Marketing Analytics Final Exam

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.

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

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."

Identify an example of sentiment opposite polarity.

"I enjoyed my coffee, but the barista was rude."

Which of the following is an example of sentiment opposite polarity?

"I woke up in a great mood today, but the hour-long commute ruined it."

Krysta, a 19-year-old university student, is shopping online and adds a geography textbook to her cart. Using this information, identify an example of a promotional message that employs user to item collaborative filtering.

"Students also bought an atlas."

A typical silhouette score ranges between ________.

+1 and -1

Which of the following is true of the supervised model of analytics?

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

In the context of activation functions, which of the statements is true?

Activation functions help the model to detect non-linear relationships.

Identify a true statement about an unsupervised model.

An unsupervised model has no target variable.

Identify a true statement about AutoML.

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

Which of the following companies spent $50 million remodeling stores and training staff according to identified consumer segments, labeled as Buzz, Jill, and Barry, to enhance in-store customer experiences, resulting in a 10 percent growth in sales?

Best Buy

Based on the concept of market basket analysis, a customer who purchases bread should have immediate and easy access to ________.

Butter

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.

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

Increase New Customers

The common adage that people use when referring to ________ data is "garbage in, garbage out."

Invalid and Unreliable

Which of the following is true of structured data?

It can be stored in a database or spreadsheet format.

Which of the following statements is true of the clustering process?

It enables marketers to identify hidden structures in data.

Identify a true statement about unstructured data.

It requires further processing before it can be used for statistical methods.

A lift value of ________ indicates a negative relationship in which two or more products in an itemset are unlikely to be purchased together.

Less than 1

The ________ approach of measuring similarity between observations is also referred to as the "City Block" distance measure.

Manhattan distance

As soon as Paula types in "The best coffee" in her search engine query box, the words "near me" and "recipe" appear as suggestions. The search engine uses the ________ technique to make such real-time recommendations possible.

N-gram

Which of the following is an example of using a neural network to create products and make service recommendations?

Netflix uses neural networks to develop insights into viewer preferences to improve production and procurement of relevant movies.

In a neural network, the output is calculated as

Output = sum (weights × inputs) + bias.

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

In the preprocessing step of text analytics, ________ is the process of removing prefixes or suffixes from words to reduce them to their root form.

Stemming

Which of the following is a difference between structured and unstructured data?

Structured data exists in predefined formats, whereas unstructured data needs to be converted before usage.

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

Support

In market basket analysis, ________ measures the number of transactions that include the items of interest divided by the total number of transactions.

Support

In market basket analysis, the measure of support is represented as ________.

Support = Number of transactions that includes both antecedent and consequent/Total number of transactions

Which of the following is true of AutoML?

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

In which of the following functions is the distance measured equivalent to the true straight line distance between two points?

The Euclidean distance

Identify a true statement regarding the divisive clustering approach of hierarchical clustering.

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 algorithms trained to recognize patterns in large volumes of data.

A neural network is constantly learning until the final optimized solution is obtained, which is when model prediction is no longer improving.

True

According to a recent survey conducted by Accenture, 40 percent of companies have adopted machine learning for improved sales and marketing performance.

True

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

True

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

True

Association rules in market basket analysis are based on the concept that an antecedent and consequent share a co-occurrent relationship.

True

AutoML, a mainly supervised approach, explores and selects models using different algorithms and compares their predictive performance.

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

Differential market basket analysis is the use of market basket analysis techniques across stores, locations, seasons, days of the week, and so forth.

True

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

True

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

True

For a specialty coffee company named Starcafe analyzing its online reviews, it is reasonable to categorize the words "Starcafe" and "coffee" as stop words.

True

K-means clustering uses the mean value for each cluster and minimizes the distance to individual observations.

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

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

True

Natural language processing is a branch of artificial intelligence used to identify patterns by reading and understanding meaning from human language.

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

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

True

Some customer segments do not adapt well to voice-guided technology—they instead prefer traditional person-to-person communications.

True

The Clorox company has applied natural language processing to analyze social media conversations about cold and flu symptoms during the COVID-19 pandemic to optimize inventory in stores.

