Proctor Exam 2- Secondary Data Syndicated and Big Data

Question 1

Machine learning can be applied anywhere there is a

need for quick automatic decisions based on ongoing feedback from patterns in the environment.

Answer 1

Machine learning can be applied anywhere there is a

need for quick automatic decisions based on ongoing feedback from patterns in the environment.

Question 2

Problems that lend themselves to machine learning:

1. The data causes problems for traditional analytic techniques, such as where variables
   are highly correlated, data is non-linear, or where there are far more variables than
   records (so called “wide and shallow” datasets)
2. Accuracy is more important than understanding
3. Potential outputs are defined, but the action is dependent on conditions which themselves cannot be easily predicted or identified before the event happens.
4. Rules and associations might be perceived or deduced, but are not easily described by logical rules

Answer 2

Problems that lend themselves to machine learning:

1. The data causes problems for traditional analytic techniques, such as where variables
   are highly correlated, data is non-linear, or where there are far more variables than
   records (so called “wide and shallow” datasets)
2. Accuracy is more important than understanding
3. Potential outputs are defined, but the action is dependent on conditions which themselves cannot be easily predicted or identified before the event happens.
4. Rules and associations might be perceived or deduced, but are not easily described by logical rules

Question 3

What makes this a good machine-learning problem is that the decisions and
the variables constantly change and the value of one variable and the right decision may depend
on the values of many more variables. Humans instinctively make these assessments, but it is
impossible to discretely list every rule and situation for a computer to look up and evaluate.

Answer 3

What makes this a good machine-learning problem is that the decisions and
the variables constantly change and the value of one variable and the right decision may depend
on the values of many more variables. Humans instinctively make these assessments, but it is
impossible to discretely list every rule and situation for a computer to look up and evaluate.

Question 4

Machines learn by studying data to detect patterns or by applying known rules (algorithms) to:
Categorize like or unlike people or things
Identify patterns and relationships that were unknown before analysis
Predict likely outcomes or actions based on identified patterns
Detect anomalous or unexpected behaviors

Answer 4

Machines learn by studying data to detect patterns or by applying known rules (algorithms) to:
Categorize like or unlike people or things
Identify patterns and relationships that were unknown before analysis
Predict likely outcomes or actions based on identified patterns
Detect anomalous or unexpected behaviors

Question 5

Machines learn through essentially an exhaustive process of trial and error, sifting through information, comparing the information to a goal, making adjustments, and trying again

Answer 5

Machines learn through essentially an exhaustive process of trial and error, sifting through information, comparing the information to a goal, making adjustments, and trying again

Question 6

Within Machine Learning The traditional advanced analytic techniques you will learn about later in this course are not well
suited for the unstructured nature of some big data

Answer 6

Within Machine Learning The traditional advanced analytic techniques you will learn about later in this course are not well
suited for the unstructured nature of some big data

Question 7

Machine learning, however, takes advantage of a computer’s ability to
follow rules and execute swift comparisons as a fast way to understand patterns and meaning in data.

The algorithms automatically sort data, testing and comparing what it has seen in the past to what it is seeing in the present. The learning may lead to a new understanding of behavior or it might serve as automatic input to an action executed by another computer process.

Answer 7

Machine learning, however, takes advantage of a computer’s ability to
follow rules and execute swift comparisons as a fast way to understand patterns and meaning in
data.

The algorithms automatically sort data, testing and comparing what it has seen in the past to
what it is seeing in the present. The learning may lead to a new understanding of behavior or it might serve as automatic input to an action executed by another computer process.

Question 8

Supervised learning always has a predetermined outcome provided by the programmer. The machine seeks faster, more efficient, or more accurate ways to meet the goal based on the data and the programmers input.

Answer 8

Supervised learning always has a predetermined outcome provided by the programmer. The machine seeks faster, more efficient, or more accurate ways to meet the goal based on the data and the programmers input.

Question 9

Supervised Learning

Process
Machine is given pre-classified data and discovers a pattern associated with the classification. As more data becomes available, the machine adjusts its associations and gets better at classifying

Example
Sorting out junk emails from wanted content

Limitations
Only works on one task at a time.
User may not be able to interpret the associations behind the sorting.

