GNMAA Marketing Research Service Learning Project

Greater North Michigan Avenue Association’s
BMO Harris Bank Magnificent Mile Lights Festival 2013
White Paper Deliverable
MARK 311- 102
GNMAA Marketing Research Icaza, Jaime, VerHoef, Wen |1

Table of Contents
Section 1: Introduction……………………………………………………………………… 3
Section 2: Background………………………………………………………………………. 4
Business to Business Partnership………………………………………… 4
Managerial Decision Opportunity…………………………………….….. 4
Delivery Oriented Potential…………………………………………………. 5
Section 3: Solution…………………………………………………………………………….. 5
Data Collection Instruments………………………………………………… 5
Focus Group Moderator Guide……………………………… 5
Qualtrics Survey………………………………………………….. 5
Sampling Frame…………………………………………………………………. 6
Quality and Validity…………………………………………….. 6
“Ethical Dilemmas” ……………………………………………. 7
Preliminary Steps to Data Analysis………………………………………. 8
Individual Variables……………………………………………………………. 8
Multiple Variables………………………………………………………………. 9
Section 4: Conclusion………………………………………………………………………… 9
Research Objective 1…………………………………………………………… 10
Conclusion to Analysis………………………………………………………… 15
Section 5: Works Cited……………………………………………………………………….. 17
Section 6: Appendix……………………………………………………………………………

Section 1: Introduction
Greater North Michigan Avenue Association (GNMAA) has a proud history with The Magnificent Mile
to kick off the holiday season. For 50 vibrant years, the lights along the mile signal the start of the
biggest annual holiday shopping season. The research team presents GNMAA with a managerial
decision opportunity to seek greater consumer involvement with its prominent annual holiday Lights
Festival. In order to provide GNMAA with insightful data to refine the Lights Festival and to better
appeal to attending consumers, the following managerial decision opportunity is as follows: What
opportunities are there to further involve consumers on The Magnificent Mile during the Lights
Festival? The interest for the opportunity came after the request for information (RFI). The research is
designed to identify attendees’ interest, opinions, and participation in Lights Festival and seasonal
activities. In support of the managerial decision opportunity are the following research objectives:
 Identify the visibility of activities leading to and on the day of the festival
 Investigate consumers’ desired level of involvement
 Compare involvement of consumers to overall market segment activity; and
 Generate ways to further engage consumers in the festival.
To explore potential developmental opportunities for the Lights Festival, a survey was created based
on the four research objectives and was then circulated during the Lights Festival. The survey was
conducted for a sample over the age of eighteen that included families, couples, and individuals alike.
In addition to the forthcoming data findings, the following are notable findings throughout the research
process, which begins with problem (opportunity) formulation. In this “opportunity formulation”
process, the most important element is developing a range of research objectives and a managerial
decision opportunity rooted in a problem or challenge facing the key contact. In the “determine
research design” phase, the most critical concept is mapping the research process in the way that
best suits the MDO and research objectives. The most significant piece of the next step of the
research process, “determine the data collection method,” is to select the data collection tools that will
provide clean and thorough data. In the “design data collection forms” phase, optimizing the data
collection tool (survey) in its construction, formatting, and inclusion of varying question types to
provide valid data is the most important piece of this step. Lastly, in the “design sample and collect
data” step of the research process, designing a sample frame with which to collect data and analyzing
and interpreting the results in a way that is meaningful and supportive of the MDO and objectives are
the most important concepts. Through this in-depth, evaluative process, the findings suggest
emerging trends that can be applicable to the future of the Lights Festival.
In 2013, Nielsen predicts US consumer spending will rise during the holidays by 2 percent above last
year’s spending; conversely, 68 percent of consumers say they “still feel like they’re in a recession,”
(Russo). The Lights Festival is situated to better appeal to all consumers by considering such external
factors as well as the consumer insights and findings collected throughout the research process.
Thank you for your partnership,
Nic Icaza Louis Jaime Chloe VerHoef Iris Wen

Section 2: Background
Business to Business Partnership
Identification of the research objectives was derived from insights gained during the key informant in-depth
interview, and through feedback provided in the request for information (RFI). To form a
business-to-business partnership with GNMAA, an RFI was generated which detailed the capabilities
as a research partner, and proposed the initial managerial decision opportunity and research
objectives. To finalize the partnership, ‘senior status’ was achieved based off a client-ready request
for proposal (RFP), allowing for the proposed survey to be used as a data collection tool. To generate
data findings, qualitative and quantitative methods were utilized: specifically, Qualtrics (quantitative),
semi-structured observations (qualitative), and the in-depth interview (qualitative). To aid the research
process, Mintel’s Women’s Clothes Shopping report from October 2013, Holiday Shopping report
from July 2013, and State Tourism report from August 2013 were used. Through the State Tourism
report, it was found that women ages 18 to 34 are more likely than men to travel with their spouse,
and more likely to travel with parents or family members (O’Donnell). Through the Holiday Shopping
report, it was found that 37% of people deal with additional holiday expenses by saving money during
the year to spend during the holidays (Erwina). Additionally, Maslow’s Hierarchy of Needs was used
within the survey questions to gain a better understanding of what drives the behaviors of consumers
along The Magnificent Mile (Qualtrics Question Bank).
Managerial Decision Opportunity
The original managerial decision opportunity focused on GNMAA’s members. With the initial proposal
the research objectives focused on identifying the visibility of members leading to and day-of the
festival, investigating members’ desired level of involvement, comparing member involvement to the
market segment activity, the member’s influence on shoppers’ perceptions, and generating ways to
Initial Proposal:
What opportunities are there
to further involve Greater
North Michigan Association
members during the Lights
Festival?
Revised
Proposal:
What opportunities
are there to further
involve consumers
on North Michigan
Avenue during the
Lights Festival?
further engage members in the festival. The focus of the initial
proposal stemmed from multiple references to the sponsors’ and
members’ appeal during the festival from the key informant in-depth
interview. However, the initial managerial decision opportunity and
research objectives were altered based on feedback from the
request for information. During the key informant in-depth interview
with GNMAA, questions regarding exposure prior to the event,
social media use, activities during the event, and goals of the
association and its sponsors helped define other opportunities the
research could explore. Other questions were raised regarding the
regulation and accessibility of the festival through various means of
transportation and crowd-control measures as well as GNMAA’s
use of social media to engage with consumers. These opportunities
represent white space outside of the research conducted on behalf
of the revised MDO; such data points were not collected in support
of further engaging Lights Festival attendees but were certainly
relevant to GNMAA’s goals of promoting safety and a more

