Midterm Review

Question 1

Marketing research

Answer 1

a process used by businesses to collect, analyze, and interpret information used to make sound business decisions

• advertising effectiveness
• A/B, copy testing
• concept testing
• brand attitude
• satisfaction

Question 2

Market research

Answer 2

a process used to define the size, location, and trends of the market for a product or service
- market size
- market trends
- market segmentation
- target market
- technical research

Question 3

Relationship between marketing research & market research

Answer 3

• competition
• pricing
• product attributes
• demand estimation

Question 4

Effective marketing decisions are based on

Answer 4

• theory
• experience
• research
• intuition

Question 5

Uses of marketing research

Answer 5

1. identify marketing opportunities and problems
2. generate, refine, and evaluate potential marketing actions
3. monitor marketing performance
4. improve marketing as a process

Question 6

1. Identify marketing opportunities and problems

Answer 6

• market demand determination
• market segment identification
• marketing audits SWOT analysis

Question 7

2. Generate, refine, and evaluate potential marketing actions

Answer 7

• selecting target markets
• product research
• pricing research
• promotion research
• distribution research

Question 8

3. Monitor marketing performance

Answer 8

Market Information System (MIS): a structure consisting of people, equipment, and procedures to gather, sort, analyze, evaluate, and distribute accurate information to marketing decision makers in a timely manner

• internal reports system
• marketing intelligence system
• marketing decision support system (DSS)
• marketing research system

Question 9

4. Improve marketing as a process

Answer 9

Basic Research: conducted to gather information and expand our knowledge

Applied Research: conducted to solve specific problems

Question 10

Research Process

Answer 10

1. establish the need for marketing research
2. the importance of properly defining the problem/opportunity
3. establishing research objectives
4. determine research design
5. identifying data types and sources
6. determining methods of accessing data
7. design data collection forms
8. determine sample plan and size
9. collect data
10. analyze data
11. prepare and present the final research report

Question 11

1. Establish the need for marketing research

Answer 11

Is there a real need for marketing research?
- Marketing research is not always needed
- The information is often readily available
- Timing is important

Value of information versus cost of information?
- Research takes time and costs money.
- Funds are not available for marketing research
- Costs outweigh the value of marketing research

Question 12

2. The importance of properly defining the problem/opportunity

Answer 12

Most important step
- If the problem/opportunity is incorrectly defined, all the remaining steps are wrong and wasted effort

Question 13

Role of Symptoms in Problem Recognition

Answer 13

Symptoms
-are not the problem, but are the “signals” that alert us to the problem
- managers often decide too fast on identifying the problem

Question 14

Consequences of the alternatives

Answer 14

1. consequences
   
   • the results of marketing decisions
2. assumptions
   
   • assertions that certain conditions exist or that certain reactions will take place if the considered alternatives are implemented
3. information state
   
   • the quantity and quality of evidence a manager possesses for each of his or her assumptions
4. information gaps
   
   • discrepancies between the current information level and the desired level of information

Question 15

Role of Hypotheses in Problem Recognition

Answer 15

something that you ​accept as ​true or suppose to be true and test via research and experiments
- assumptions are hypotheses

Question 16

3. Establising Research Objectives

Answer 16

No universally accepted, step-by-step approach used by marketing researchers to define the problem and establish research objectives

Research Objectives: specific and tells the researcher exactly what information must be collected to solve the problem by facilitating selection of an alternative

Question 17

What construct do we wish to measure?

Answer 17

Construct: an abstract idea inferred from specific instances that are thought to be related
- intention to buy
- satisfaction
- brand loyalty
- preference
- awareness
- knowledge

Question 18

4. Determine research design

Answer 18

1. Exploratory research
2. Descriptive Research
3. Causal studies

Question 19

5. Identifying data types and sources

Answer 19

Primary data: information that is developed or gathered by the researcher for the research project at hand

Secondary data: information that has previously been gathered by another researcher for some other purpose than the research project at hand

Question 20

6. Determining methods of accessing data

Answer 20

• Primary data is more complex to access
• Secondary data is relatively easy

Forms of accessing data:
- online surveys (most popular)
- telephone
- mail delivery
- face-to-face interviews

Question 21

7. Design data collection forms

Answer 21

Questionnaire/Survey:
- clear and objective to avoid bias responses

Observation Form:
- observing respondents

Question 22

8. Determine sample plan and size

Answer 22

Sample Plan: describes how each sample element, or unit, is to be drawn from the total population
- Gives you representativeness!

