Marketing Analytics Exam #1 Questions
With Accurate Answers
Marketing analytics - ANSWER the practice of measuring, managing and analyzing
marketing performance to maximize its effectiveness
Data Visualization - ANSWER the presentation of qualitative and quantitative data in a
pictorial or graphical format
qualitative data - ANSWER data involving textual, visual or oral information... the focus is
on stories, visual portrayals, and descriptions
quantitative data - ANSWER data represents phenomena by assigning numeric values
Why is Data Visualization important? - ANSWER 90% of information transformed to the
brain is visual
Visuals are processed 60,000 times faster in the brain than text
What is Visual Organization? - ANSWER one that increasingly uses new data
visualization tools to help employees at all levels make better decisions
Types of Data Visualization - ANSWER Word clouds, Charts (pie, bar), Infographics
What is an infographic? - ANSWER a artistic representation of information in a graphic
format designed using different elements such as graphs, pictures, narratives, timelines
When/Why use Data Visualization? - ANSWER to explore the data
-to find patterns and trends to get insights
-to find research questions before using more advanced statistical analyses
to make your audience more engaged
Word cloud - ANSWER a visual representation of unstructured text data
-font size represents word frequency (# of times a word appears in a context)
-layout and color are developed based on different semantic coherence criteria
When to use Word Clouds in Marketing? - ANSWER analysis of customer feedback
to illustrate the content of your websites or blogs
to enhance your Search Engine Optimization (SEO)
,Competitive Analysis
Search Engine Optimization (SEO) - ANSWER optimizing your website to generate
organic traffic from search engines like google
Advantages of Word Clouds - ANSWER essential keywords are revealed
quick to implement
no need to code qualitative data and analyze the content of the data
good visual tool for massive unstructured text data
Disadvantages of Word Clouds - ANSWER interpretation is subjective
limited to the basic count information - size for the frequency of occurrence
overwhelming with a lot of key words and colors
The Iceberg Principle - ANSWER the symptom which is observable and measurable
represent 10% of the true problem, while 90% of the problem is neither typically
observable nor clearly understood
1. Define marketing goals/KPIs (STEP 1) - ANSWER Build awareness, Acquire new
customers, Increase loyalty
Find data source and collect data (STEP 2) - ANSWER Primary data, secondary data,
internal secondary database, external secondary database
Primary Data - ANSWER Data gathered by the researcher for a specific purpose
addressing the research problem.
Examples:
Survey, observation, experiment, interviews
Secondary Data - ANSWER Data gathered from other sources that are already
published.
Examples:
Census data, internet information, library database, books, journal articles
Internal Secondary Database - ANSWER Data collected within the firm
Examples:
Sales records,
Accounting information (cost records)
Customer database
, External Secondary Database - ANSWER Data collected by outside agencies
Books/Periodicals
Government sources
Trade association sources
Commercial sources
Consumer data
Prepare data for analysis (STEP 3) - ANSWER Data Preparation Process
1. Integrate multiple data > 2. Clean Data > Transform Data
Relational Database - ANSWER a collection of data organized as a set of table
Each table contains one or more data categories (variables) in columns and one or more
observations (e.g., customers, products, date, grocery store and so on) in rows
Data Integration - ANSWER merges multiple data into one dataset
Marketing Analytics Process - ANSWER 1. Define marketing analytics goals/KPI's
2. Find data source and collect data
3. Prepare data for analysis
4. Analyze data
5. Report findings
Data Preparation Process - ANSWER 1. Integrate multiple data > 2. Clean Data >
Transform Data
Steps of merging multiple datasets - ANSWER Step 1. Determine whether to use
vertical, horizontal, or a mix of both types
Step 2. Find key variable(s) for merging datasets
Step 3. Sort by key variable(s)
With Accurate Answers
Marketing analytics - ANSWER the practice of measuring, managing and analyzing
marketing performance to maximize its effectiveness
Data Visualization - ANSWER the presentation of qualitative and quantitative data in a
pictorial or graphical format
qualitative data - ANSWER data involving textual, visual or oral information... the focus is
on stories, visual portrayals, and descriptions
quantitative data - ANSWER data represents phenomena by assigning numeric values
Why is Data Visualization important? - ANSWER 90% of information transformed to the
brain is visual
Visuals are processed 60,000 times faster in the brain than text
What is Visual Organization? - ANSWER one that increasingly uses new data
visualization tools to help employees at all levels make better decisions
Types of Data Visualization - ANSWER Word clouds, Charts (pie, bar), Infographics
What is an infographic? - ANSWER a artistic representation of information in a graphic
format designed using different elements such as graphs, pictures, narratives, timelines
When/Why use Data Visualization? - ANSWER to explore the data
-to find patterns and trends to get insights
-to find research questions before using more advanced statistical analyses
to make your audience more engaged
Word cloud - ANSWER a visual representation of unstructured text data
-font size represents word frequency (# of times a word appears in a context)
-layout and color are developed based on different semantic coherence criteria
When to use Word Clouds in Marketing? - ANSWER analysis of customer feedback
to illustrate the content of your websites or blogs
to enhance your Search Engine Optimization (SEO)
,Competitive Analysis
Search Engine Optimization (SEO) - ANSWER optimizing your website to generate
organic traffic from search engines like google
Advantages of Word Clouds - ANSWER essential keywords are revealed
quick to implement
no need to code qualitative data and analyze the content of the data
good visual tool for massive unstructured text data
Disadvantages of Word Clouds - ANSWER interpretation is subjective
limited to the basic count information - size for the frequency of occurrence
overwhelming with a lot of key words and colors
The Iceberg Principle - ANSWER the symptom which is observable and measurable
represent 10% of the true problem, while 90% of the problem is neither typically
observable nor clearly understood
1. Define marketing goals/KPIs (STEP 1) - ANSWER Build awareness, Acquire new
customers, Increase loyalty
Find data source and collect data (STEP 2) - ANSWER Primary data, secondary data,
internal secondary database, external secondary database
Primary Data - ANSWER Data gathered by the researcher for a specific purpose
addressing the research problem.
Examples:
Survey, observation, experiment, interviews
Secondary Data - ANSWER Data gathered from other sources that are already
published.
Examples:
Census data, internet information, library database, books, journal articles
Internal Secondary Database - ANSWER Data collected within the firm
Examples:
Sales records,
Accounting information (cost records)
Customer database
, External Secondary Database - ANSWER Data collected by outside agencies
Books/Periodicals
Government sources
Trade association sources
Commercial sources
Consumer data
Prepare data for analysis (STEP 3) - ANSWER Data Preparation Process
1. Integrate multiple data > 2. Clean Data > Transform Data
Relational Database - ANSWER a collection of data organized as a set of table
Each table contains one or more data categories (variables) in columns and one or more
observations (e.g., customers, products, date, grocery store and so on) in rows
Data Integration - ANSWER merges multiple data into one dataset
Marketing Analytics Process - ANSWER 1. Define marketing analytics goals/KPI's
2. Find data source and collect data
3. Prepare data for analysis
4. Analyze data
5. Report findings
Data Preparation Process - ANSWER 1. Integrate multiple data > 2. Clean Data >
Transform Data
Steps of merging multiple datasets - ANSWER Step 1. Determine whether to use
vertical, horizontal, or a mix of both types
Step 2. Find key variable(s) for merging datasets
Step 3. Sort by key variable(s)