Traditional stat tool
Regression
Classification
Decision Trees
Random Forests
Bayesian statistics

Answer 9

Supervised Learning

Process
Machine is given pre-classified data and discovers a pattern associated with the classification. As more data becomes available, the machine adjusts its associations and gets better at classifying

Example
Sorting out junk emails from wanted content

Limitations
Only works on one task at a time.
User may not be able to interpret the associations behind the sorting.

Traditional stat tool
Regression
Classification
Decision Trees
Random Forests
Bayesian statistics

Question 10

Unsupervised Learning

Here the data determines the outcome. The algorithm’s mission is to extract structure from the data, and to present the structure in a way that is useful to us. Data is segmented and scored based on what the computer itself decides is relevant or related.

Answer 10

Unsupervised Learning

Here the data determines the outcome. The algorithm’s mission is to extract structure from the data, and to present the structure in a way that is useful to us. Data is segmented and scored based on what the computer itself decides is relevant or related.

Question 11

Unsupervised Learning

Process
Machine is given a lot of data and told to hunt for patterns and “clusters” of things related to each other. It draws its own conclusions about relationships.

Example
Recommendation engines
Loyalty card targeting

Limitation
Usually requires human input after the fact

Traditional Statistics Tool
Factor Analysis
Cluster Analysis
Multidimensional Scaling
Principle Component

Answer 11

Unsupervised Learning

Process
Machine is given a lot of data and told to hunt for patterns and “clusters” of things related to each other. It draws its own conclusions about relationships.

Example
Recommendation engines
Loyalty card targeting

Limitation
Usually requires human input after the fact

Traditional Statistics Tool
Factor Analysis
Cluster Analysis
Multidimensional Scaling
Principle Component

Question 12

Reinforcement Learning

This type of learning has no supervisor, but instead it has a reward signal that defines success. Similar to human learning, when success is rewarded, the machine tries to learn the patterns that result in receiving the reinforcement signal. The machine’s decisions affect the subsequent data it receives.

Answer 12

Reinforcement Learning

This type of learning has no supervisor, but instead it has a reward signal that defines success. Similar to human learning, when success is rewarded, the machine tries to learn the patterns that result in receiving the reinforcement signal. The machine’s decisions affect the subsequent data it receives.

Question 13

Reinforcement Learning

Process
Machine not only analyzes data but uses the output to improve efficiency or create new strategies. Learns how to apply a set of rules toward an outcome in the most efficient way.

Example
Game playing bots
War Game Simulations

Limitation
Strategies may not be understandable by humans so may be limited to one situation.

Traditional Statistics Tool
Game Theory
Linear Programming

Answer 13

Reinforcement Learning

Process
Machine not only analyzes data but uses the output to improve efficiency or create new strategies. Learns how to apply a set of rules toward an outcome in the most efficient way.

Example
Game playing bots
War Game Simulations

Limitation
Strategies may not be understandable by humans so may be limited to one situation.

Traditional Statistics Tool
Game Theory
Linear Programming

Question 14

Unsupervised Learning works well if we have little or limited knowledge of the data. The best examples of this application are so-called targeting engines or recommendation engine . When a
supermarket checkout machine issues you a coupon at checkout

Answer 14

Unsupervised Learning works well if we have little or limited knowledge of the data. The best examples of this application are so-called targeting engines or recommendation engine . When a
supermarket checkout machine issues you a coupon at checkout

Question 15

The best examples of reinforcement machine learning are machines that play games. Typically the
machine is taught the rules of the game and given a goal to win.

Answer 15

The best examples of reinforcement machine learning are machines that play games. Typically the
machine is taught the rules of the game and given a goal to win.

Question 16

Big Data is “The record of all interactions with people, institutions, and things recorded and stored digitally.”
Big data, then, is the digital trail left by humans and their connected machines.

Answer 16

Big Data is “The record of all interactions with people, institutions, and things recorded and stored digitally.”
Big data, then, is the digital trail left by humans and their connected machines.

Question 17

The 7 V’s of Big Data

Volume 
Velocity
Variety
Variability
Visualization
Veracity
Value

Answer 17

The 7 V’s of Big Data

Volume 
Velocity
Variety
Variability
Visualization
Veracity
Value

Question 18

Within the Healthcare industry, pharmaceutical syndicated services tracks sales, price, and
distribution of most pharmaceuticals.