True

The Hidden Valley company uses natural language processing to identify and seize the opportunity to develop new products.

True

The boosting process in the AutoML process achieves error reduction by observing the error records in a model and then oversampling misclassified records in the next model created.

True

To achieve the most effective models while using AutoML, analysts must understand the context of the data and ensure that it meets quality standards.

True

In a neural network, inputs

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

According to market basket analysis, which of the following products should be placed next to each other?

bread, beer, and salty snacks

The first step in the k-means clustering algorithm is ________.

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 t

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

The purpose of building models in the AutoML process is to

extract insights from data.

The two most common techniques of cluster analysis discussed in the chapter are ________ and ________.

k-means clustering; hierarchical clustering

In the preprocessing step of text analytics, the words "best" and "writing" were reduced to "good" and "write." This is an example of ________.

lemmatization

The step of creating ensemble models in the AutoML process allows us to

reduce the generalization error of the prediction.

The boosting process in the creating ensemble models step in the AutoML process serves the purpose of

reducing error in the model.

In a neural network, which of the following occurs during the process of forward propagation?

sending of data through the hidden layer where it is processed using an activation function

In which of the following methods of linking individual observations both within and between clusters is similarity defined as the shortest distance from an object in a cluster to an object from another cluster?

single linkage

Which of the following is the first step of text analytics?

text acquisition and aggregation

In hierarchical clustering, approaches such as ________ are most often used when numerical variables are analyzed.

the Euclidean distance or the Manhattan distance

In the Manhattan distance approach of measuring similarity between observations

the distance between two points is a path with right turns as if one is walking a grid in a city.

In a neural network, the learning rate consists of negative values that generally range between -1 and -10.

False

In a neural network, weights are values representing features from the dataset that pass information to the next layer via connections.

False

In text preprocessing, the term-document matrix consists of the x-axis that represents terms and the y-axis that represents the frequency of a particular term occurring.

False

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

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.

False

Structured data represents more than 75 percent of the data emerging from the internet and social media.

False

Term frequency measures the frequency of a term (or word) over all documents, whereas inverse document frequency (IDF) measures the number of times a term (or word) occurs in a document.

False

The confidence in a market basket analysis measures the frequency of the specific association rule.

False

The goal of collaborative filtering is to recommend repeat purchases of services and products to a customer.

False

The k-means clustering method can be inefficient and complex when used with large sample sizes.

False

The support measure in market basket analysis indicates the percentage of times the association rule is correct.

False

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

False

Ward's method measures the average distance between each observation in a cluster and a cluster centroid.

False

When running k-means clustering, it is best to begin with a dataset in which each variable is measured differently.

False

As per the text, which company applies natural language processing to make discoveries in social media conversations, so that it can make the best decisions about adding features such as seat heaters to its products?

Ford

Which of the following statements is most likely to be true of a grocery store transaction?

IF [soda] THEN [milk]

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

False

In market basket analysis, the measure of ________ indicates the percentage of times the association rule is correct.

Confidence

In market basket analysis, the measure of confidence is represented as ________.

Confidence = Support of transactions that includes both antecedent and consequent/Support of transactions that includes antecedent only.

According to the text, chatbots at ________ manage about 30 percent of the incoming volume, whereas the chatbots at ________ can manage almost 70 percent of customers' questions.

Dish Network; Avis

Based on the concept of market basket analysis, a customer who buys laundry detergent should have immediate and easy access to ________.

Fabric Softner

A frequency bar chart technique counts the occurrence of words in a document while ignoring the order or the grammar of words.

False

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

False

Data groups exhibit dissimilar characteristics (heterogeneity) within cluster (intra-cluster) and homogeneity or similarities between groups (inter-cluster).

False

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.

All of the four measurement approaches for determining clusters when applying hierarchical clustering can be illustrated using a ________.

dendrogram

Neural networks

often do not work well with out-of-range data.

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.

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

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

predict lead scoring.

Identify the correct sequence of the four key steps in the AutoML process.

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