comfortable, enjoyable, and engaged experience. The ultimate goal of GNMAA is for members and
sponsors to be satisfied and every attendee to leave the event with a lasting impression. When
GNMAA discussed incentives the organization uses to draw people back to the Lights Festival, it
became evident that the changes reflected ways to get consumers more involved. GNMAA discussed
the use of social media as a tool for engagement and the addition of activities to this year’s events.
Corresponding with the revised opportunity, the focus on consumer involvement during the Lights
Festival led to exploration of how exposure during the planning process influence the consumer, how
consumers’ were motivated to participate, how comparisons can be drawn between activity at the
Lights Festival to the overall market, and ways to further engage consumers.
Discovery- Oriented Potential
To formulate a ‘problem,’ feedback was leveraged from the request for information and key informant
in-depth interview with GNMAA. Following the aforementioned, the research utilized exploratory and
descriptive research design to generate data findings. To generate exploratory research findings, a
focus group moderator guide was provided to GNMAA in the request for proposal. The focus group
moderator guide could be used to further generate qualitative data and in-depth insight on the Lights
Festival attendees. Additionally, to generate descriptive research findings, a survey was conducted
on the day of the Lights Festival. Through discovery-oriented research, potential solutions to further
engage consumers along The Magnificent Mile during the Lights Festival were uncovered.
Section 3: Solution
Data Collection Instruments
Focus Group Moderator Guide
The focus group moderator guide was designed to gather primary, qualitative, exploratory data. The
guide was formatted to include three question types: engagement, exploration, and exit. Engagement
questions invoke participants to recall their overall experience, while exploration questions look for
more specific insights from attendees. The exit question gives participants the chance to add any
additional comments regarding their experience that may have not been asked in the prior questions.
All of the questions in the guide are open-ended and respond to one or more research objective, but
emphasize the discovery of evidence to support the following research objectives: identify the visibility
of activities leading to and on the day of the festival; investigate consumers’ desired level of
involvement; and generate ways to further engage consumers in the festival. For instance, the
question “[w]hat kinds of new experiences would you like to see at the Lights Festival?” in the
exploration section will allow for insight on consumers’ desired level of involvement. The engagement
and exploration sections and subsequent questions follow a funnel approach, beginning with more
general questions to acclimate participants to discussion and then narrowing down to more specific
questions that foster deeply engaged discussion.
Qualtrics Survey

Within the Qualtrics survey, there are twenty-two questions overall: eleven nominal, two ordinal,
seven interval, and two ratio type questions. The allocation of question types in the survey
strategically includes only a small number of free response ratio questions. Less reliability is provided
by ratio questions due to the open-ended nature of the responses they gather. Similarly, ordinal
questions allow participants to rank their responses, but neglect to consider the degree of preference
for one selection over another. The survey is made more reliable by including more nominal and
interval scale question types and limiting the number of ordinal and ratio type questions. The
Qualtrics survey includes questions that collected data to respond to each of the four research
objectives. Before the surveys could be administered it was important that the questions were easy to
understand and covered variables relevant to the research objectives and managerial decision
opportunities so the data collected was as “clean” as possible. The first step towards achieving this
was to conduct peer-driven pretests, during which the survey was assessed using the Writing Good
Questions as a guide for edits (Qualtrics). Using this checklist made suggestions to edit or remove
questions. Examples of question errors that were encountered and revised included double-barreled
questions, leading words, and non-exhaustive lists. One such question that was identified and
removed from the survey asked participants to indicate the events they planned on attending before
and after arriving at the Lights Festival, representing a double-barreled question type. Another way
the Qualtrics survey was designed to mitigate erroneous responses was through including exhaustive
response options, such as allowing for multiple response selections as well as allowing for text entry
to cover alternative responses. Within Qualtrics, the skip-logic feature was enabled to skip attendees
from one question to another based on their response to avoid collecting redundant data. Blocking
was another Qualtrics feature that was optimized within the survey, allowing for questions to be
grouped within a section that corresponded with a specific research objective. Lastly, by using the
‘test survey’ feature, 300 pre-tests were conducted in Qualtrics to ensure the survey was free of error
prior to distribution.
Sampling Frame
The sampling frame for the data collection includes individuals eighteen years or older, couples, and
families. The survey data was collected during the day of the Lights Festival on Saturday, November
23, 2013. The data was collected between the times of 8 AM and 6 PM on The Magnificent Mile. The
population under study is the entire body of attendees at the Lights Festival. Because random
sampling was used to collect the survey data, not all population elements had a fair chance to
participate in the research. Attendees to the Lights Festival were randomly approached and asked to
participate in the survey. The quality of the data collection is reflected in the non-bias nature of the
questions and the goal of mitigating participant bailout.
Quality and Validity
Internal validity is difficult to determine through the research as the focus of the data collection was
done on the day of the Lights Festival and may not reflect the behavior of consumers through the
entire holiday season. Due to high traffic within the defined boundary of the festival, the attendees in
the may have faced greater extraneous factors which may influence their expectations or level of
happiness. External validity could have been caused by confounding factors such as poor weather
conditions on the day of the festival, the mood of the attendee, surveys taken by availability of the