Answer 18

Within the Healthcare industry, pharmaceutical syndicated services tracks sales, price, and
distribution of most pharmaceuticals.

Question 19

The majority of pharmaceutical data comes from patient billing and processing at every point of
the drug supply chain.

Answer 19

The majority of pharmaceutical data comes from patient billing and processing at every point of
the drug supply chain.

Question 20

Unlike most CPG categories however, the pharmaceutical sales and
distribution chain involves many government regulations, physicians, other providers, and
insurance companies as mediators of sales to the patient as the ultimate consumer. As we have
said, drug products historically have not been easily tracked using industry standard digital codes
such as the UPC .

Answer 20

Unlike most CPG categories however, the pharmaceutical sales and
distribution chain involves many government regulations, physicians, other providers, and
insurance companies as mediators of sales to the patient as the ultimate consumer. As we have
said, drug products historically have not been easily tracked using industry standard digital codes
such as the UPC .

Question 21

Big Data Researcher Skills
These are the most common skills found on big data analytic teams:

Programming 
Data Manipulation
Exploratory Data Analytics 
Mathematics Statistics 
Business Skills domain Expertise
People Skills communication Skills

Answer 21

Big Data Researcher Skills
These are the most common skills found on big data analytic teams:

Programming 
Data Manipulation
Exploratory Data Analytics 
Mathematics Statistics 
Business Skills domain Expertise
People Skills communication Skills

Question 22

The evolution of big data has produced an entirely new field called data science, an interdisciplinary field about scientific methods, processes, and systems to extract knowledge or insights from data in various forms.

Answer 22

The evolution of big data has produced an entirely new field called data science, an interdisciplinary field about scientific methods, processes, and systems to extract knowledge or insights from data in various forms.

Question 23

In addition to the typical and historical skills of qualitative techniques and traditional statistical skills of quantitative surveys and analytics, modern researchers are concerned with:
Data Curation
Data Governance
Data Provenance

Answer 23

In addition to the typical and historical skills of qualitative techniques and traditional statistical skills of quantitative surveys and analytics, modern researchers are concerned with:
Data Curation
Data Governance
Data Provenance

Question 24

Data Curation

Right data is assembled for the right question

Answer 24

Data Curation

Right data is assembled for the right question

Question 25

Data Governance | Data is secure & accurate

Answer 25

Data Governance | Data is secure & accurate

Question 26

Data Provenance | Data from reputable sources & tracked through all potential uses

Answer 26

Data Provenance | Data from reputable sources & tracked through all potential uses

Question 27

Machine Learning is also being used to understand the return on investment of marketing itself ( MROI ), that is, measuring how much money is generated by investing in marketing

Answer 27

Machine Learning is also being used to understand the return on investment of marketing itself ( MROI ), that is, measuring how much money is generated by investing in marketing

Question 28

The datasets that track marketing spending are large, have more variables than cases, and contain relationships that are often non-linear mixed with responses that are well behaved and straightforward.

Answer 28

The datasets that track marketing spending are large, have more variables than cases, and contain relationships that are often non-linear mixed with responses that are well behaved and straightforward.

Question 29

Prediction and understanding are related but independent goals of market research; It is simply a decision of the business regarding the problem at hand whether one goal might be favored over the other.

Answer 29

Prediction and understanding are related but independent goals of market research; It is simply a decision of the business regarding the problem at hand whether one goal might be favored over the other.

Question 30

striking the right balance between prediction and understanding is still required

Answer 30

striking the right balance between prediction and understanding is still required

Question 31

The complexity of big data and the algorithms that read it have increased the frequency with which predictive models take precedence as more and more marketing occurs in digital environments where automation is possible and desirable.

Answer 31

The complexity of big data and the algorithms that read it have increased the frequency with which predictive models take precedence as more and more marketing occurs in digital environments where automation is possible and desirable.

Question 32

data that is collected for any purpose subsequently used in research other than to meet the needs of your particular study is called “secondary” data.

Answer 32

data that is collected for any purpose subsequently used in research other than to meet the needs of your particular study is called “secondary” data.

Question 33

secondary data in some detail: any purpose other than to meet the needs of your particular study. non-specific research purposes, called “syndicated” or multi-client data. another purpose and subsequently used in research.

