MKTG 390 quiz review

Marsha, a 30-year-old woman, is shopping online for clothes and adds a blouse to her cart. Based on this information, identify an example of a promotional message that uses item to item collaborative filtering. "Female customers in your age group also bought lipstick." "Customers who are similar to you also liked a shirt ." "Male customers in your age group also bought a jacket." "Customers who bought a shirt also bought a scarf."

"Customers who bought a shirt also bought a scarf."

Ben, age 65, is shopping for groceries online and adds a pack of pancake mix to his cart. Based on this information, identify an example of a promotional message that uses item to item collaborative filtering. "Male customers in your age group also bought a can of tuna." "Customers who bought pancake mix also bought toothpaste." "Customers who bought pancake mix also bought maple syrup." "Male customers in your age group also bought strawberries."

"Customers who bought pancake mix also bought maple syrup."

Rupert, age 16, is shopping online for a baseball cap. Using this information, identify an example of a promotional message that employs user to item collaborative filtering. "Customers who share your interest also bought a baseball bat." "Customers who live in tropical weather also bought ice cream." "Customers who bought a baseball cap also bought ice cream." "Customers who bought a baseball cap also bought a baseball bat."

"Customers who share your interest also bought a baseball bat."

A typical silhouette score ranges between ________. +5 and −5 +10 and −10 +1 and −1 +100 and −100

+1 and −1

Which of the following is true of the supervised model of analytics? A supervised model typically employs clustering methods to identify patterns in data Association analysis and collaborative filtering are typical examples of the supervised model of analytics A supervised model is one that consists of a defined target variable In a supervised model, all data is unlabeled

A supervised model is one that consists of a defined target variable

Identify a true statement about an unsupervised model. Unsupervised learning enables the collection of data or a data output from a previous calculation An unsupervised model has no target variable An unsupervised model includes techniques that require a defined outcome measure An unsupervised model provides an answer key the algorithm can use to evaluate its training data accuracy

An unsupervised model has no target variable

Which of the following is true of the agglomerative clustering approach? At the end of the process, all observations are included in a single cluster All observations are initially assigned to a single cluster The most dissimilar observations are sequentially separated from the initial 100-observation cluster The process starts with a single cluster of 100 and quickly ends up with 100 different clusters

At the end of the process, all observations are included in a single cluster

Identify a true statement about AutoML. AutoML facilitates accurate decision making for users with limited coding and modeling experience AutoML capabilities cannot be easily extended to populations beyond traditional data scientists, particularly in medium- and smaller-sized businesses AutoML, if implemented precisely, can replace human analytical expertise AutoML is mainly an unsupervised approach that employs the traditional, manual approach of standard machine learning

AutoML facilitates accurate decision making for users with limited coding and modeling experience

Identify a true statement about the hidden layer of a neural network. Calculations are carried out in this method and weights are produced from the input layer This layer is used to input data into the neural network for analysis Data from the output layer is transferred to the hidden layer The neural network model arrives at a prediction in the hidden layer

Calculations are carried out in this method and weights are produced from the input layer

In the k-means clustering algorithm, what happens after observations are randomly assigned to a cluster? Cluster centroids are recalculated Cluster centroids are determined Initial k clusters are determined Observations are reassigned

Cluster centroids are determined

Which of the following statements is true of the clustering process? It typically assigns names and definitions to unrelated sections of data It enables companies to assign groups of customers to their network It enables marketers to forecast revenue for next quarter It enables marketers to identify hidden structures in data

It enables marketers to identify hidden structures in data

Which of the following is true of AutoML? AutoML is mainly an unsupervised approach that employs the traditional, manual approach of standard machine learning AutoML capabilities cannot be easily extended to populations beyond traditional data scientists, particularly in medium- and smaller-sized businesses AutoML, if implemented precisely, can replace human analytical expertise The AutoML platform is typically capable of analytical discovery of relationships actually present in the dataset

The AutoML platform is typically capable of analytical discovery of relationships actually present in the dataset

Identify a true statement regarding the divisive clustering approach of hierarchical clustering. It is a bottom-up approach in which each observation is initially considered to be a separate cluster The process starts with a single cluster of 100 and ends up with 100 different clusters At the end of the process, all observations are included in a single cluster All observations are assigned to a cluster that has unique and common characteristics

The process starts with a single cluster of 100 and ends up with 100 different clusters

Which of the following is true of neural networks? They are based on the chemical reactions that make up brain signals They are cheaper and simpler to execute as compared to linear regression methods They are algorithms trained to recognize patterns in large volumes of data They are most useful when predictive relationships are linear