Sample Size: determining how many individuals in the population should be included in the sample
- Gives you accuracy!

Question 23

9. Collect data

Answer 23

Non-sampling Errors:
- are always present in data collection
- researchers must know the sources of these errors and implement controls to minimize them (validations)

Field Service Firms: companies that specialize in data collection

Question 24

10. Analyze data

Answer 24

SPSS:
- involves entering data into computer files
- inspecting data for errors
- running tabulations and various statistical tests

Question 25

11. Prepare and present the final research report

Answer 25

Reporting:
- one of the most important phases
- report or presentation that properly communicates the results to the client

Question 26

Research design

Answer 26

A set of advance decisions that make up the master plan specifying and deciding one or more methods for collecting and analyzing the needed information

Question 27

Objectives of research design

Answer 27

• to gain background information and to develop hypotheses
• to measure the state of a variable of interest
• to test hypotheses that specify the relationships between two or more variables

Question 28

Types of research design

Answer 28

1. exploratory
2. descriptive
3. causal

Question 29

1. Types of research design: exploratory research

Answer 29

Conducted at the outset of research projects and when the researcher does not know much about the problems

Methods:
1. Secondary data analysis
2. Experience surveys
3. Case analysis
4. Focus groups

Question 30

1. Exploratory research: secondary data analysis

Answer 30

the process of searching and interpreting existing information relevant to the research topic

Question 31

2. Exploratory research: experience surveys

Answer 31

Key-informant technique: gathering information from experts on the issues relevant to the research problem

Lead-user survey: used to acquire information from lead users of a new technology

Question 32

3. Exploratory research: case analysis

Answer 32

a review of available information about a former situation that has some similarities to the current research problem

Question 33

4. Exploratory research: focus groups

Answer 33

small groups brought together and guided by a moderator through an unstructured, spontaneous discussion for the purpose of gaining information relevant to the research problem

Question 34

2. Types of research design: descriptive research

Answer 34

A set of methods and procedures describing marketing variables
- Diagnostic research: designed to determine sources of satisfaction and dissatisfaction
- Prescriptive research: provides information that best treats the dissatisfaction

If the sample is representative, then the findings can be projected to a larger population (describe and measure marketing phenomena at a point in time)

Classifications
- Cross-sectional studies
- Longitudinal studies

Studies
- Continuous panels
- Discontinuous panels

Question 35

1. Descriptive research: continuous panels

Answer 35

Ask panel members the same questions on each panel measurement

• Brand-switching studies: studies examining how many consumers switched brands
• Market-tracking studies: those that measure some variables of interest over time (market share or unit sales)

Question 36

1. Descriptive research: discontinuous panels

Answer 36

vary questions from one panel measurement to the next (omnibus panels - including many things)

Question 37

3. Types of research design: causal research

Answer 37

Causality may be thought of as understanding a phenomenon in terms of conditional statements of the form “If x, then y.”
- attempt to uncover what factors cause something to occur

Causal relationships are often determined by the use of experiments

Question 38

Independent variables

Answer 38

variables that the researcher has control over and wishes to manipulate (4 P’s)
- level of ad expenditure
- type of ad appeal
- display location
- method of compensating salespersons
- price
- type of product

Question 39

Dependent variables

Answer 39

variables that we have little or no direct control over but a strong interest in changing
- return on investment (ROI)
- net profits
- market share
- customer satisfaction

Question 40

Extraneous variables

Answer 40

variables that may have some effect on a dependent variable yet are not independent variables (must be controlled through proper experimental design)
- larger landscape issues
- weather
- personal issues for study participant

Question 41

Types of experimental design

Answer 41

1. “True” experimental design
2. Quasi-experimental design
3. Pretest-posttest control group design

Question 42

1. Types of experimental design: “true” experimental design

Answer 42

Isolates the effects of the independent variable on the dependent variable while controlling for the effects of any extraneous variables
- Field experiments: those in which the independent variables are manipulated and the measurements of the dependent variable are made on test units in their natural setting