Answer 33

secondary data in some detail: any purpose other than to meet the needs of your particular study. non-specific research purposes, called “syndicated” or multi-client data. another purpose and subsequently used in research.

Question 34

The second most important question in your research design, just behind the original purpose of the research, is “What is already known about your research goal?”

Answer 34

The second most important question in your research design, just behind the original purpose of the research, is “What is already known about your research goal?”

Question 35

To reiterate and re-emphasize: All market research designs for every research project should begin with an assessment of what is already known about your research problem. The answer to that question almost always involves the search for and use of secondary data in its many forms, whether you are merely searching the Internet or buying needed data from a broker.

Answer 35

To reiterate and re-emphasize: All market research designs for every research project should begin with an assessment of what is already known about your research problem. The answer to that question almost always involves the search for and use of secondary data in its many forms, whether you are merely searching the Internet or buying needed data from a broker.

Question 36

the advantage of each imagined example of secondary research is that it costs less time, money and effort.

Answer 36

the advantage of each imagined example of secondary research is that it costs less time, money and effort.

Question 37

No single organization outside of governments could fund entire population studies such as censuses or large -scale public health studies, for example

Answer 37

No single organization outside of governments could fund entire population studies such as censuses or large -scale public health studies, for example

Question 38

Secondary data may be older than you like or might be an annual estimate rather than the monthly trend information that would be best for your project; or the best information that you can nd may be at a regional level and you might need data about a city in the region

Answer 38

Secondary data may be older than you like or might be an annual estimate rather than the monthly trend information that would be best for your project; or the best information that you can nd may be at a regional level and you might need data about a city in the region

Question 39

Two key elements to review to assess the potential for bias are the original purpose of the research or data and the methodology of the original research.

Answer 39

Two key elements to review to assess the potential for bias are the original purpose of the research or data and the methodology of the original research.

Question 40

If possible, it is always a good idea to evaluate the original sources rather than a summary or an article describing the research

Answer 40

If possible, it is always a good idea to evaluate the original sources rather than a summary or an article describing the research

Question 41

The best way to evaluate accuracy is to examine multiple sources of the same estimates

Answer 41

The best way to evaluate accuracy is to examine multiple sources of the same estimates

Question 42

Finally, you should evaluate the credibility and reputation of the source of your data

Answer 42

Finally, you should evaluate the credibility and reputation of the source of your data

Question 43

One part of the syndicated data industry builds these pro les and makes them available to buyers.

Answer 43

One part of the syndicated data industry builds these pro les and makes them available to buyers.

Question 44

The bene t from knowing more about your customer is pretty obvious, and there are many ways to know them. One part of the syndicated data industry builds these pro les and makes them available to buyers.

Answer 44

The bene t from knowing more about your customer is pretty obvious, and there are many ways to know them. One part of the syndicated data industry builds these pro les and makes them available to buyers.

Question 45

Psychographics pertain to people’s values, attitudes, lifestyles , and personalities. These deeper, more personal and less obviously observed criteria are helpful in understanding consumer motivation.

Answer 45

Psychographics pertain to people’s values, attitudes, lifestyles , and personalities. These deeper, more personal and less obviously observed criteria are helpful in understanding consumer motivation.

Question 46

Demographics: Grouping people by age, gender, ethnicity, income, education, geographic or other physical and structural characteristics.

Answer 46

Demographics: Grouping people by age, gender, ethnicity, income, education, geographic or other physical and structural characteristics.

Question 47

Behavioral: Grouping people by common behaviors, e.g., products purchased, websites or stores visited, shopping behaviors.

Answer 47

Behavioral: Grouping people by common behaviors, e.g., products purchased, websites or stores visited, shopping behaviors.

Question 48

Psychographics: Grouping people by shared values, | principles, personality, interests, and lifestyle.

Answer 48

Psychographics: Grouping people by shared values, | principles, personality, interests, and lifestyle.

