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Duluth Campus

Consumer Insights and Analytics Minor

Marketing
Labovitz School of Business and Economics
  • Program Type: Undergraduate minor related to major
  • Requirements for this program are current for Spring 2024
  • Required credits in this minor: 41 to 47
LSBE's Consumer Insights and Analytics (CIA) minor will develop students' expertise in handling and analyzing consumer data in order to generate insights that facilitates a business and consumer centric decisions. CIA will train students in the tools and techniques of consumer data analysis and will provide students exposure to a variety of data used in consumer centric decision-making scenarios transactional, digital, survey (quantitative and qualitative) unstructured, and publicly available data. CIA will combine core business knowledge with analytics skills so that graduates can help companies make sense of the vast amounts of consumer data to which they have access to. The minor is open only to BA Economics and non-LSBE students. BBA and BAcc students interested in CIA must major in it. During spring semester, the application and selection process involves a thorough review of each candidate's application and academic performance, as well as a formal interview. Applicants are reviewed and the top candidates selected for the incoming cohort. Candidates are expected to bring and maintain high academic and ethical standards.
Program Delivery
This program is available:
  • via classroom (the majority of instruction is face-to-face)
Admission Requirements
Freshman and transfer students are usually admitted to pre-major status before admission to this major.
A GPA above 2.0 is preferred for the following:
  • 2.60 already admitted to the degree-granting college
  • 2.60 transferring from another University of Minnesota college
  • 2.60 transferring from outside the University
Sophomores interested in this major/minor are strongly encouraged to meet with the CIA Program Director. An initial informational meeting or review of program opportunities helps interested students determine whether or not to pursue formal application and the appropriate prerequisite courses. Applicants are reviewed and selected according to their skills, academic qualifications and "fit" with the program in terms of career goals and interests. Students with a 3.0 UM GPA and a B+ or better in both MATH 1160 (or equivalent) and ECON 2030 (or equivalent) and who have completed the LSBE Excel workshops or achieved MS Excel Certification: Fill out a simple form, automatic admission, subject to space availability. All other students: go through a full application and interview process. Contact the CIA Program Director for the details of the application process.
For information about University of Minnesota admission requirements, visit the Office of Admissions website.
Minor Requirements
Pre-Minor Core (20 - 26 cr)
Mathematics
MATH 1160 - Finite Mathematics and Introduction to Calculus [LE CAT, LOGIC & QR] (5.0 cr)
or MATH 1296 - Calculus I [LE CAT, LOGIC & QR] (5.0 cr)
Computer Science/IT
CS 1511 - Computer Science I [LE CAT] (5.0 cr)
or MIS 2201 - Information Technology in Business (3.0 cr)
Accounting
ACCT 2005 - Survey of Accounting [LE CAT] (3.0 cr)
Business
MKTG 3701 - Principles of Marketing (3.0 cr)
Statistics
ECON 2030 - Applied Statistics for Business and Economics [LOGIC & QR] (3.0 cr)
or PSY 3020 - Statistical Methods (4.0 cr)
or SOC 3155 - Quantitative Research Methods and Analysis (4.0 cr)
or STAT 1411 - Introduction to Statistics [LE CAT, LOGIC & QR] (3.0 cr)
or STAT 2411 - Statistical Methods [LE CAT, LOGIC & QR] (3.0 cr)
or STAT 3411 - Engineering Statistics (3.0 cr)
or STAT 3611 - Introduction to Probability and Statistics (4.0 cr)
Economics
ECON 1003 - Economics and Society [LE CAT, SOC SCI] (3.0 cr)
or ECON 1022 - Principles of Economics: Macro [LE CAT, SOC SCI] (3.0 cr)
ECON 1023 - Principles of Economics: Micro [LE CAT, SOC SCI] (3.0 cr)
Consumer Insights and Analytics (21 cr)
CIA 3760 - Introduction to Consumer Insights & Analytics (3.0 cr)
CIA 4797 - Consumer Analytics Internship (3.0 cr)
MIS 3220 - Database Management and Design (3.0 cr)
BA 4410 - Data Visualization (3.0 cr)
or BA 5410 - Data Visualization (3.0 cr)
MKTG 4731 - Consumer Behavior (3.0 cr)
or MKTG 5731 - Consumer Behavior (3.0 cr)
CIA 4761 - Fundamental Consumer Analytic Techniques (3.0 cr)
or CIA 5761 - Fundamental Consumer Analytic Techniques (3.0 cr)
CIA 4762 -  Advanced Consumer Analytics (3.0 cr)
or CIA 5762 - Advanced Consumer Analytics (3.0 cr)
 
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MATH 1160 - Finite Mathematics and Introduction to Calculus (LE CAT, LOGIC & QR)
Credits: 5.0 [max 5.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall, Spring & Summer
Elementary functions, matrices, graphical and algebraic methods for solving systems of linear equations and inequalities, introduction to linear programming, and abbreviated treatment of calculus with emphasis on business and social science applications. prereq: Math ACT 24 or higher or a grade of at least C- in Math 1005 or department consent; if you have received credit for 1290 or 1296 or 1596, you will not receive credit for Math 1160.