Question 43

2. Types of experimental design: quasi-experimental design

Answer 43

Ones that do not properly control for the effects of extraneous variables on our dependent variable

Question 44

3. Types of experimental design: pretest-posttest control group design

Answer 44

May be achieved by randomly dividing subjects of the experiment in two groups:
- Control group: control of extraneous variables typically achieved by the use of a second group of subjects
- Experimental group: the group that has been exposed to a change in the independent variable

Question 45

Validity in experiments

Answer 45

Internal validity: examines whether the study design, conduct, and analysis answer the research questions without bias

External validity: examines whether the study findings can be generalized to other contexts

Question 46

Test marketing

Answer 46

Commonly used to indicate an experiment, study, or test that is conducted in a field setting

Main uses of test markets:
- To test sales potential for a new product or service
- To test variations in the marketing mix for a product or service

Four types
- Standard test market
- Controlled test market
- Electronic test market
- Simulated test market

Question 47

Selecting test-market cities

Answer 47

Three main criteria:
- Representativeness
- Degree of isolation
- Ability to control distribution and promotion

Question 48

Secondary data: internal databases

Answer 48

Data mining: software that helps managers make sense out of seemingly senseless masses of information contained in databases

Micro-marketing: using a differentiated marketing mix for specific customer segments, sometimes fine-tuned for the individual shopper

Question 49

Secondary data: external databases

Answer 49

Databases supplied by organizations outside the firm:
- Published
- Syndicated services data
- Databases

Question 50

Advantages & disadvantages of secondary data

Answer 50

Advantages:
- Obtained quickly
- Inexpensive
- Usually available
- Enhances existing primary data
- May achieve research objective

Disadvantages:
- Data is outdated
- Incompatible reporting units (zip code data and county data are not the same)
- Measurement units do not match (per capita income and household income are not the same)
- Class definitions are not usable (percent of population with income above $100k and of $50k and over is not the same - info doesn’t range high or low enough)

Question 51

Secondary data: packaged information

Answer 51

The data collected and the process of collecting the data are prepackaged for all users

Two broad classes of packaged information:
- Syndicated data: collected in a standard format and made available to all subscribers
- Packaged services: the data will differ for each client

Question 52

Big Data

Answer 52

Simply the act of gathering and storing large amounts of information for analysis (new term, old idea)

Question 53

Three main characteristics of big data

Answer 53

Volume: Organizations collect data from
- business transactions
- social media
- info from sensor/machine-to-machine data

Velocity: Data streams in at an unprecedented speed and must be dealt with in a timely manner
- RFID (radio-frequency identification) tags
- sensors and smart metering in near-real time

Variety: Data comes in all types of formats from
- structured numeric data in traditional databases
- unstructured text docs, email, video, audio, stock ticker data, financial transactions

Question 54

How do we gather big data?

Answer 54

Growing by levels of magnitude as technology grows, but currently Big Data is compiled through the following methods:
- recorded and manually inputted by companies
- collected autonomously by computers through companies, internet, etc.
- individual posts and shares via social media, apps, blogs, search history, online shopping, etc

Question 55

Why is big data important?

Answer 55

The importance of big data doesn’t revolve around how much data you have, but what you do with it
- Building a 360 degree view of the customer
- Determining root causes of failures, issues and defects in near-real time
- Generating coupons at the point of sale based on the customer’s buying habits
- Recalculating entire risk portfolios in minutes
- Detecting fraudulent behavior before it affects your organization

Question 56

CRM - Customer Relationship Management

Answer 56

Practices, strategies and technologies that companies use to manage and analyze customer interactions and data throughout the customer lifecycle with the goal of improving business relationships with customers

Designed to compile information on customers across different channels
- company’s website
- telephone
- live chat
- direct mail
- marketing materials
- social media

Give staffs detailed information on customers’
- personal information
- purchase history
- buying preferences
- concerns

Question 57

Types of CRM

Answer 57

1. Operational CRM
2. Analytical CRM
3. Collaborative CRM

Question 58

1. Operational CRM

Answer 58

Integrate and automate sales, marketing and customer support
- sales force automation
- marketing automation
- service automation

Question 59

2. Analytical CRM

Answer 59

Analyze customer data collected through multiple systems and present it to make informed decisions
- data mining
- correlation
- pattern recognition