Question 49

Market Share is one of the oldest and simplest forms of measuring performance and seems so basic that many do not realize that Arthur Nielsen, Sr. actually invented it as a tracking measure in his first Nielsen syndicated database in the 1930s

Answer 49

Market Share is one of the oldest and simplest forms of measuring performance and seems so basic that many do not realize that Arthur Nielsen, Sr. actually invented it as a tracking measure in his first Nielsen syndicated database in the 1930s

Question 50

Simply tracking the sales of a product relative | to total category sales is still a simple and powerful measure of performance

Answer 50

Simply tracking the sales of a product relative | to total category sales is still a simple and powerful measure of performance

Question 51

A Development Index compares the sales of a product to either population (as sales per capita) or to total possible ACV in a market.

Answer 51

A Development Index compares the sales of a product to either population (as sales per capita) or to total possible ACV in a market.

Question 52

The Developmental Indices allow you to quickly spot performance gaps and detect any regional issues that might result from retail performance, sales personnel performance or even product preference

Answer 52

The Developmental Indices allow you to quickly spot performance gaps and detect any regional issues that might result from retail performance, sales personnel performance or even product preference

Question 53

High Category Indices show reasonable demand for products similar to ours, but for some reason, we are not appealing to the market or there is a barrier to our sales that bears further investigation.

Answer 53

High Category Indices show reasonable demand for products similar to ours, but for some reason, we are not appealing to the market or there is a barrier to our sales that bears further investigation.

Question 54

The BDI/CDI chart can help visualize where our new product might have high potential (High CDI) but face strong competition (High Competitive BDI). When over 50 markets are commonly available, this matrix helps organize and visualize the information.

Answer 54

The BDI/CDI chart can help visualize where our new product might have high potential (High CDI) but face strong competition (High Competitive BDI). When over 50 markets are commonly available, this matrix helps organize and visualize the information.

Question 55

Advanced analytic techniques can precisely estimate and predict the effects of the change for every item, product, brand, or category, but often simple observational techniques and arithmetic can provide much real information to inform price decisions

Answer 55

Advanced analytic techniques can precisely estimate and predict the effects of the change for every item, product, brand, or category, but often simple observational techniques and arithmetic can provide much real information to inform price decisions

Question 56

Every company generates and retains data as part of | conducting their business and much of it is useful in answering market research questions.

Answer 56

Every company generates and retains data as part of | conducting their business and much of it is useful in answering market research questions.

Question 57

Most modern businesses compile information in customer databases, data warehouses, or enterprise decision support systems. Increasingly this information is augmented by external information obtained from sources we will discuss later so that massive amounts of information are available internally.

Answer 57

Most modern businesses compile information in customer databases, data warehouses, or enterprise decision support systems. Increasingly this information is augmented by external information obtained from sources we will discuss later so that massive amounts of information are available internally.

Question 58

Modern computing power is enabling businesses to track and manage millions of customers, whether consumers or businesses, in a practice called Customer Relationship Management (CRM

Answer 58

Modern computing power is enabling businesses to track and manage millions of customers, whether consumers or businesses, in a practice called Customer Relationship Management (CRM

Question 59

Data mining is the application of usually automated analytic techniques to nd patterns in data that can be used to grow a business

Answer 59

Data mining is the application of usually automated analytic techniques to nd patterns in data that can be used to grow a business

Question 60

two types of | external data: Syndicated Services and Big Data.

Answer 60

two types of | external data: Syndicated Services and Big Data.

Question 61

Technologies that promise to automate and discover new insights about customers and consumers are transforming the market research industry as well. Technology and the Internet have now automated many market research processes that replace what was considerable human effort. Data coding, text analysis, sample selection, and questionnaire management and creation are all examples Automated facial recognition algorithms can now detect emotional response to advertising real time. Advanced data fusion techniques interconnect and link attitudes and opinions from thousands of surveys that may share only the minimum of actual questionnaire content

Answer 61

Technologies that promise to automate and discover new insights about customers and consumers are transforming the market research industry as well. Technology and the Internet have now automated many market research processes that replace what was considerable human effort. Data coding, text analysis, sample selection, and questionnaire management and creation are all examples Automated facial recognition algorithms can now detect emotional response to advertising real time. Advanced data fusion techniques interconnect and link attitudes and opinions from thousands of surveys that may share only the minimum of actual questionnaire content

Question 62

So it makes sense that primary and secondary research often work together in the same project

Answer 62

So it makes sense that primary and secondary research often work together in the same project

Question 63

The use of multiple sources validates your data and investigation by cross verifying the same ideas and information. This process is sometimes known as data triangulation , taken from the navigation process of locating an unknown point in space through geometric relationships among other known points. You can validate by triangulating data sources, research methods, or even theories

Answer 63

The use of multiple sources validates your data and investigation by cross verifying the same ideas and information. This process is sometimes known as data triangulation , taken from the navigation process of locating an unknown point in space through geometric relationships among other known points. You can validate by triangulating data sources, research methods, or even theories

Question 64

Data triangulation is simply using evidence from many di erent types of data sources, such as interviews, documents, public records, social media conversations, or observations.