attendee, distractions such as children or family that could shift the focus of the attendee and even
the relationship to the researcher giving the survey. While the festival is largely regionalized to nearby
Midwest states, it is a fair representation of those that have interest in attending a holiday festival.
The measurement validity is translated through the operationalized means the research team
conducted the research trough: the attendees of the Lights Festival over the age of eighteen who
willingly participate. Because the survey was organized by research objective, measurements were
specified to the type of questions surveyed. The survey was pre-tested on Qualtrics and by peer
evaluations to clarify measurement validity. By matching assessment measures to the goal and
opportunities, measurement validity increased the reliability of the data collected. The high impact of
internal and external factors could decrease some reliability, a large factor being the mood of the
attendee due to poor weather conditions the day of the Lights Festival and the instinct to complete the
survey as quickly as possible. The research may be under representative of consumers involved on
The Magnificent Mile that were unwilling to participate in the research. The use of incentives (glow
sticks) was one tactic to encourage participants to take and complete the survey. However, the glow
sticks are more child-friendly; thus, there was a bigger incentive for adults with children to participate.
“Ethical Dilemmas”
Ethical dilemmas that might have incurred include limitations in access to the survey, the use of
incentives, and transparency in the survey. The survey was to be conducted electronically and by pen
and paper. Limits in the number of tablets and pens could have limited the number of people that
could possibly take the survey at the same time. While the use of incentives was in alignment with
ESOMAR, this tactic may shed light on the nature of the participant (ESOMAR). Participants of the
survey may have assumed that volunteering to take the survey meant gaining a glow stick. This
possibly skewed the participants’ interest in the survey, therefore decreasing the validity in the
response. While the survey was conducted and the objectives explained to most participants, there
were many that used the incentive and had no interest in the purpose of the research. While market
researchers should ensure that activities are documented accurately, transparently and objectively,
some participants did not care to know why the survey was being conducted. These ethical dilemmas
may have limited the data collected collection process.
Preliminary Steps to Data Analysis
Although the planned data collection method the day of the Lights Festival was the use of surveys
administered using tablets, the weather the day of the festival made the most effective method of data
collection to be using paper copies to administer the survey. The responses needed to be manually
entered from the paper survey into a digital format via Qualtrics before the data could be migrated
from Qualtrics to SPSS. Once all data was entered into Qualtrics, it was then migrated into SPSS
using the following click stream, starting in Qualtrics:
View Results Tab Select Survey Download Data
File Format: SPSS, Data Representation: Values.
The most important step during office edits was coding the data. This required assigning a numeric
value to each text response. SPSS automatically coded some responses because the software

recognizes basic answer formats such as yes or no questions in which SPSS associated the values
as “1” for yes and “2” for no. However, the majority of the data needed to be manually coded
because of the complexity of the question. There were a significant number of questions left
unanswered, resulting in incomplete data sets from the surveys. These unanswered questions in
Qualtrics resulted in system missing or “pindots” when migrated to SPSS. These pindots needed to
be coded to create a clean and complete data set. The system missing responses were re-coded
using the following click stream:
Transform Recode into the Same Variables Select the Variable
Click "Old and New Values" Select "System-Missing" under Old Value
Add the New Value (0= no response) Click Continue Click OK.
To increase ease and efficiency during analysis each question or variable was given a label, which
was the full question text and response text, and a name, which was the question number and the
response formatted as (Q3_shopping). This preliminary step made the analysis of data easier as data
could be found quickly using the name view for variables.
Individual Variables
When analyzing the data collected from Lights Festival surveys two types of analyses were run:
frequency analyses and crosstab analyses. Frequency analysis involves a straight forward count of
occurrence of responses to each question. Although running data crosstabs allow for the discovery of
association between two variables, frequency counts are important because they isolate data from a
single variable. Another advantage to frequency analysis is that the data can be interpreted easily.
Frequency analysis is not measuring any association or relation to other variables, so data
conclusions can be made simply and objectively. Relevant insights can certainly be gained from
analyzing the frequency of occurrence of specific activities or perceptions. The variables or questions
that were most important for frequency analysis were as follows: the frequency of both positive and
negative perceptions to the Lights Festival, the frequency of use and lack of use of media types as a
resource to plan the Lights Festival activities attendance, the frequency of parents, the frequency of
non-parents, the frequency of attendees in specific age groups, and the frequency of attendees in
specific household income groups. A frequency analysis was also run on the Maslow’s Hierarchy of
Needs question to determine the importance of needs and motivators within the daily lives of
attendees. The survey questions that resulted in data critical to measuring the research objectives
were not the same as the questions that appeared most frequently on the Data Analysis Plan
template concerning individual variable analysis. The data collected on the variables that appeared
on the Data Analysis Plan resulted in data that did not lead to significant conclusions when analyzed
in isolation. Regardless, the single question intended to best help identify the visibility of activities was
“After arriving at the Lights Festival, which activities do you now plan on participating in?” To identify
consumers’ desired level of involvement, the question that best answers this was “Please rate how
important the following items are to you in your daily life.” Asking participants for their age was
intended to best respond to comparing involvement of consumers to overall market segment activity.
Finally, to generate ways to further engage consumers, the single most applicable question to answer
this objective was “Of the following, what do you predict your total spending (in dollars) will be on the