Question 60

3. Collaborative CRM

Answer 60

Incorporate external stakeholders (vendors & distributors) to share info across organizations
- Real life example: outsourced tech support and customer service support are integrated within the company so that marketing, sales and operations can react to tech issues and customer service

Question 61

Advantages of CRM

Answer 61

• Improve customer services
• Improve customization of marketing
• Increased personalized service
• Responsive to customer needs
• Customer segmentation
• Multichannel integration
• Time saving

Question 62

Social media analytics

Answer 62

Process of gathering data from stakeholder conversations on digital media and processing into structured insights leading to more information-driven business decisions and increased customer centrality for brands and businesses
- social media listening
- social media monitoring
- social media intelligence

Question 63

Digital media sources for social media analytics

Answer 63

• social media channels
• blogs, wikis, other similar sites
• forums
• image and video sharing sites
• aggregators
• classifieds
• comments, complaints, Q&A, & reviews

Question 64

What is included in social media analytics?

Answer 64

• Textual data (tweets, comments)
• Network data (followers, networks)
• Actions (likes, shares, views)
• Hyperlinks (embedded within text)
• Mobile data (mobile application data)
• Location data
• Search engines data

Some are visible or easily identifiable (text and actions) and other are invisible (social media and hyperlink networks)

Question 65

The social media analytics compass

Answer 65

Contains the most essential areas that you need to monitor for your social media channels
- audience profile
- audience size
- content analysis
- sentiment analysis
- competitive benchmarking
- community responsiveness
- reach and engagement
- traffic

Not possible to monitor everything across every channel due to limitations of tools
- not essential to monitor everything depending on the business

Question 66

In-built social media analytics tools

Answer 66

Pros:
- FREE, available to all. Good place to start
Cons:
- functionality is more restrictive
- harder to combine data with multiple platforms for an overall picture of social media analytics

Examples
- Facebook insights
- Instagram insights
- Pinterest analytics
- Twitter analytics
- Youtube analytics
- Google alerts
- Google analytics

Question 67

Specialized social media analytic tools

Answer 67

Pros:
- gathers social media analytics into one central main hub
- make insights based on ‘the big picture’

Cons:
- can be pricy, vary in cost depending upon the size and features of the tool you choose

Examples:
- buzzsumo
- hoosuite
- brandwatch
- crowdbooster
- klout

Question 68

Types of statistical analyses used in marketing research

Answer 68

1. Descriptive analysis
2. Inferential analysis
3. Differences analysis
4. Associative analysis
5. Predictive analysis

Question 69

1. Statistical Analyses: Descriptive analysis

Answer 69

Summarizes basic findings
- describes the typical respondent
- describes how similar respondents are to the typical respondent

Statistical concepts:
- mean, median, mode, frequency distribution, range, standard deviation

Question 70

2. Statistical Analyses: Inferential analysis

Answer 70

Determines population parameters, tests hypothesis and estimates population values

Statistical concepts
- standard error, null hypothesis

Question 71

3. Statistical Analyses: Differences analysis

Answer 71

Determines if differences exist, evaluates statistical significance of difference in the means of two groups in a sample

Statistical concepts:
- t test of differences, analysis of variance

Question 72

4. Statistical Analyses: Associative analysis

Answer 72

Determines if two variables are related in a systematic way

Statistical concepts:
- correlation, cross-tabulation

Question 73

5. Statistical Analyses: Predictive analysis

Answer 73

Finds complex relationships for variables in the dataset
- determines how several independent variables influence a key dependent variable

Statistical concepts:
- multiple regressions

Question 74

Types of Measurements

Answer 74

1. Measures of central tendency
2. Measures of variability

Question 75

1. Measurements: measures of central tendency

Answer 75

Central tendency applies to any statistical measure used that somehow reflects a typical or frequent response

Measures of central tendency:
- Mean: the average of all numbers
- Median: middle number in a sorted list
- Mode: the most frequent number

Question 76

2. Measurements: measures of variability

Answer 76

Concerned with depicting the “typical” difference between the values in a set of values

Measures of variability:
- Frequency distribution: the number (%) of occurrences in each category
- Range: max and min values in sorted list
- Standard deviation: the degree of variation in the sample, assuming a bell-shaped curve distribution
- Empirical Rule or 68-95-99.7%