Answer 64

Data triangulation is simply using evidence from many di erent types of data sources, such as interviews, documents, public records, social media conversations, or observations.

Question 65

``` Theory triangulation is a bit more complicated because the theories are helping you understand your data better rather than the sorts of integration required in data and methodology triangulation. Here you are applying different theories to the data to help make sense of it. One theory might support your data and another might undermine it. ```

Answer 65

``` Theory triangulation is a bit more complicated because the theories are helping you understand your data better rather than the sorts of integration required in data and methodology triangulation. Here you are applying different theories to the data to help make sense of it. One theory might support your data and another might undermine it. ```

Question 66

It is important to remember when working with secondary data that it often contains personal data; that is, data that can be used either directly or indirectly (e.g., by combining it with other data) about a specific individual.

Answer 66

It is important to remember when working with secondary data that it often contains personal data; that is, data that can be used either directly or indirectly (e.g., by combining it with other data) about a specific individual.

Question 67

Two key responsibilities that apply to secondary data: 1. Researchers must ensure that personal data used in research is thoroughly protected from unauthorized access and never disclosed without the consent of the data subject. 2. Researchers must always behave ethically and not do anything that might cause harm to a data subject or damage the reputation of market, opinion, and social research.

Answer 67

Two key responsibilities that apply to secondary data: 1. Researchers must ensure that personal data used in research is thoroughly protected from unauthorized access and never disclosed without the consent of the data subject. 2. Researchers must always behave ethically and not do anything that might cause harm to a data subject or damage the reputation of market, opinion, and social research.

Question 68

This data is collected or purchased by research companies and then the curated data is sold to multiple buyers to help track or interpret their businesses. The companies collect the data once, but sell it many times to multiple buyers as a subscription. The research companies also leverage the data for research products and consulting services that may be customized for their customers.

Answer 68

This data is collected or purchased by research companies and then the curated data is sold to multiple buyers to help track or interpret their businesses. The companies collect the data once, but sell it many times to multiple buyers as a subscription. The research companies also leverage the data for research products and consulting services that may be customized for their customers.

Question 69

Many research companies syndicate what are called “ omnibus surveys ”, where questions on many topics are conducted during the same interview

Answer 69

Many research companies syndicate what are called “ omnibus surveys ”, where questions on many topics are conducted during the same interview

Question 70

By keeping track of unique but anonymous identi ers and using advanced data fusion techniques, CivicScience builds a massive database of opinions, preferences, attitudes, and demographic information that it provides to its customers by subscription.

Answer 70

By keeping track of unique but anonymous identi ers and using advanced data fusion techniques, CivicScience builds a massive database of opinions, preferences, attitudes, and demographic information that it provides to its customers by subscription.

Question 71

Household Panel Sales Data The types of syndicated sales tracking data discussed so far are very accurate estimates of sales and share in a market, but they hide some very important dynamics of purchasing necessary to understand trends, diagnose performance, and grow products with the right marketing plans

Answer 71

Household Panel Sales Data The types of syndicated sales tracking data discussed so far are very accurate estimates of sales and share in a market, but they hide some very important dynamics of purchasing necessary to understand trends, diagnose performance, and grow products with the right marketing plans

Question 72

Market Measurement What the business does not know, however, is how much its competitors are selling, and the need for that knowledge drives the largest scale type of syndicated data: sales tracking for consumer goods.

Answer 72

Market Measurement What the business does not know, however, is how much its competitors are selling, and the need for that knowledge drives the largest scale type of syndicated data: sales tracking for consumer goods.

Question 73

The markets for consumer package goods (CPG) known as Fast Moving Consumer Goods (FMCG) outside the United States, is particularly well suited for this kind of tracking. The distribution channels are well known, products are identi ed easily, and there are lots of CPG businesses that can pay for the information and support the costs of collecting the data.