They are algorithms trained to recognize patterns in large volumes of data

An ensemble model blends the most favorable elements from all models into a single model. True False

True

Appropriate data preparation to ensure the quality of data is an elemental first step in producing accurate model predictions. True False

True

Cluster analysis is an effective and efficient method of executing market segmentation to identify subgroups of customers to help improve business and marketing decisions and therefore performance. True False

True

Collaborative filtering is based on data such as what a user has purchased in the past, which items a user liked, and what other similar customers have viewed and bought. True False

True

Distinguishing clusters from the larger population or dataset is necessary for learning and responding to different engagement or buying behaviors. True False

True

Facebook uses AutoML to understand user patterns to improve business performance, such as increasing ad revenues and user engagement. True False

True

Market basket analysis, sometimes referred to by marketers as association discovery, uses purchase transaction data to identify links between products or combinations of products and services that occur together frequently. True False

True

Market segmentation enables companies to divide business and consumer markets into smaller groups that have shared characteristics. True False

True

Neural networks can aid marketers in predicting customer behavior, understanding buyer segmentation, developing brand strategies, forecasting sales, optimizing inventory, improving marketing automation, developing digital content, and much more. True False

True

Regression is useful for forecasting consumer behavior when predictive relationships are linear. True False

True

Segmenting a market using shared characteristics is called cluster analysis. True False

True

The logic of neural networks is based on patterns recognized by observing biological activities in the human brain. True False

True

In a neural network, inputs are the constant value given to the weighted input of each node determine the speed at which the model can arrive at the most accurate solution are variables from the dataset that move information to the next layer via connections determine the amount of adjustment made to the weights in the network

are variables from the dataset that move information to the next layer via connections

In the ________ method of linking individual observations both within and between clusters, similarity is defined by the group average of observations from one cluster to all observations from another cluster. single linkage average linkage complete linkage bell crank linkage

average linkage

According to market basket analysis, which of the following products should be placed next to each other? the newspaper, moisturizer, and bananas popcorn, magazines, and hand gloves candy, socks, and yogurt bread, beer, and salty snacks

bread, beer, and salty snacks

Based on the concept of market basket analysis, a customer who purchases bread should have immediate and easy access to ________. cake mix deodorant butter chewing gum

butter

The first step in the k-means clustering algorithm is ________. determining the initial k clusters randomly assigning and designating a cluster seed as the initial cluster centroid calculating cluster centroids (means) recalculating and reassigning cluster centroids

determining the initial k clusters

Under Armour has a health-tracking mobile application known as Record. The app collects health-related data from a variety of sources, such as manually entered user data, wearable devices, and other third-party applications. The data includes sleeping patterns, workouts, nutrition, and related information that can best be used in a neural network to develop customized digital content, such as exercise and diet recommendations for its app users classify new customers by their potential profitability when planning direct marketing strategies entice customers to visit a brick-and-mortar store predict a customer lead score

develop customized digital content, such as exercise and diet recommendations for its app users

The market basket analysis measure of lift ________. evaluates the strength of an association shows the frequency of the specific association rule indicates the percentage of times the association rule is correct determines the benchmark score of expected confidence

evaluates the strength of an association

A supermarket is trying to mimic the "Target Effect" to boost its sales. It creates a special, fast checkout line for shoppers with toddlers and babies. Which of the following products should this checkout line display prominently? formula and diapers lettuce and spinach soap and shampoo caps and gloves

formula and diapers

To explore patterns between two or more products, market basket analysis uses association rules that employ ________. if not-then yes statements but-if statements if-then statements except statements

if-then statements

A health insurance company uses Neuralmind to drive its customers to log on to its website and complete a primary health assessment and an insurance quote. This is an example of using a neural network to predict lead scoring increase new customers entice customers to a brick-and-mortar store analyze audience sentiment

increase new customers

The common adage that people use when referring to ________ data is "garbage in, garbage out." continuous and categorical large and diverse complex and interrelated invalid and unreliable

invalid and unreliable

The two most common techniques of cluster analysis discussed in the chapter are ________ and ________. k-means clustering; hierarchical clustering centroid clustering; density clustering distribution clustering; connectivity clustering schema comparisons; DAX functions

k-means clustering; hierarchical clustering

The Jaccard's coefficient approach of measuring similarity between observations measures the distance as the true straight line distance between two points measures the similarity between two observations with values that represent the minimum differences between two points makes calculations based on how dissimilar two observations are from each other is a path with right turns as if one is walking a grid in a city