day of the Lights Festival?” The questions chosen for individual variable analysis tended to be more
significant when analyzed against other variables as cross-tabs. Many of the frequency analyses
were run on demographic questions which are important to fully understand general qualities the
population attending the Lights Festival and were thus applicable to all research objectives. The
results from the analysis of frequency counts also aided in establishing what variables gave data
significant enough to warrant running that variable against other variables in crosstab analyses.
Frequency counts highlighted groups of survey respondents frequently occurring at the Lights
Festival which served to spark curiosity towards possible associations that could be found by
analyzing two variables in crosstab analyses.
Multiple Variables
The bulk of significant insights gained from the survey data emanated from data analysis considering
multiple variables. Multiple variable results could be compared in table format through the cross-tab
analysis function in SPSS. The results of a cross-tab of two variables showed how respondents that
answered a specific response to one question responded to another question thus determining an
association or lack thereof between the two variables. Under the input file or .sav file a crosstab could
be run using the following click stream:
Analyze tab Descriptive Statistics Crosstabs.
This click stream opened a window in which a variable or question response was selected as the
cross-tab table column and row. The column and row was determined by the historical order of the
variables: the variable occurring first chronologically was the column, and the second variable in
chronological occurrence was the row. When running cross-tabs it was important not to order by
causation but by chronology to ensure output would not reflect bias resulting from expectations the
researcher had about variable association. Within the cross-tab window were links labeled statistics
and cells. Under the statistics link, chi-square was selected to be included in the output; under the
cells link, column percent was selected to be included in the output. The chi-square statistic
measured association between the variables. If the output value for chi-square was less than 0.05,
the cross-tab was significant and statistically associated. Although none of the cross-tabs resulted in
chi-square values below this threshold, possible associations could be gathered from the cross-tab
analyses. One cross-tab analysis run for the first research objective was “Did you use the Holiday
Guide for the Lights Festival?” and “After arriving at the Festival which activities do you now plan on
participating in?” An example of a cross-tab analysis reflective of the second research objective is
“Please rate how important the following items are to you in your daily life” as the column and “After
arriving at the Lights Festival, which activities do you now plan on participating in?” as the row. A
cross-tab for the third research objective was “What is your gender” as the column and “Please rank
the types of activities that would increase your involvement at the Lights Festival” as the row. A final
cross-tab reflective of the fourth research objective was “How many children do you have?” as the
column and “Please rank the types of activities you would be interested in seeing at the Lights
Festival: Artistic” as the row.
Section 4: Conclusion

Once the data collected was compiled into Qualtrics then coded in SPSS, the research team broke up
the research objectives by the corresponding cross-tabs mentioned above for an in-depth analysis.
Each Research Objective is as follows:
Identify the visibility of activities leading to and day-of the festival
To uncover data findings for the research objective, “Identify the visibility of activities leading to and
day-of the Festival”, six crosstabs and one individual variable were generated from the survey
conducted during the Lights Festival. There individual variables lend valuable insights to GNMAA
because of their relevance to improvement opportunities mentioned during the key informant
interview. Due to the Lights Festival’s dependency on funding from sponsorships, the research team
decided upon uncovering which planning resources consumers most frequently used to select
activities that attendees were going to attend, which Lights Festival activities did consumers plan to
attend before and after arriving to the Lights Festival, and how the Holiday Guide affected consumers,
insights that could further draw funding from sponsors. To discover potential ways to generate
additional visibility for the Lights Festival, the following individual variables and crosstabs were run in
SPSS for the first research objective:
Column Question Row Question
Which media types did you use as a resource to plan
the Lights Festival activities you wish to attend?
What is your gender?
What is your gender? Did you use the Holiday Guide for the Lights Festival?
What is your gender? Did you use the Holiday Guide for the Lights Festival?
After arriving at the Lights Festival, which activities
do you now plan on participating in?
Prior to the Lights Festival, which activities did you
plan on participating in?
Did you use the Holiday Guide for the Lights Festival?
Prior to the Lights Festival, which activities did you
plan on participating in?
Resulting from the individual variable, the research concluded that when planning which activities
Lights Festival attendees wished to attend, the three most commonly used resources were the Lights
Festival website (27.4%), social media (23.2%), and television (17.9%). Furthermore, it is shown
through the results that the three least utilized resources for Lights Festival planning were the radio
(9.5%), other (3.2%), and newspaper (2.1%). In addition to the planning resources, the research
findings also portrayed the listed planning types, females utilized and planned more so than males.