Answer 73

The markets for consumer package goods (CPG) known as Fast Moving Consumer Goods (FMCG) outside the United States, is particularly well suited for this kind of tracking. The distribution channels are well known, products are identi ed easily, and there are lots of CPG businesses that can pay for the information and support the costs of collecting the data.

Question 74

The Universal Product Code or UPC, developed in the early 1970s to help automate inventory tracking, proved also to be an essential factor in automating collection of market information and almost instantly ampli ed our ability to understand and optimize price, promotion, and distribution.

Answer 74

The Universal Product Code or UPC, developed in the early 1970s to help automate inventory tracking, proved also to be an essential factor in automating collection of market information and almost instantly ampli ed our ability to understand and optimize price, promotion, and distribution.

Question 75

The UPC scanner that allowed quick check-out and payment at the supermarket also automatically entered each transaction into an electronic database that grew with each transaction

Answer 75

The UPC scanner that allowed quick check-out and payment at the supermarket also automatically entered each transaction into an electronic database that grew with each transaction

Question 76

By the late 1970s, a research company named Information Resources Incorporated (IRI) realized the potential for using UPC’s as the basis for automated and powerful data collection for market research.

Answer 76

By the late 1970s, a research company named Information Resources Incorporated (IRI) realized the potential for using UPC’s as the basis for automated and powerful data collection for market research.

Question 77

The basic structure of all syndicated scanner databases is similar no matter who builds or sells it. Databases consist of five essential elements: Product, Markets, class of Trade, Time Periods and measures

Answer 77

The basic structure of all syndicated scanner databases is similar no matter who builds or sells it. Databases consist of five essential elements: Product, Markets, class of Trade, Time Periods and measures

Question 78

The basic measure of audience size is the audience rating .

Answer 78

The basic measure of audience size is the audience rating .

Question 79

rating is de ned as the number of households with their radio/TV sets tuned to a particular station/channel or program for a speci ed length of time divided by the total number of households that have radio/TV.

Answer 79

rating is de ned as the number of households with their radio/TV sets tuned to a particular station/channel or program for a speci ed length of time divided by the total number of households that have radio/TV.

Question 80

The other fundamental measure is audience share , which is the number of TV sets in use tuned to a program or commercial.

Answer 80

The other fundamental measure is audience share , which is the number of TV sets in use tuned to a program or commercial.

Question 81

Nielsen has had to expand its service to cover this now very fragmented audience and other research companies have stepped up to o er di erent versions of so-called “ cross-platform ” audience measurement.

Answer 81

Nielsen has had to expand its service to cover this now very fragmented audience and other research companies have stepped up to o er di erent versions of so-called “ cross-platform ” audience measurement.

Question 82

atistically, when a sample cannot or does not measure something that is real, it is called sampling error . Sampling error happens when a sample is not representative of a population or is not large enough to accurately measure a population condition.

Answer 82

atistically, when a sample cannot or does not measure something that is real, it is called sampling error . Sampling error happens when a sample is not representative of a population or is not large enough to accurately measure a population condition.

Question 83

``` Although the datasets are large, they may not be representative, and therefore not projectable to wider situations The datasets build so fast they may accumulate incorrect information. Sometimes the underlying process behind the accumulation of data makes the data in the past less predictive of the future. A predictive process that works well enough once may not work in the future Sometimes the variables of big data are not the things that are closest to what we want to measure directly ```

Answer 83

``` Although the datasets are large, they may not be representative, and therefore not projectable to wider situations The datasets build so fast they may accumulate incorrect information. Sometimes the underlying process behind the accumulation of data makes the data in the past less predictive of the future. A predictive process that works well enough once may not work in the future Sometimes the variables of big data are not the things that are closest to what we want to measure directly ```

Question 84

We are going to focus on one type of this research Sentiment Analysis , as an example, because of its popularity and promise. We will also see how big data can supplement and amplify primary research, and at least speculate on the value of the sensor data from connected devices as a secondary research application.

Answer 84

We are going to focus on one type of this research Sentiment Analysis , as an example, because of its popularity and promise. We will also see how big data can supplement and amplify primary research, and at least speculate on the value of the sensor data from connected devices as a secondary research application.