Question 77

Statistical inference

Answer 77

A set of procedures in which the sample size and sample statistic are used to make an estimate of the corresponding population parameter

Statistics: values that are computed from a sample
- mean or percentage
- standard error
- confidence interval: degree of accuracy

Parameters: values that are computed from the complete census or population (precise and valid measures)

Question 78

Types of statistical inference

Answer 78

1. Population parameter estimation
2. Hypothesis testing

Question 79

1. Statistical inference: population parameter estimation

Answer 79

• used to approximate the population value through the use of confidence intervals
• the lower the standard error, the more precise our sample statistic will estimate the population parameter
• researchers can increase the sample size to minimize standard error

Question 80

2. Statistical inference: hypothesis testing

Answer 80

• used to compare the sample statistic with what is believed to be the population value prior to undertaking the study
• null hypothesis and the alternative hypothesis

Question 81

Example question: What is your gender?

Answer 81

Measurement Level: nominal scale (qualitative - categorical)

Central Tendency: mode

Variability: frequency, percentage distribution, range

Question 82

Example question: Rank these five brands from your first choice to your fifth choice

Answer 82

Measurement Level: ordinal scale (qualitative -categorical)

Central Tendency: median or mode

Variability: frequency distribution, range, IQR range

Question 83

Example question: On a scale of 1 to 5, how does Starbucks rate on variety of its coffee drinks?

Answer 83

Measurement Level: interval scale (quantitative - continuous)

Central Tendency: mean, median, or mode

Variability: standard deviation, range, or variance

Question 84

Example question: About how many times did you buy fast food for lunch last week?

Answer 84

Measurement Level: ratio scale (quantitative- continuous)

Central Tendency: mean, median, or mode

Variability: standard deviation, range, or variance

Question 85

Example question:
As part of the Target survey, they also asked respondents to indicate their type of profession.

Percentage Analysis Results:

Profession Type
- Administrative Staff (Frequency - 25 / Percent - 5%)
- Business Owner/Entrepreneurs (Frequency - 25 / Percent - 5%)
- Customer Service/Retail (Frequency - 15 / Percent - 3%)
- Home Maker/ Non-working (Frequency - 10 / Percent - 2%)
- Professional (Frequency - 200 / Percent - 40%)
- Retired (Frequency - 75 / Percent - 15%)
- Student (Frequency - 100 / Percent - 20%)
- Trades worker (plumber, etc.) (Frequency - 50 / Percent - 10%)
- Total (Frequency - 500 / Percent - 100%)

Answer 85

a. What is the level of measurement?
- categorical, specifically nominal, as it involves different categories of professions without any inherent order

b. What is the appropriate indicator of central tendency?
- mode, which represents the most frequently occurring category. In this case, the mode would be the profession type with the highest frequency, which is “Home Maker/Non-working” with a frequency of 200.

c. What is the appropriate indicator of variability?
- Since the data is categorical, the appropriate indicator of variability would be the range, which shows the difference between the highest and lowest frequencies

d. Is this measure high or low in terms of variability? Explain your answer.
- The measure of variability appears to be high because there is a considerable difference between the highest frequency (200) and the lowest frequency (10). This indicates a wide spread of responses across the different profession types

e. Of course, this is one single variable, and an effective strategy would consider ALL variables in the decision-making process. But, for the purposes of the test, assume you are part of the Target Marketing team deciding about this location. How would you use this data from marketing strategy standpoint? Explain your answer.

From a marketing strategy standpoint, understanding the distribution of professions among the respondents can help Target tailor its marketing efforts more effectively. For instance:

• Since “Home Maker/Non-working” individuals represent the highest proportion, Target may consider promoting products or services that cater to this demographic, such as home goods, cooking appliances, or children’s products.
• The significant presence of “Professional” respondents suggests a potential market for business attire, office supplies, or professional services.
• Target may also analyze the overlap between professions and other demographic information, such as age or income level, to further refine their marketing strategies.
• Additionally, Target could use this data to identify potential gaps in their current product offerings or services and develop targeted marketing campaigns to attract customers from underrepresented professions.
  Overall, leveraging this data can help Target better understand its customer base and tailor its marketing efforts to meet the diverse needs and preferences of different professional groups.