Multiple Variables
From prior to after arriving at the Lights Festival, the data findings show that
there was not much variance in the respondents’ planned activities. From
comparing responses asking consumers for their planned activity participation
prior to arrival compared with that of after arrival to the Lights Festival, the
only activities to retain a significant number of these participants were the
Tree Lighting Parade (46.3%), Lights Festival Lane (37.0%), and shopping
(27.8%). In contrast, after arriving, the top three responses from females
shifted to the Tree Lighting Parade (43.4%), Fireworks Spectacular (37.7%),
and lastly shopping (30.2%). While Lights Festival Lane was still listed as the
fourth most preferred activity after arriving (26.4%), the data shows a potential
opportunity for meeting the Lights Festival Lane expectations of female
consumers the day of the Lights Festival.
As the findings indicate, the Holiday Guide played a significant role in the
decision making process of consumers during the Lights Festival. A
relationship is shown through the data that the more activities consumers planned to participate in
prior to the Lights Festival; they became more likely to pick-up a Holiday Guide (84.7%). Once a
consumer picked up a Holiday Guide, the data shows that the number of activities the consumer
planned to participate in increased (84.7%). Furthermore, of the people surveyed that used the
Holiday guide, 80.8% of them identify as female, while only 19.2% identify as male. An insight gained
from the data findings is that making an impact on consumers before arriving to the Lights Festival is
crucial to what activities they plan to participate in. This finding is supported by “Prior to the Lights
Festival, which activities did you plan on participating in?” question, and “After arriving at the Lights
Festival, which activities do you now plan on participating in?”, both equaling 84.7% when picking up
a Holiday Guide at the Lights Festival. Additionally, when researching and planning Lights Festival
activities, a majority of the work is done by female consumers (females: 66.7% vs. males: 33.3%).
Investigate consumers’ desired level of involvement
From the question regarding Maslow’s Hierarch of Needs in the results, 35.0% of respondents rated
self-fulfillment and excitement as being very important in their daily lives. Closely above that, 36.7%
rated fun and enjoyment and sense of accomplishment as very important. The significance of these
frequencies emerges in the associated behaviors—such as participation in particular kinds of
seasonal activities—resulting from the consumers’ specific motivators.
Multiple Variables
From the survey data, one appropriate method to investigate consumers’ desired levels of
involvement was to analyze motivators in their daily lives based on Maslow’s Hierarchy of Needs and
to observe associations these findings share with attendee participation in different Lights Festival
activities. One cross tab produced the following results: of consumers who rate excitement as very

important in their daily lives as important or very important, respectively 87.5% and 81.0% did not
plan on participating in in-store events. Similarly, the 2012 GNMAA survey data reflects a lack of
current involvement in in-store events. The question asked participants to indicate what activities
participants would be participating in the day of the Lights Festival. Events in-store ranked last of six
choices with only 30.0% of respondents choosing that option. The Tree Lighting Parade was the top
choice for this question, with 78.0% of respondents indicating that he/she attended or planned on
attending. Only 8.0% of this year’s respondents who were very satisfied with the Lights Festival
placed in-store events in his/her top three activities. Conversely, of consumers who find excitement
very important in their daily lives, 61.9% intend on shopping along The Magnificent Mile either
frequently or very frequently during the holiday season. These findings show a discrepancy between
the shopping related activities consumers plan on participating in during the Lights Festival versus
during the holiday season in direct relation to the motivators for activities such as shopping.
For those who found having a sense of accomplishment very important, 90.3% did not plan on
participating in the BMO Harris Bank Community Art Project. 72.7% of those who indicated that fun
and enjoyment is very important in their daily lives did not plan on attending the BMO Harris Bank
Stage after arriving, while 43.3% of participants ranked music in the top three types of activities with
potential to increase his/her involvement at the Lights Festival. Satisfaction was another significant
reference point which indicated an association to festival activities that attendees planned on
participating in. 12.0% of Lights Festival attendees who were very satisfied with his/her overall
experience placed the BMO Harris Bank Stage in his/her top three favorite activities, while 52.0%
placed the Tree Lighting Parade in the top three. 64% of attendees who were very satisfied with their
experience at the Lights Festival indicated that they would like for his/her experience on the day of
the festival to be described as “family oriented” while 52% wanted their experience to be described as
interactive. What this data shows is that the intended involvement in particular activities (e.g. music,
in-store and interactive events) along The Magnificent Mile and at Lights Festivals during the holidays
and in years to come surpasses the current level of involvement in related Lights Festival activities.
The findings can be interpreted to suggest that these consumers want their time during the holiday
season to be family oriented and interactive, engaging in events such as shopping and hearing
music. While these events received lower favorability in relation to other Lights Festival activities,
consumers expressed possibilities for deeper involvement in the Lights Festival by expanding in
these areas.
Compare involvement of consumers’ to overall market segment activity
The primary data shows that 60% of attendees at the Lights Festival are women and 32% are men
(the remaining 8% responded prefer not to answer). With almost half of the participants having
children (48% with children, 43% with no children, 9% prefer not to answer). Over 50% of attendees
were from the Cook County area in Illinois while the remainder showed scattered residence in
Michigan, Indiana, and counties in Illinois just outside of Cook County.
Multiple Variables
Although the data shows that there was a high volume of women at the festival, according to ESPN
Research and Analytics, it has been recently discovered that for adults between the ages of 18 to 54,