makes calculations based on how dissimilar two observations are from each other

The step of creating ensemble models in the AutoML process allows us to reduce the generalization error of the prediction provide an understanding of invisible relationships and patterns extract insight from data handle missing data, outliers, variable selection, data transformation, and data standardization to maintain a common format

reduce the generalization error of the prediction

The boosting process in the creating ensemble models step in the AutoML process serves the purpose of boosting noise and bias reducing error in the model extracting new insights from data calculating the sum of predictions from multiple models

reducing error in the model

In cluster analysis, a market is segmented using ________. outlier values dissimilar characteristics shared traits distance from company headquarters

shared traits

In market basket analysis, ________ measures the frequency of the specific association rule divided by the total number of transactions. lift support confidence positivity

support

In hierarchical clustering, approaches such as ________ are most often used when numerical variables are analyzed. Jaccard's coefficient or the Euclidean distance Matching coefficient or Jaccard's coefficient the Euclidean distance or the Manhattan distance Matching coefficient or the Manhattan distance

the Euclidean distance or the Manhattan distance

In the model recommendation step of the AutoML process, original data outliers and patterns are highlighted. True False

False

Running one supervised learning model technique at a time and comparing the results with other models is a time-saving process that provides the best accuracy and prediction. True False

False

Using AutoML in marketing analytics requires extensive coding and modeling experience. True False

False

Which of the following statements is most likely to be true of a grocery store transaction? IF [soda] THEN [milk] IF [bread] THEN [tomatoes] IF [beer] THEN [butter] IF [milk] THEN [grapes]

IF [soda] THEN [milk]

End-of-aisle displays in a supermarket can increase product sales a by a maximum of 50 percent during the time that products are placed there. True False

False

In a neural network, inputs that are important in predicting the output have smaller weights, whereas the less important inputs have larger weights. True False

False

In a neural network, the hidden layer sits on top of the input and output layers. True False

False

An estimated 95 percent of supermarket product purchases are based on impulse decisions while in the store. True False

False

An advertising company uses a neural network software to determine which buyers are most likely to open their promotional emails based on past purchase behavior. Using data from 20 previous email campaigns, the neural network trains itself to examine the impact of 25 features and develop recommended solutions. The results almost doubled customers' response rates to 8.2 percent, which in turn, reduced product promotion costs by 35 percent. This example illustrates the use of neural network technology to increase new customers that often request online product quotes determine customer lifetime value and well-defined customer segments develop new products or make product and service recommendations to customers classify customers by their likely profitability when planning direct marketing strategies

classify customers by their likely profitability when planning direct marketing strategies

A marketing company uses BrainMaker to identify the customers who are most likely to click on their direct mail based on their past purchase behavior. This resulted in a 35 percent drop in advertising costs. This is an example of using a neural network to classify new customers by their likely profitability when planning direct marketing strategies innovate and design new products and categories analyze market sentiment to alter advertising approaches entice customers to visit a brick-and-mortar store

classify new customers by their likely profitability when planning direct marketing strategies

In market basket analysis, ________ measures the conditional probability of the consequent actually occurring given that the antecedent occurs. lift confidence positivity support

confidence

HealthX, a fitness products company, launched a mobile application that enables customers to obtain fitness assessments. The app analyzes customers' data to determine potential health issues and then recommends specific measures and products to address areas of concern. The digital interaction mimics an in-person transaction while allowing customers to remain in the comfort of their home. This example illustrates the use of neural network technology to personalize customer experiences predict lead scoring analyze audience sentiment to improve a product entice customers to visit a brick-and-mortar store

personalize customer experiences

The Proctor & Gamble brand Olay has a mobile application that enables customers to obtain skincare assessments. The app examines the customer's image to determine potential skin issues and then recommends specific products to address areas of concern. This is an example of using a neural network to determine the value of a potential buyer assess market sentiment personalize customer experiences predict lead scoring

personalize customer experiences

DialogTech provides neural network-driven marketing analytics solutions to manage customer inbound call centers. The collected data includes incoming caller objectives, interactions between the callers and salespersons, and assessment of conversation outcomes. This example from the text illustrates the use of neural network technology to generate personalized content categorize customers predict lead scoring build a dataset

predict lead scoring

Which of the four key steps in the AutoML process involves handling missing data, outliers, variable selection, data standardization, and data transformation to maintain a common format? preparing data creating ensemble models building models recommending models

preparing data

Identify the correct sequence of the four key steps in the AutoML process. recommending models, preparing data, building models, creating ensemble models creating ensemble models, preparing data, recommending models, building models preparing data, building models, creating ensemble models, recommending models building models, creating ensemble models, recommending models, preparing data

preparing data, building models, creating ensemble models, recommending models