Question 86

Example question: The Aloha Food Truck conducted a survey of 500 adults in the West Oahu area. One of their survey questions asks respondents to indicate the type of housing in which they live. Here is the data from that survey question.
Percentages Analysis Results

Dwelling type:

Category

• Single family homeowner
  150
  30%
• Condo owner
  250
  50%
• Apartment/condo renter
  90
  18%
• Home renter
  10
  2%
• Total
  500
  100.0%

Answer 86

a. What is the level of measurement?
- categorical, specifically nominal, as it involves different categories of dwelling types without any inherent order

b. What is the appropriate indicator of central tendency?
- mode, which represents the most frequently occurring category. In this case, the mode would be the dwelling type with the highest frequency, which is “Condo owner” with a frequency of 250.

c. What is the appropriate indicator of variability?
- Since the data is categorical, the appropriate indicator of variability would be the range, which shows the difference between the highest and lowest frequencies.

d. Is this measure high or low in terms of variability? Explain your answer.
- The measure of variability appears to be relatively low because there is not a significant difference between the highest frequency (250) and the lowest frequency (10). This indicates that the responses are relatively concentrated around the two most common dwelling types, “Condo owner” and “Single family homeowner”.

e. Of course, this is one single variable, and an effective strategy would consider ALL variables
in the decision-making process.

From a business standpoint, understanding the distribution of dwelling types among the survey respondents can help the Aloha Food Truck tailor its marketing efforts and offerings accordingly:

• Given that “Condo owner” is the most common dwelling type, the Aloha Food Truck may consider targeting areas with a high concentration of condominium complexes for marketing and promotional activities.
• They may also consider offering catering services or special promotions tailored to condominium communities, such as lunch delivery to condo complexes or discounts for residents.
• However, they should not neglect the other dwelling types entirely. For instance, although “Single family homeowners” have a lower frequency in this survey, they still represent a significant portion of the population and may have different preferences or needs that the Aloha Food Truck could address with targeted marketing strategies.
• Additionally, understanding the distribution of dwelling types can inform decisions about where to locate the food truck for maximum visibility and foot traffic, such as near areas with a high concentration of condos or apartment complexes.
  Overall, leveraging this data can help the Aloha Food Truck tailor its marketing and operational strategies to better meet the needs and preferences of the local community in the West Oahu area.

This data from the Aloha Food Truck’s survey provides insights into the housing types of residents in the West Oahu area. Understanding the distribution of housing types can be valuable for several reasons:

Targeted Marketing: Knowing the predominant housing types in the area allows the food truck to tailor its marketing efforts accordingly. For example, if there is a high percentage of condo owners, the food truck might consider promoting its services in condo complexes or areas with a high concentration of condominiums.

Menu Planning: Different housing types may indicate varying lifestyles and dietary preferences. For instance, single-family homeowners might be more interested in family-friendly meals, while apartment/condo renters might prefer quick and convenient options. Understanding the demographics of the housing types can help the food truck adjust its menu offerings to better appeal to its target audience.

Location Selection: The distribution of housing types can also influence the food truck’s choice of locations for parking and serving. For instance, if there is a high concentration of apartment/condo renters in a particular area, the food truck might prioritize setting up in locations that are easily accessible to this demographic.

Business Strategy: Knowledge of the housing types can inform broader business strategies, such as pricing, promotions, and partnerships. For example, the food truck might offer discounts or special deals targeted at specific housing types to attract more customers.

However, it’s essential to recognize that relying solely on housing type data may not provide a comprehensive understanding of the target market. Other factors such as age, income level, cultural background, and lifestyle preferences also play crucial roles in shaping consumer behavior and preferences.

Overall, understanding housing types can provide valuable insights into the demographics and preferences of the target market, enabling the food truck to better tailor its offerings and marketing strategies to meet the needs of its customers effectively.