33% of men surveyed consider themselves the primary shopper for the household (Berg). It can also
be observed that not only do men outspend women during almost every annual holiday, but men also
tend to be faster, more direct shoppers. However, from the primary data that was heavy with women
respondents, it can be said that shopping was an activity 40.9% of women said would increase their
involvement at the Lights Festival, compared to 10% of men. According to Mintel’s Holiday Shopping
report, 64% of big-ticket holiday purchases are browsed and purchased in-person at a store. An
effective way to engage with a large proportion of consumers includes using coupons during the
holiday season and advertisements that promote in-store sales (Erwina). Because in-store displays
still play a prominent communication device, in-store events tend to show an increase in sales. 100%
of respondents that ranked shopping as the most enjoyable Lights Festival activities were women,
which is reflective of women’s appeal for the right mix of style and affordability. According to Mintel’s
Women’s Clothes Shopping report, the number one reason women buy clothes is because the stores
was having a sale, this reason is closely followed by replacing something old or worn out, and there
was no particular reason but they saw something they liked and bought it (Lipson, Women’s Clothes
Shopping). To emphasize the draw of sales and special offers in-stores, 46% of parents usually wait
for sales to buy their children’s clothing; 37% of parents buy children’s clothing at stores they were
not planning to shop at because of sales and special offers (Lipson, Children’s Clothes Shopping).
From the primary data, the research team found that 33.3% of participants planned to shop and go to
in-store events after their arrival to the festival. Of the 33.3%, 4.2% of participants planned to go to in-store
events prior to their arrival. Almost half the people who planned on attending in-store events
prior to his/her arrival actually went. Of the people who did not plan to go to in-store events prior to
his/her arrival, 13.2% ended up going to in-store events after arriving. Of the attendees planning to
participate in in-store events after arriving, 60.0% were women, while 67.7% of attendees planning on
shopping were women. From observations made on the day, everyone generally seemed interested
in shopping and in the special deals going on the day of the event. From talking to survey participants
or families of the survey participants, many people that went shopping found deals by walking up to
greeters at stores and getting offered a deal which drew them in.
From the results, just over 40% of attendees came to the Lights Festival from outside Cook County:
specifically bordering states such as Michigan and Indiana. Because domestic travel contributes to
the profitability of the Lights Festival in Chicago, there is data that supports a demanding market for
affordable travel especially for families. Typical domestic travel companions include immediate family
(O’Donnell). Domestic travel of more than 100 miles away (one way) is relevant across different
marital status and age groups: although there is almost three-fourths of domestic travel for vacation
by married people over the age of 55. The large draw that comes with a domestic destination is a
unique experience (O’Donnell). Events like the Lights Festival would be considered a vacation
experience that an attendee couldn’t get anywhere else, as well as local scenery, culture, and dining
experiences that cannot be provided elsewhere. While Chicago is already the third-largest
metropolitan in the United States, the marketing efforts of the Lights Festival have the potential to
reach the larger market for state tourism (United States).

Generate ways to further engage consumers in the festival
The primary data from individual variable analysis showed print was not frequently being used as a
resource to plan Lights Festival engagement in activities. Of the sixty respondents to the question
“What types of media did you use as a resource to plan your Lights Festival activities?” fifty-eight did
not select print as a resource they used. The data suggests print is not being used, thus it may not be
economical to allocate resources towards print. This is not the most insightful information given that
print has been a dying industry since the conception of the PC and the availability of the internet. The
primary data from individual variable analysis also shows attendees were not particularly interested in
seeing informational activities at the festival. Fourteen out of thirty survey takers who responded to
the question, “How well do the following describe activities you would be interested in seeing at the
Lights Festival?” responded poorly or neutral when the adjective was informational. The data
suggests there is not a substantial desire from attendees to include more informational events at the
Festival.
Multiple Variables
Under the hypothesis that there may be some association between Lights Festival attendees who
read business reviews and the types of activities they’re interested in, several cross-tabs were run
addressing this possibility. The data shows over half of the survey respondents who responded
affirmatively to reading business reviews also responded that “interactive” described very well
activities he/she would like to see at the Lights Festival. The data suggests that the people attending
the Lights Festival who are interested in seeing interactive activities are also reading reviews. There
may be an opportunity to increase attendee engagement by increasing reviews about interactive
activities. There would be other variables playing into this scenario, for example in forming this
conclusion it is also logical to assume the reviews of the interactive events would need to be positive
to encourage people to engage. In contrast the data shows that people who said “creative” described
activities they’d want to see well or very well did not read business reviews at the same frequency as
those responding very well and well to “interactive”. Of the nineteen survey takers who responded
very well or well to “creative” as a description of activities they’d like to see at the Festival, twelve did
not respond affirmatively to reading business reviews. This data cross-tab suggest that people who
are interested in seeing creative activities at the Festival are not reading reviews at a high occurrence
thus reviews may not be the best tool for increasing engagement in creative activities. A limitation of
this data insight is the response rate to the business review reader variable. Twenty survey takers
responded affirmatively to reading business reviews which gives a very small sample to compare
against desired activity involvement.
An interesting insight gained from primary data analyzed as a cross tab was the potential association
between non-parent attendees and an interest in live music. The cross tab that suggested this
involved the variable, “How many children do you have?” in the column and the “Live Music” rankings
for the question “Rank the types of activities you’d be interested in seeing at the Lights Festival?”
Respondents with zero children ranked live music high compared to respondents with children. Of the
respondents with no children, eighteen out of twenty-two ranked live music at three or above. This
means eighty-two percent of the non-parent sample ranked live music in the top three activities they