MATH 1296 - Calculus I (LE CAT, LOGIC & QR)
Credits: 5.0 [max 5.0]
Course Equivalencies: Math1290/1296/1596
Grading Basis: A-F or Aud
Typically offered: Every Fall, Spring & Summer
First part of a standard introduction to calculus of functions of a single variable. Limits, continuity, derivatives, integrals, and their applications. prereq: Math ACT 27 or higher or a grade of at least C- in Math 1250 or department consent
CS 1511 - Computer Science I (LE CAT)
Credits: 5.0 [max 5.0]
Course Equivalencies: CS 1511/1581
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
A comprehensive introduction to computer programming using the C++ language. The course covers program design, C++ programming basics, control structures, functions and parameter passing. Students write and implement programs with data structures (arrays), pointers and files. Object-oriented programming is also introduced, along with concepts of abstraction, ADTs, encapsulation and data hiding. prereq: 3 1/2 yrs high school math or instructor consent
MIS 2201 - Information Technology in Business
Credits: 3.0 [max 3.0]
Course Equivalencies: FMIS 2201/1201/3201/CS 1011
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Introduction to information technology (IT) concepts: computer hardware and software; use of personal productivity tools (spreadsheet, database, and presentation software); system development processes; Web technologies; applications of IT in business processes. prereq: LSBE major or minor student or Graphic Design and Marketing major or Graphic Design with Marketing subplan major or Computer Information Systems majors or minors, or Arts Administration, minimum 15 credits or college consent; credit will not be granted if already received for FMIS 2201
ACCT 2005 - Survey of Accounting (LE CAT)
Credits: 3.0 [max 3.0]
Grading Basis: A-F only
Typically offered: Every Fall
Survey of Accounting provides an overview of fundamental concepts and procedures in financial and managerial accounting. The emphasis is on helping students to develop a basic understanding of the contexts of accounting reports provided to decision makers. Credit cannot be applied toward the BAcc or BBA degree programs or the Accounting minor.
MKTG 3701 - Principles of Marketing
Credits: 3.0 [max 3.0]
Grading Basis: A-F only
Typically offered: Every Fall, Spring & Summer
Marketing as a process of exchange management. Emphasis on conceptual tools necessary to deal with both strategic marketing management issues and tactical management of product, price, promotion, and distribution. prereq: LSBE candidate or non-LSBE Marketing minor or approved non-LSBE business administration minor or college consent
ECON 2030 - Applied Statistics for Business and Economics (LOGIC & QR)
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall, Spring & Summer
Introduction to modern business statistics, emphasizing problem solving applications through statistical decision making using case studies. Topics include organization and presentation of data, summary statistics, distributions, statistical inference including estimation, and hypothesis testing. prereq: minimum 30 credits, LSBE student, pre-business or pre-accounting or Econ BA major or Graphic Design and Marketing major or Graphic Design with Marketing subplan major or Econ minor or Accounting minor or Business Admin minor or Arts Administration; credit will not be granted if already received for Econ 2020, Stat 1411, Stat 2411, Stat 3611, Soc 3151, Psy 3020
PSY 3020 - Statistical Methods
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall, Spring & Summer
Descriptive statistics; introduction to correlational analysis and regression; sampling techniques and statistical inference; applications of simple and factorial design analysis of variance and other parametric and nonparametric hypothesis-test statistics in the behavioral sciences. prereq: Math ACT 21 or higher or Accuplacer score of 237-300 or higher or MATH 1005
SOC 3155 - Quantitative Research Methods and Analysis
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Descriptive statistics. Measures of central tendency, deviation, association. Inferential statistics focusing on probability and hypothesis testing. T-tests, Chi-square tests, analysis of variance, measures of association, introduction to statistical control. Statistical software (SPSS) used to analyze sociological data. Lab. prereq: 2155, crim major or soc major or URS major, min 30 cr
STAT 1411 - Introduction to Statistics (LE CAT, LOGIC & QR)
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Statistical ideas involved in gathering, describing, and analyzing observational and experimental data. Experimental design, descriptive statistics, correlation and regression, probabilistic models, sampling, and statistical inference. prereq: Math ACT 21 or higher or a grade of at least C- in MATH 0103 or department approval
STAT 2411 - Statistical Methods (LE CAT, LOGIC & QR)
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Graphical and numerical descriptions of data, elementary probability, sampling distributions, estimations, confidence intervals, one-sample and two-sample t-test. prereq: Math ACT 24 or higher or a grade of at least C- in Math 1005 or higher or department approval
STAT 3411 - Engineering Statistics
