Part 2. MM4XL Tools
- 1. Strategic Tools
- BCG Matrix
- Brand Mapping
- Brand Switch
- Decision Tree
- Forecast Manager
- McKinsey Matrix
- Profile Manager
- Quality Manager
- Risk Analyst
- Risk Analyst Expert in a Few Minutes
- Introduction to Decision Analysis
- Introducing Risk Analyst with an example
- 1. How to run Risk Analyst
- 2. Simulation Never heard of it
- 3. Examples
- 4. Functions
- 1. Property Functions
- 2. Utility Functions
- 3. Distribution Functions
- mmBETA (Scale, Shape)
- mmBETAGEN (Scale, Shape, [Optional: Lower], [Optional: Upper])
- mmBINOMIAL (Trials, Successes)
- mmCHI2 (Degrees)
- mmDISCRETE (InputRange, Probabilities)
- mmERF (Mean)
- mmERLANG (Scale, Shape)
- mmEXPON (Mean)
- mmEXTVAL (ModalValue, StDeviation)
- mmGAMMA (Scale, Shape)
- mmGAUSSINV (Mean, Scale)
- mmGEO (Trials)
- mmHYPERGEO (Sample, Defects, BatchSize)
- mmINTUNI (Lower, Upper)
- mmLOGISTIC (Mean, StDeviation)
- mmLOGNORMAL (Mean, StDeviation)
- mmNEGBIN (Failures, Successes)
- mmNORMAL (Mean, StDeviation)
- mmPARETO (Location, ModalValue)
- mmPARETO2 (Location, ModalValue)
- mmPERT (Lower, ModalValue, Upper)
- mmPOISSON (Mean)
- mmRANDBETWEEN (Lower, Upper)
- mmRAYLEIGH (ModalValue)
- mmSTUDENT (Degrees)
- mmTRI (Lower, ModalValue, Upper)
- mmUNIFORM (Lower, Upper)
- mmWEIBULL (Life, Shape)
- Probability functions
- Technicalities
- Sources
- 2. Analytical Tools
- Business Formulas
- mmBASS, Bass Diffusion Model
- mmBEI, Brand Equity Index
- mmBEP, Break-Even Point
- mmBEPR, Break-Even Point with Fixed Rate of Return
- mmBUYRATE, Purchase Rate Model
- mmCAGR, Compound Annual Growth
- mmCHIp, Chi Squared Test
- mmCODING, Coding of variables
- 1. Customer Satisfaction
- 2. Database Functions
- mmDHMS, Number to Time
- mmEI, Evolution Index
- mmEXPECT, Expected values
- 3. Forecast Errors
- mmGROWTH
- mmGROWTHBACK
- mmGRP, Gross Rating Points
- mmHERF, Herfindahl Index
- mmINTERPOLE, Linear Interpolation
- mmLEARN, Learning Curve
- mmMSAR, Market Share to Advertising Ratio
- 4. Opportunity Index
- 5. Performance Ranking
- 6. Project Management
- mmPREMIUM, Price Premium
- mmPRESS, Product Performance Index
- 7. Price Indexes
- 8. Queuing Theory
- mmRANGE
- mmREBUY, Repeat Purchase Rate
- mmREBUYS, Estimated Number of Re-Purchases
- mmRELATIVE
- mmSAMPLE, Sample Size
- mmSAMPLEMIN, Minimum Sample for Significant Values
- mmSEASON, Seasonality Indexes
- mmSHARE
- mmSIGNIF, Significance Test
- mmVARc, Coefficient of Variation
- Cluster Analysis
- CrossTab
- Descriptive Analyst
- Gravitation Analysis
- Proportion Analyst
- Sample Manager
- Segmentation Tree
- Variation Analyst
- 3. Charts and Maps
- mytest
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- Part 1. Introduction to MM4XL
- Part 2. MM4XL Tools
- 1. Strategic Tools
- BCG Matrix
- Brand Mapping
- Brand Switch
- Decision Tree
- Forecast Manager
- McKinsey Matrix
- Profile Manager
- Quality Manager
- Risk Analyst
- 1. How to run Risk Analyst
- 2. Simulation Never heard of it
- 3. Examples
- 4. Functions
- 1. Property Functions
- 2. Utility Functions
- 3. Distribution Functions
- mmBETA (Scale, Shape)
- mmBETAGEN (Scale, Shape, [Optional: Lower], [Optional: Upper])
- mmBINOMIAL (Trials, Successes)
- mmCHI2 (Degrees)
- mmDISCRETE (InputRange, Probabilities)
- mmERF (Mean)
- mmERLANG (Scale, Shape)
- mmEXPON (Mean)
- mmEXTVAL (ModalValue, StDeviation)
- mmGAMMA (Scale, Shape)
- mmGAUSSINV (Mean, Scale)
- mmGEO (Trials)
- mmHYPERGEO (Sample, Defects, BatchSize)
- mmINTUNI (Lower, Upper)
- mmLOGISTIC (Mean, StDeviation)
- mmLOGNORMAL (Mean, StDeviation)
- mmNEGBIN (Failures, Successes)
- mmNORMAL (Mean, StDeviation)
- mmPARETO (Location, ModalValue)
- mmPARETO2 (Location, ModalValue)