would be interested in seeing at the Festival. The data suggests there may be an opportunity to
further involve non-parent adults in the festival by including more musicians targeting adults without
children.
The results from the cross-tab analyzing a possible association between non-parents and interest in
live music sparked curiosity to further investigate non-parents vs. parents and how that could be
associated with interest in activities. An insight came from the cross tab ranking interest level towards
“artistic” activities and respondents without children. People who responded to having zero children
ranked artistic low; sixteen out of twenty-two respondents without children, ranked artistic at four or
below. The data suggests there is more of an opportunity to gear art projects towards children and/or
parents rather than childless adults. A limitation to this insight is that it cannot be supported by other
related data collected. Although respondents without children ranked creativity low, respondents with
children didn’t rank artistic particularly high. Another data cross-tab supporting this conclusion
compared the interest in seeing adult focused activities at the Festival to those planning to attend the
BMO Harris Bank stage. Of the twenty-two respondents who classified “adult focused” as describing
activities he/she would like to see at the festival well and very well, eight responded that they planned
on visiting the BMO Harris Bank stage. This data suggests that people desiring adult-focused
activities are not frequently attending the BMO Harris Bank Stage. This could be based on a
perception of the BMO Harris Bank Stage as non adult-focused.
Conclusion to Analysis
The primary data reflects trends in participation during the Lights Festival. Valid and reliable
recommendations can be communicated based on the trends in the data. For example, females
played a larger influence in the planning process, and the more resources available to plan activities
increased participation. Female-interest drove the majority of the activities. People who did not have
children felt a stronger interest in live music and incorporating creativity into the activities, since this
was roughly half of the sampled population, it can be noted that their highest participation was as
expected in the Tree Lighting parade. Some of the actual findings can be applicable beyond the day
of the festival such as which types of activities stemmed the most interest, as well as which type of
activities showed the most interest and the most participation. This could be applicable to other
holiday festivals similar to the Lights Festival, and could be reflective of the marketable activities.
Though the data may seem regionalized, it would be applicable to other festival or free-public
activities put on by non-profit organizations that want a similar outcome and a long-term outstanding
reputation Other generalizations that can be made are that the Holiday Guide results in higher
participation from consumers much like how consumer interest can be gained through knowledge.
Also the choice in music affects the audience that is present. However, for the most part, the research
has limited application to GNMAA due to the specific events listed at the festival.
Limitations to the methodology
Sources of error innate to the methodology were found when the Qualtrics survey was translated to
paper copies. The survey was initially optimized for tablet/online use; on the day of the festival,
attendees preferred to take the paper survey over the online version. This decreased the reliability of

some of questions that were meant to be more interactive-- the final survey included drag-and-drop
and ranking questions that could not easily be completed on paper. The use of paper surveys also
meant that values may have not been recorded as accurately as they would have been had an online
survey been distributed. When online surveys were conducted, participants quickly became
frustrated because of slow internet connections. Overall, willing participants were found at the center
of the festival at Pioneer Court; these participants were more willing than others situated outside of
the area to take the survey, likely because of lines formed for Lights Festival Lane tents. Another
limiting factor in the collection of data was the use of glow sticks as an incentive. Glow sticks did not
always appeal to potential survey candidates. When the glow sticks did act as an incentive, it was
short-lived due to the limited supply of glow sticks. The most immediate factor in the sources of error
was the cold weather the day of the festival. This caused attendees to be short-tempered, easily-agitated,
and unwilling to take the survey because it meant hands would be exposed to the bitter chill.
In conjunction with the cold weather, participants responded negatively towards the length of the
survey and allocation of question types (e.g. multiple response, rank).

Section 5: Works Cited
Berg, Meredith Derby. "Men Outspend Women During Holiday Season: ESPN Survey."Advertising Age. Ad
Age, 27 Nov. 2013. Web. 17 Dec. 2013.
Erwina, Ika. Holiday Shopping- U.S. Rep. Mintel Group Ltd., July 2013. Web. 13 Dec. 2013.
ESOMAR. International Chamber of Commerce. ICC/ESOMAR International Code on Market and Social
Research. N.p.: n.p., 2007. Print.
Lipson, Alison. Women's Clothes Shopping- U.S. Rep. Mintel Group Ltd., Oct. 2013. Web. 13 Dec. 2013.
Lipson, Alison. Children's Clothes Shopping- U.S. Rep. Mintel Group Ltd., Nov. 2013. Web. 13 Dec. 2013.
O'Donnell, Fiona. State Tourism- U.S. Rep. Mintel Group Ltd., Aug. 2013. Web. 13 Dec. 2013.
Russo, James. "'Tis the Season to Be Fiscally Cautious." Nielsen. Nielsen, 4 Nov. 2013. Web. 5 Dec. 2013.
United States. Census Bureau. Department of Commerce. Guide to State and Local Census Geography.
United State Census Bureau, Apr. 2011. Web. 13 Dec. 2013.