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Statistical considerations in data collection and experimentation. Descriptive statistics, least squares, elementary probability distributions, confidence intervals, significance tests, and analysis of variance as applied analysis of engineering data. prereq: MATH 1297 with a grade of C- or better, cannot be applied to a math or statistics major
STAT 3611 - Introduction to Probability and Statistics
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall, Spring & Summer
Basic probability, including combinatorial methods, random variables, mathematical expectation. Binomial, normal, and other standard distributions. Moment-generating functions. Basic statistics, including descriptive statistics and sampling distributions. Estimation and statistical hypothesis testing. prereq: A grade of at least C- in Math 1290 or Math 1296
ECON 1003 - Economics and Society (LE CAT, SOC SCI)
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Periodic Spring
General description of U.S. economy and analysis of contemporary economic problems. Introduction to major economic issues and problems of the day, providing a simple framework used by economists for analysis. prereq: Cannot apply credit to economics major or minor or BAc or BBA majors
ECON 1022 - Principles of Economics: Macro (LE CAT, SOC SCI)
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Analyzing overall performance of an economic system. National income accounting and theory, unemployment, inflation, fiscal policy, money, monetary policy, economic growth, international trade, non-U.S. economies, and real-world application of these concepts. prereq: Minimum 15 credits or department consent
ECON 1023 - Principles of Economics: Micro (LE CAT, SOC SCI)
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Analyzing free enterprise system through study of product and resource markets. Supply and demand, utility, production and cost, market structure, resource use, market failures, regulatory role of government, and real-world application of these concepts. prereq: Minimum 15 credits or department consent
CIA 3760 - Introduction to Consumer Insights & Analytics
Credits: 3.0 [max 3.0]
Course Equivalencies: CIA 3760/MKTG 4763
Grading Basis: A-F or Aud
Typically offered: Every Fall
Course provides students the theoretical framework of analytical process and thinking. This course also equips students with the key concepts and methods of marketing research and allow student to understand how to apply those tools to solve real-life business and consumer-centric problems. The course introduces students to data gathering approaches, performing data cleaning and quality checks, creating analytical metrics from the data, identifying anomalies and outliers in the data, mine insights from metrics and finally synthesize insights into a coherent story for business ation. Students will apply the course learning using Excel, Tableau and SAS. pre-req: CIA major or minor
CIA 4797 - Consumer Analytics Internship
Credits: 3.0 [max 6.0]
Course Equivalencies: CIA 3767/MKTG 3767
Grading Basis: A-F or Aud
Typically offered: Every Fall, Spring & Summer
The internship provides students with an opportunity to work as a member of an analytics team for a minimum of 200 hours. During the internship, students have the opportunity to apply their analytic knowledge and skills in a chosen business or industry sector. At the end of the course, students are expected to meet face-to-face with instructor to discuss and submit a presentation on the internship experience. pre-req: CIA major or minor, CIA 3760, at least one of the following courses: CIA 4761, MIS 3220, MKTG 4731 or 5731
MIS 3220 - Database Management and Design
Credits: 3.0 [max 3.0]
Grading Basis: A-F only
Typically offered: Every Fall & Spring
Concepts and structures relating to design, implementation, and administration of database management systems. Emphasis on relational databases and development of integrated applications. prereq: FMIS 2201 or MIS 2201 or CS 1121 or CS 1511, LSBE candidate or non-LSBE MIS minor or college consent; credit will not be granted if already received for FMIS 3220
BA 4410 - Data Visualization
Credits: 3.0 [max 3.0]
Course Equivalencies: BA 4410/MIS 3231
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Data visualization is the art and science of presenting data effectively in order to facilitate knowledge sharing and decision making. How to present and visualize data is an important skill for business professions to develop. This course will teach the principles and techniques that empower students to understand and interpret data, as well as make effective decisions based on data. Students will learn the benefits of effective data presentation and visualization, understand the principles and methods of visualization, and apply the principles using popular data visualization technologies. pre-req: FMIS 2201 or MIS 2201, LSBE candidate or Business Analytics minor, no grad credit, credit will not be granted if already received for MIS 3231
BA 5410 - Data Visualization
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Data visualization is the art and science of presenting data effectively in order to facilitate knowledge sharing and decision making. How to present and visualize data is an important skill for business professions to develop. This course will teach the principles and techniques that empower students to understand and interpret data, as well as make effective decisions based on data. Students will learn the benefits of effective data presentation and visualization, understand the principles and methods of visualization, and apply the principles using popular data visualization technologies. Students enrolled in the 5410 version of the course will have to fulfill an extra assignment/project to earn graduate credit. pre-req: FMIS 2201 or MIS 2201, LSBE candidate or Business Analytics minor, credit will not be granted if already received for MIS 3231
