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Marketing analytics : data-driven techniques with Microsoft Excel /
Helping tech-savvy marketers and data analysts solve real-world business problems with Excel Using data-driven business analytics to understand customers and improve results is a great idea in theory, but in today's busy offices, marketers and analysts need simple, low-cost ways to process and...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Hoboken :
John Wiley & Sons,
2014.
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Cover; Title Page; Copyright; Contents; Introduction; Part I Using Excel to Summarize Marketing Data; Chapter 1 Slicing and Dicing Marketing Data with PivotTables; Analyzing Sales at True Colors Hardware; Analyzing Sales at La Petit Bakery; Analyzing How Demographics Affect Sales; Pulling Data from a PivotTable with the GETPIVOTDATA Function; Summary; Exercises; Chapter 2 Using Excel Charts to Summarize Marketing Data; Combination Charts; Using a PivotChart to Summarize Market Research Surveys; Ensuring Charts Update Automatically When New Data is Added; Making Chart Labels Dynamic.
- Summarizing Monthly Sales-Force RankingsUsing Check Boxes to Control Data in a Chart; Using Sparklines to Summarize Multiple Data Series; Using GETPIVOTDATA to Create the End-of-Week Sales Report; Summary; Exercises; Chapter 3 Using Excel Functions to Summarize Marketing Data; Summarizing Data with a Histogram; Using Statistical Functions to Summarize Marketing Data; Summary; Exercises; Part II Pricing; Chapter 4 Estimating Demand Curves and Using Solver to Optimize Price; Estimating Linear and Power Demand Curves; Using the Excel Solver to Optimize Price.
- Pricing Using Subjectively Estimated Demand CurvesUsing SolverTable to Price Multiple Products; Summary; Exercises; Chapter 5 Price Bundling; Why Bundle?; Using Evolutionary Solver to Find Optimal Bundle Prices; Summary; Exercises; Chapter 6 Nonlinear Pricing; Demand Curves and Willingness to Pay; Profit Maximizing with Nonlinear Pricing Strategies; Summary; Exercises; Chapter 7 Price Skimming and Sales; Dropping Prices Over Time; Why Have Sales?; Summary; Exercises; Chapter 8 Revenue Management; Estimating Demand for the Bates Motel and Segmenting Customers; Handling Uncertainty.
- Markdown PricingSummary; Exercises; Part III Forecasting; Chapter 9 Simple Linear Regression and Correlation; Simple Linear Regression; Using Correlations to Summarize Linear Relationships; Summary; Exercises; Chapter 10 Using Multiple Regression to Forecast Sales; Introducing Multiple Linear Regression; Running a Regression with the Data Analysis Add-In; Interpreting the Regression Output; Using Qualitative Independent Variables in Regression; Modeling Interactions and Nonlinearities; Testing Validity of Regression Assumptions; Multicollinearity; Validation of a Regression; Summary.
- ExercisesChapter 11 Forecasting in the Presence of Special Events; Building the Basic Model; Summary; Exercises; Chapter 12 Modeling Trend and Seasonality; Using Moving Averages to Smooth Data and Eliminate Seasonality; An Additive Model with Trends and Seasonality; A Multiplicative Model with Trend and Seasonality; Summary; Exercises; Chapter 13 Ratio to Moving Average Forecasting Method; Using the Ratio to Moving Average Method; Applying the Ratio to Moving Average Method to Monthly Data; Summary; Exercises; Chapter 14 Winter's Method; Parameter Definitions for Winter's Method.