Lec -1 & 2MarketingAnalytics_Ch1_Introduction.ppt
- 2. Introduction
- 3. Topic Description Definition (Broad) Broad definition (but too vague): Data analysis for marketing purposes, from data gathering to analysis to reporting Definition (Applied) Techniques and tools to provide actionable insight by using - Models - Metrics Marketing Analytics: Models, Metrics & Measurements
- 4. Models • Models are Decision tools that aid us in decision making based on marketing data and organizational objectives. • Models simplify the real world along the dimensions of interest. • Models allow us to focus our efforts., e.g. Regression model, discriminant model etc. • We use spreadsheets to implement decision models. • As an analogy we can consider GPS navigation in a car is the model which is the simplification of the real world ( the map do not show rocks and trees), it is representative ( the map are to scale) and it serves as a decision making tool ( drivers can decide which route to take , based on information in the maps)
- 5. Metrics • Metrics are measurement representing performance level of important variables within an organization such as sales revenue. • Marketers can apply metrics to monitor situations and diagnose problems. • Organizations refers metrics as Key performance indicators to monitor business as they indicate the performance of important attributes of the company such as sales in different markets. • Marketers can leverage the information gained by metrics as insight toward the performance of the system. • As an analogy for metrics, one could consider the instruments in a car(speedometer, odometer, fuel gauge, temperature, etc.) to display key metrics. The instruments display vital information to monitor the status of the vehicle. The driver can see the speedometer to check its speed, odometer and fuel gauge to notice its fuel consumption. The driver can also use the metrics to diagnose the problem( the quickly climbing temperature gauge could signal an overheating engine.)
- 6. Models: Decision tools, like spreadsheets Example: Bass Forecasting Metrics: KPIs to monitor business, like charts and graphs Example: Sales/ Channel
- 7. Models and Metrics Metrics = Gauges: - Monitor situation - Diagnose problems Models = GPS: - Representation of Reality - Decide on course of action
- 8. Trends Driving Marketing Analytics Adoption Before: Huge budgets Now: Tiny budgets Marketing Analytics Adoption Online Data Availability Reduced Resources Massive Data Accountability Data-Driven Presentations Improve productivity Reduce costs “What gets measured gets done” Data to back up proposals Predict success of plans Initiatives to capture customer information What to do with all that data? Cloud-based data storage Online = speed Online = convenience Do more with less Scrutinized budgets Marketers must show outcomes
- 9. Marketing Analytics Advantages Marketing Analytics Advantages Persuade Executives Side-step Politics Encourage Experimentation Drive Revenue Save Money Marketing as cost center Marketing as profit center Correlation between spending and results Old way: Execute campaign guess outcome No longer tolerate such an approach New way: Predict outcome Test multiple scenarios before proceeding Run simulations Predict which will work best Focus on revenue impact from marketing Correlation between spending & results Some CEOs do not appreciate marketing Show impact of efforts with metrics
- 10. Topic Description Model Simplified representation of reality to solve problems Example: Advertising effectiveness model Purpose Evaluate impact of input variables Example: Assess how advertising impacts sales Decisions Models provide guidance on marketing actions Example: Decide on ad budget to achieve objectives Models: What is a Model? Advertising Effectiveness: Response (sales revenue) increases with increasing ad budget until Point A, then decreases Sales time A © Stephan Sorger 2016 www.StephanSorger.com; Marketing Analytics: Introduction 7
- 11. Topic Description Verbal Expressed in words “Sales is influenced by advertising” Pictorial Expressed in pictures Chart or graph of phenomenon Mathematical Expessed in equation Sales = a + b * Advertising Styles: Verbal, Pictorial, Mathematical Verbal Pictorial Mathematical Sales = f(advertising) © Stephan Sorger 2016 www.StephanSorger.com; Marketing Analytics: Introduction 8
- 12. Topic Description Descriptive Characterize (describe) marketing phenomenon Identify causal relationships and relevant variables Example: Sales = a*Advertising + b*Features +c*… Predictive Determine likely outcomes given certain inputs Classic “What If?” spreadsheet exercise Example: Sales forecast model Normative Decide best course of action to maximize objective, given limits on input variables (constrained optimization) “Given X, what should I do?” Example: Determine price using forecasts at diff. prices Models: Forms Descriptive Predictive Normative Sales Advertising This Way © Stephan Sorger 2016 www.StephanSorger.com; Marketing Analytics: Introduction 9
- 13. Topic Description Variable Quantity that can be changed, or varied Examples: Advertising budget, Sales Independent Variable Variable whose value impacts dependent variable (x) Controllable: Advertising budget Non-controllable: Customer age Dependent Variable Variable representing marketing objective (y, or output) Responds to changes in independent variable For-profit: Revenue, Profit; Not-for-profit: Donations Models: Variables © Stephan Sorger 2016 www.StephanSorger.com; Marketing Analytics: Introduction 10
- 14. Models: Terminology: Linear Response Model Y = a + b * X Y = Sales (Dependent Variable) (Output) a = Parameter: Y-intercept b = Parameter: Slope x = Advertising (Independent Variable) (Input) 1 b Slope = rise/run = b/1 X (Advertising) Independent Variable Y (Sales) Dependent Variable Y-intercept (Sales level when advertising spending =0) © Stephan Sorger 2016 www.StephanSorger.com; Marketing Analytics: Introduction 11
- 15. Topic Description Definition Business-oriented key performance indicators Examples: Sales per channel, Cost per sale Purpose Monitor and improve marketing effectiveness Take corrective action as necessary Example: Marketing expense as percentage of sales Metrics Families Groups of control metrics; Diagnostic & predictive info Example: Sales metrics: sales/industry; sales/product Metrics Dashboards Marketing automation systems - Eloqua, Marketo, Pardot Salesforce automation systems Netsuite, Salesforce.com Metrics Metrics Dashboard © Stephan Sorger 2016 www.StephanSorger.com; Marketing Analytics: Introduction 12
- 16. Outline/ Learning Objectives Topic Description Definitions Styles and Forms Metrics © Stephan Sorger 2016; www.StephanSorger.com; Marketing Analytics: Introduction 1
- 17. Let’s Get Started! East Bay South Bay Peninsula SF North Bay Example: Team 1: SF-Marina Team 2: SF-Downtown Team 3: East Bay Team 4: North Bay Team 5: Peninsula/ South Bay Participant Introductions - Name Say your name clearly so others can hear you - Reason for being here What you hope to learn in the course - Geographical area Desired geographical area for team meetings Listen for your area during introductions During Class Break - Meet with Others Meet with others from your area during break - Contact Info Exchange email addresses & phone numbers - Get to Know Familiarize yourself with others during cases © Stephan Sorger 2016 www.StephanSorger.com; Marketing Analytics: Introduction 13