Question 87

Example question:
Foodland is trying to better understand their customers. They hire a research firm to ask 300 adult respondents to rate how many times they have been to a Foodland supermarket in the past month. Here is a summary of what the respondents report:

• mean number of times shopped in a supermarket in the past month: 6
• median number of times shopped in a supermarket restaurant in the past month: 6
• modal number of times shopped in a supermarket in the past month: 4
• standard deviation of mean number of time shopped in a supermarket in the past month: 2.33
• range: 8 (2-10)
  95% confidence interval: 5.47 <= µ<= 6.00

Answer 87

a. What is the level of measurement?
- quantitative, specifically interval, as it involves measuring the frequency of visits to a supermarket in the past month

b. What is the appropriate indicator of central tendency?
- mean, which represents the average number of times respondents shopped at the supermarket in the past month

c. What is the appropriate indicator of variability?
- The appropriate indicator of variability is the standard deviation, which measures the spread or dispersion of the data around the mean.

d. Is this measure high or low in terms of variability? Explain your answer.
- The measure of variability, as indicated by the standard deviation of 2.33, can be considered relatively moderate. It suggests that the data points are somewhat dispersed around the mean of 6, but not excessively so. However, without a specific benchmark for comparison, it’s challenging to determine definitively whether the variability is high or low.

e. Of course, this is one single variable, and an effective strategy would consider ALL variables
in the decision-making process. But, for the purposes of the test, assume you are part of the Foodland Marketing team deciding about this location. How would you use this data from marketing strategy standpoint? Explain your answer.

From a marketing strategy standpoint, Foodland can utilize this data in several ways:

• Understanding that the mean number of visits to a supermarket in the past month is 6, Foodland can tailor their marketing efforts to retain existing customers and attract new ones. This could include loyalty programs, promotions, or targeted advertising campaigns aimed at encouraging more frequent visits.
• Since the modal number of times shopped is 4, Foodland may want to investigate why this is the most common frequency and if there are any factors influencing customers to shop at this frequency. They can then adjust their strategies accordingly, such as offering incentives for customers to increase their frequency of visits.
• The 95% confidence interval provides a range within which Foodland can be reasonably confident that the true population mean lies. This can help guide decision-making and resource allocation for marketing initiatives.
• Analyzing the range of visits (2-10) can provide insights into the diversity of customer behavior. Foodland can segment their customer base based on frequency of visits and tailor marketing messages or offerings to different segments accordingly.
  Overall, leveraging this data can help Foodland better understand their customers’ shopping habits and preferences, allowing them to develop targeted marketing strategies that enhance customer satisfaction and drive business growth.
• 95% confidence interval: 5.47 <= µ<= 6.00
  We are 95% confident that the true population mean of number of times a person visits Foodland is between 5.47 and 6 times.

This information provides Foodland with valuable insights into the shopping behavior of their customers, particularly regarding how frequently they visit their supermarkets. Let’s break down the implications and why Foodland might care about this information:

Mean, Median, and Mode:
The mean, median, and mode all provide different measures of central tendency. In this case, they are all around 6, indicating that, on average, customers visit Foodland approximately 6 times a month. However, the mode being 4 suggests that 4 visits per month is the most common frequency among customers.
Standard Deviation:
The standard deviation of 2.33 indicates the spread of data around the mean. A higher standard deviation suggests more variability in the data, meaning that customer shopping frequencies may vary considerably around the average of 6 visits per month.
Range:
The range of 8 (from 2 to 10) indicates the spread between the lowest and highest reported shopping frequencies. This shows the extent of variation in customer behavior.
95% Confidence Interval:
The 95% confidence interval provides a range within which we are 95% confident that the true mean number of times customers visit Foodland supermarkets falls. In this case, the interval is between 5.47 and 6.00 visits per month. This gives Foodland an idea of the precision of their estimate of the average number of visits.
Why Foodland might care:

Marketing Perspective:

Understanding how frequently customers visit the store allows Foodland to tailor their marketing efforts. For example, if most customers visit around 5-6 times a month, they can plan promotions or loyalty programs to incentivize additional visits or retain existing customers.
Product, Placement, and Price:

Knowing the frequency of visits can inform decisions about product placement and assortment. Items that are frequently purchased together can be placed closer to each other to enhance convenience for customers. Moreover, pricing strategies can be adjusted based on the frequency of visits to encourage more frequent or larger purchases.
Promotions:

Foodland can use this information to design promotions that align with customers’ shopping behavior. For example, they can offer discounts or special deals during peak shopping periods to capitalize on customers’ regular visits.
In conclusion, understanding the frequency of customer visits to their supermarkets allows Foodland to better meet the needs and preferences of their customers, optimize their marketing strategies, and enhance overall customer satisfaction and loyalty.