Marketing Analytics Introduction

1. Introduction
Disclaimer:
• All logos, photos, etc. used in this presentation are the property of their respective
copyright owners and are used here for educational purposes only
© Stephan Sorger 2015; www.StephanSorger.com; Marketing Analytics: Introduction Ch.1.1

2. Outline/ Learning Objectives
© Stephan Sorger 2015; www.StephanSorger.com; Marketing Analytics: Introduction Ch. 1.2
Topic Description
Introduction Marketing analytics definition, drivers, and advantages
Models Definition, styles, forms, and variables of models
Metrics Definition, families, and dashboards of metrics

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
- Models - Metrics
Models Decision tools, such as spreadsheets
Metrics Key performance indicators to monitor business
Marketing Analytics: Models, Metrics & Measurements
Models:
Decision tools,
like spreadsheets
Example: Bass Forecasting
Metrics:
KPIs to monitor business,
like charts and graphs
Example: Sales/ Channel
© Stephan Sorger 2015; www.StephanSorger.com; Marketing Analytics: Introduction Ch.1.3

4. Models and Metrics
Metrics = Gauges:
- Monitor situation
- Diagnose problems
© Stephan Sorger 2015; www.StephanSorger.com; Marketing Analytics: Introduction Ch. 1.4
Models = GPS:
- Representation of Reality
- Decide on course of action

5. Metrics Gone Wrong
Military leaders in World War II used metrics regarding airplane damage incorrectly
“Reinforce damaged areas”
Abraham Wald, a statistician skilled in analytics, said: Right Metrics, Wrong Conclusion
“Reinforce non-damaged areas” (fixing selection bias from studying only airplances that returned)
© Stephan Sorger 2015; www.StephanSorger.com; Marketing Analytics: Introduction Ch. 1.5

6. Trends Driving Marketing Analytics Adoption
Before:
Huge budgets
Now:
Tiny budgets
© Stephan Sorger 2015; www.StephanSorger.com; Marketing Analytics: Introduction Ch. 1.6
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

7. Marketing Analytics Advantages
© Stephan Sorger 2015; www.StephanSorger.com; Marketing Analytics: Introduction Ch. 1.7
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

8. Topic Description
Model Simplified representation of reality to solve problems
Example: Advertising effectiveness model
Purpose Evaluate impact of input variables
Example: Assess how advertising affects 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
© Stephan Sorger 2015; www.StephanSorger.com; Marketing Analytics: Introduction Ch. 1.8
Advertising
Sales
time
A

9. 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
© Stephan Sorger 2015; www.StephanSorger.com; Marketing Analytics: Introduction Ch. 1.9
Verbal Pictorial Mathematical
Sales = f(advertising)

10. 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
© Stephan Sorger 2015; www.StephanSorger.com; Marketing Analytics: Introduction Ch. 1.10
Descriptive Predictive Normative
Sales
Advertising
This Way

11. Topic Description
Variable Quantity that can be changed, or varied
Examples: Advertising budget, Sales
Independent Variable Variable whose value affects 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 2015; www.StephanSorger.com; Marketing Analytics: Introduction Ch. 1.11

12. 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 2015; www.StephanSorger.com; Marketing Analytics: Introduction Ch. 1.12
Models: Terminology
Linear Response Model

13. 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 2015; www.StephanSorger.com; Marketing Analytics: Introduction Ch. 1.13

14. Number Question
1 Describe how marketing analytics models are analogous to automotive
global positioning system (GPS) units.
2 Explain how marketing accountability is driving the adoption of marketing analytics.
3 Describe how marketing analytics approaches can help persuade executives.
4 Identify the type of style a model expressed in pictures represents.
5 Identify the form of model used in standard computer spreadsheet programs.
6 Understand the difference between controllable & non-controllable independent variables.
7 Understand the basic form of a linear response model: Y = a + b*X
8 Identify the types of systems that typically include metrics dashboards.
Check Your Understanding
© Stephan Sorger 2015; www.StephanSorger.com; Marketing Analytics: Introduction Ch. 1.14