MKTG 4731 - Consumer Behavior
Credits: 3.0 [max 3.0]
Grading Basis: A-F only
Typically offered: Every Fall & Spring
Buyer behavior and implications for marketing strategy. Emphasis on information processing concepts, influences on behavior, and decision-making processes from both conceptual and pragmatic perspectives. Students requiring graduate credit must complete additional coursework. prereq: MgtS 3701 or Mktg 3701, LSBE candidate or Graphic Design and Marketing majors or Graphic Design with Marketing sub plan major or non-LSBE Marketing Minor or college consent
MKTG 5731 - Consumer Behavior
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Buyer behavior and implications for marketing strategy. Emphasis on information processing concepts, influences on behavior, and decision-making processes from both conceptual and pragmatic perspectives. Students requiring graduate credit must complete additional coursework. pre-req: MKTG 3701, MBA student or department consent
CIA 4761 - Fundamental Consumer Analytic Techniques
Credits: 3.0 [max 3.0]
Course Equivalencies: CIA 4761/MKTG 3761
Grading Basis: A-F or Aud
Typically offered: Every Spring
Course develops core quantitative skills necessary to convert large amounts of consumer data into actionable information for businesses. The course builds knowledge and understanding of the essential business and consumer metrics as well as the statistical techniques necessary fro students to be able to competently summarize data, appropriately classify data and use daa to make predictions. Marketing research is a constantly evolving field, In this course, we explore some of the current development and new application areas of marketing research. Emphasis is placed on the application of skills and techniques to data sets and using the analysis to answer business questions and formulate consumer focused recommendations. pre-req: CIA major or minor, CIA 3760, no grad credit
CIA 5761 - Fundamental Consumer Analytic Techniques
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Course develops core quantitative skills necessary to convert large amounts of consumer data into actionable information for businesses. The course builds knowledge and understanding of the essential business and consumer metrics as well as the statistical techniques necessary fro students to be able to competently summarize data, appropriately classify data and use data to make predictions. Marketing research is a constantly evolving field, In this course, we explore some of the current development and new application areas of marketing research. Emphasis is placed on the application of skills and techniques to data sets and using the analysis to answer business questions and formulate consumer focused recommendations. Students enrolled in the 5761 version of the course will have to fulfill an extra assignment/project to earn graduate credit. pre-req: CIA 3760, MBA student or department consent
CIA 4762 - Advanced Consumer Analytics
Credits: 3.0 [max 3.0]
Course Equivalencies: CIA 4762/MKTG 4762
Grading Basis: A-F or Aud
Typically offered: Every Fall
Course introduces customer relationship management and advanced analytical techniques. Emphasis is placed on understanding and calculating the metrics behind profit enhancing customer level management, including RFM Analysis, attrition and churn prediction, customer value and profitability, and customer lifetime value. Students will be asked to calculate these metrics during classroom scenarios and assigned case studies to gain an understanding of how these metrics can be used to select, retain and grow profitable customer segments. Having mastered the basic concepts and tools of marketing research, we move on to study three more advanced and specialized tools most commonly used by qualitative marketing researchers. We study the application of these techniques to optimize the marketing mix (pricing, promotion, product design, positioning). pre-req: CIA 4761 or 5761; no grad credit
CIA 5762 - Advanced Consumer Analytics
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall
Course introduces customer relationship management and advanced analytical techniques. Emphasis is placed on understanding and calculating the metrics behind profit enhancing customer level management, including RF< Analysis, attrition and churn prediction, customer value and profitability, and customer lifetime value. Students will be asked to calculate these metrics during classroom scenarios and assigned case studies to gain an understanding of how these metrics can be used to select, retina and grow profitable customer segments. Having mastered the basic concepts and tools of marketing research, we move on to study three more advanced and specialized tools most commonly used by qualitative marketing researchers. We study the application of these techniques to optimize the marketing mix (priding, promotion, product design, positioning). Students enrolled in the 5762 version of the course will have to fulfill an extra assignment/project to earn graduate credit. pre-req: CIA 4761 or 5761, credit will not be granted if already received for MKTG 4762