- mmPERT (Lower, ModalValue, Upper)
- mmPOISSON (Mean)
- mmRANDBETWEEN (Lower, Upper)
- mmRAYLEIGH (ModalValue)
- mmSTUDENT (Degrees)
- mmTRI (Lower, ModalValue, Upper)
- mmUNIFORM (Lower, Upper)
- mmWEIBULL (Life, Shape)
- Probability functions
- Risk Analyst Expert in a Few Minutes
- Introduction to Decision Analysis
- Introducing Risk Analyst with an example
- Technicalities
- Sources
- 2. Analytical Tools
- Business Formulas
- 1. Customer Satisfaction
- 2. Database Functions
- 3. Forecast Errors
- 4. Opportunity Index
- 5. Performance Ranking
- 6. Project Management
- 7. Price Indexes
- 8. Queuing Theory
- mmBASS, Bass Diffusion Model
- mmBEI, Brand Equity Index
- mmBEP, Break-Even Point
- mmBEPR, Break-Even Point with Fixed Rate of Return
- mmBUYRATE, Purchase Rate Model
- mmCAGR, Compound Annual Growth
- mmCHIp, Chi Squared Test
- mmCODING, Coding of variables
- mmDHMS, Number to Time
- mmEI, Evolution Index
- mmEXPECT, Expected values
- mmGROWTH
- mmGROWTHBACK
- mmGRP, Gross Rating Points
- mmHERF, Herfindahl Index
- mmINTERPOLE, Linear Interpolation
- mmLEARN, Learning Curve
- mmMSAR, Market Share to Advertising Ratio
- mmPREMIUM, Price Premium
- mmPRESS, Product Performance Index
- mmRANGE
- mmREBUY, Repeat Purchase Rate
- mmREBUYS, Estimated Number of Re-Purchases
- mmRELATIVE
- mmSAMPLE, Sample Size
- mmSAMPLEMIN, Minimum Sample for Significant Values
- mmSEASON, Seasonality Indexes
- mmSHARE
- mmSIGNIF, Significance Test
- mmVARc, Coefficient of Variation
- Cluster Analysis
- CrossTab
- Descriptive Analyst
- Gravitation Analysis
- Proportion Analyst
- Sample Manager
- Segmentation Tree
- Variation Analyst
- 3. Charts and Maps
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Part 2. MM4XL Tools > 1. Strategic Tools > Profile Manager > 2. Technicalities > The Model
Profile Manager The Model Professor Kotler suggest that marketing managers evaluate models drawn with the same modellingtechnique applied by Profile Manager when they want to make explicit the individual effect variables exert on brand switching behaviour. Professor Kotler assumes the characteristics of different brands are summarized, at time t, in a competitive marketing mix matrix similar to the one we use in the section Anatomy of a Report. The measures of relative attractiveness of each brand on one dimension are shown in the rows. The higher one row value the better that brand performs on that variable. If we were working with price, the highest relative attractiveness would be attributed to the lowest price. Kotler calls brand probability purchase vector the market shares estimated with the model, which are obtained by multiplying the competitive marketing mix matrix and the marketing response vector. The resulting vector will add up to one and its outcome is influenced by (1) the relative attractiveness of the attributes and (2) the weight customers attach to each brand characteristic. Profile Manager uses the formula MMULT() for multiplying matrixes in Excel. Among limitations, this model is linear and does not allow modelling interaction effects among variables. One of the benefits Kotler mentions is that it helps in finding better ways to scale relative awareness and attitudes toward brand differences. The sensitivity analysis is run altering iteratively the content of the input data. Each input value of the matrix is set first to zero and then to 1, while other row values are rescaled accordingly. The shares obtained with the fictitious parameters are displayed in the columns Min and Max of the table below, and the column Max Min of the matrix shows the width of the impact each variable exerts on the estimated share. |