Question 85

Sentiment Analysis tries to analytically determine the attitude of a speaker or writer with respect to some topic. The attitude may be an opinion, or an intended or actual emotional state.

Answer 85

Sentiment Analysis tries to analytically determine the attitude of a speaker or writer with respect to some topic. The attitude may be an opinion, or an intended or actual emotional state.

Question 86

Computers read words through a process called Natural Language Processing (NLP) and they infer sentiment by a combination of NLP and machine learning. Both NLP and sentiment analysis are very complex computer processes to accomplish a task that seems obvious to humans, but the sheer scale of the data requires a machine. New algorithms are continuously improving our ability to accurately read this data in a field of computer science that is relatively young.

Answer 86

Computers read words through a process called Natural Language Processing (NLP) and they infer sentiment by a combination of NLP and machine learning. Both NLP and sentiment analysis are very complex computer processes to accomplish a task that seems obvious to humans, but the sheer scale of the data requires a machine. New algorithms are continuously improving our ability to accurately read this data in a field of computer science that is relatively young.

Question 87

Three Sentiment Analysis Approaches Knowledge Based Statistically Based Hybrid

Answer 87

Three Sentiment Analysis Approaches Knowledge Based Statistically Based Hybrid

Question 88

Knowledge Based Pre-classify text by categories based on the presence of unambiguous words such as happy, sad, angry, or bored. Assign scores to more ambiguous terms based on previous search Compare analysis text to pre-scored reference database

Answer 88

Knowledge Based Pre-classify text by categories based on the presence of unambiguous words such as happy, sad, angry, or bored. Assign scores to more ambiguous terms based on previous search Compare analysis text to pre-scored reference database

Question 89

Statistically Based Use machine learning to train algorithms against known outcomes. For example, a machine can sift through reviews and learn which words in the reviews are associated with accompanying star ratings Compare analysis text to a reference database built from the statistical analysis

Answer 89

Statistically Based Use machine learning to train algorithms against known outcomes. For example, a machine can sift through reviews and learn which words in the reviews are associated with accompanying star ratings Compare analysis text to a reference database built from the statistical analysis

Question 90

Hybrid Both methods combined, for example pre- coding unambiguous words and modeling more ambiguous terms against star ratings Compare analysis text to a reference database

Answer 90

Hybrid Both methods combined, for example pre- coding unambiguous words and modeling more ambiguous terms against star ratings Compare analysis text to a reference database

Question 91

Given a target subject, then, sentiment analysis can analyze an enormous amount of text and classify whether the text is generally positive, negative, or neutral about the subject. The best techniques are pretty good at this task relative to human classi cation. Many studies have shown that there is generally about 80% agreement between human readers in classifying the same text. The best machines analysis achieves about 70%. That level is pretty good compared to 80%.

Answer 91

Given a target subject, then, sentiment analysis can analyze an enormous amount of text and classify whether the text is generally positive, negative, or neutral about the subject. The best techniques are pretty good at this task relative to human classi cation. Many studies have shown that there is generally about 80% agreement between human readers in classifying the same text. The best machines analysis achieves about 70%. That level is pretty good compared to 80%.

Question 92

Machines currently are not as accurate when assessing finer degrees of positivity or negativity, as in the difference between a 4- and a 5-star rating in a review.

Answer 92

Machines currently are not as accurate when assessing finer degrees of positivity or negativity, as in the difference between a 4- and a 5-star rating in a review.

Question 93

Probably the biggest limitation of sentiment analysis is that all social listening data, no matter how much of it exists, is essentially qualitative. Most comments are by de nition non-representative. People passionate enough to comment generate these comments, and they are people with access to social media. The large number of comments does not change this inherent fact.

Answer 93

Probably the biggest limitation of sentiment analysis is that all social listening data, no matter how much of it exists, is essentially qualitative. Most comments are by de nition non-representative. People passionate enough to comment generate these comments, and they are people with access to social media. The large number of comments does not change this inherent fact.

Question 94

Internet of Things analysis is not yet a common form of data | for marketing organizations. It is being tested and we are all learning.

Answer 94

Internet of Things analysis is not yet a common form of data | for marketing organizations. It is being tested and we are all learning.