Section 6: Appendix: Visuals and Examples
Appendix Table of Content
Item 1: Qualtrics Survey………………………………………..……………....19-23
Item 2: SPSS Data Output File…………………………………………….….24-269
Item 3: Field Notes from Key Informant Interview………………………....270-272
Item 4: Focus Group Moderator Guide…………………………………………...273
Item 5: Semi-Structured Observations………………………………………274-275
Item 6: Client Round Table Content……………………………………………...276
Item 7: Resumes
A. Nic Icaza………………………………………………………………....278
B. Louis Jaime……………………………………………………........279-280
C. Chloe VerHoef………………………………………………...………...281
D. Iris Wen …………………………………………………………………282

Appendix item 1: Qualtrics Survey
MARK 311 Survey-- GNMAA Final
Q1 We're Loyola University students conducting research on behalf of The Magnificent Mile Lights
Festival. Thank you for taking the time to help out with the development of The Magnificent Mile and the
Lights Festival. Let's get this survey rolling!
Q2 Prior to the Lights Festival, which activities did you plan on participating in? (Select all that apply)
Lights Festival Lane
BMO Harris Bank Stage
Tree Lighting Parade
Fireworks Spectacular
In-Store Events
Shopping
Canned Food Drive
Holiday Carol
BMO Community Art Project
Other ____________________
Q3 After arriving at the Lights Festival, which activities do you now plan on participating in? (Select all that
apply)
Lights Festival Lane
BMO Harris Bank Stage
Tree Lighting Parade
Fireworks Spectacular
In-Store Events
Shopping
Canned Food Drive
Holiday Carol
BMO Community Art Project
Other ____________________
Q4 How well do the following items describe other activities you would be interested in seeing at the Lights
Festival?
Very Well Well NeutralPoorly Very Poorly
______ Interactive ______ Interactive ______ Interactive ______ Interactive ______ Interactive
______ Adult focused ______ Adult focused ______ Adult focused ______ Adult focused ______ Adult focused
______ Family oriented ______ Family oriented ______ Family oriented ______ Family
oriented ______ Family oriented
______ Social ______ Social ______ Social ______ Social ______ Social
______ Contests ______ Contests ______ Contests ______ Contests ______ Contests
______ Games ______ Games ______ Games ______ Games ______ Games
______ Informational ______ Informational ______ Informational ______ Informational ______ Informational
______ Creative ______ Creative ______ Creative ______ Creative ______ Creative

______ Other ______ Other ______ Other ______ Other ______ Other
Q5 Did you use the Holiday Guide for the Lights Festival?
Yes
No
Q25 During the holiday season, which business types do you shop at most frequently? (1 being the most
frequent, and 8 being the least)
______ Apparel
______ Electronics
______ Entertainment (e.g. music & movies)
______ Food and beverage
______ Health and beauty
______ Sporting goods
______ Retail
______ Online (e.g. Ebay, Amazon, Groupon)
Q26 Do you use social media for reviews?
For products I leave product reviews I read product reviews Not Applicable
For businesses I leave business reviews I read business reviews Not
Applicable
Q27
Q28 By using the options provided, please indicate how frequently through the holiday season you plan on
engaging in the following activities, along The Magnificent Mile.
Shopping Very Infrequently Infrequently Neither Frequently
Very Frequently
Dining Very Infrequently Infrequently Neither Frequently Very
Frequently
Sightseeing Very Infrequently Infrequently Neither Frequently
Very Frequently
Theater Very Infrequently Infrequently Neither Frequently
Very Frequently
Live Music Very Infrequently Infrequently Neither Frequently
Very Frequently
Museums Very Infrequently Infrequently Neither Frequently
Very Frequently
Lodging Very Infrequently Infrequently Neither Frequently
Very Frequently

Q29 How long do you plan on spending at each of the following Lights Festival events?
______ Lights Festival Lane
______ BMO Harris Bank Stage
______ Tree Lighting Parade
______ Fireworks Spectacular
______ In-Store Events
______ Shopping
______ Holiday Carol
______ BMO Community Art Project
Q30 Please rank the following Lights Festival activities in order of enjoyment (1 being the most enjoyable and 9
being the least enjoyable).
______ Canned Food Drive
______ Lights Festival Lane
______ BMO Harris Bank Stage
______ Tree Lighting Parade
______ Fireworks Spectacular
______ In-Store Events
______ Shopping
______ Holiday Carol
______ BMO Community Art Project
Q31 Please rate how important the following items are to you in your daily life (1 star being the least important
and 5 stars being the most important).
______ Sense of belonging
______ Fun and enjoyment
______ Warm relationships with others
______ Self-fulfillment
______ Being well respected
______ Excitement
______ Sense of accomplishment
______ Security
______ Self-respect
Q32 After today, you would like for your Lights Festival experience to be described as: (Select all that apply)
Family oriented
Interactive
Creative
Social
Informational
Fulfilling
Secure
Other ____________________

Q33
Q34 Of the following items, what do you predict your total spending (in dollars) will be on the day of the Lights
Festival?
______ Dining
______ Shopping
______ Lodging
______ Sightseeing
______ Other
Q35 Which media types did you use as a resource to plan the Lights Festival activities you wish to attend?
(Select all that apply)
Television
Radio
Word of mouth
Social media
Lights Festival website
Print (magazine or newspaper)
Other ____________________
Q36 Please rank the types of activities that would increase your involvement at the Lights Festival (1 describing
the activity that would increase your involvement the most, and 5 increasing your involvement the least).
______ Shopping
______ Dining
______ Live Music
______ Sightseeing
______ Artistic
______ Informational
______ Other
Q37 What is your perception of the Lights Festival?
1
2
3
4
5
Q38 If possible, we would like to ask you a few personal questions. Please note: you will not be associated with
any of your responses, and you will be able move past any questions that you do not wish to answer.
Q39 How old are you?
18-25

26-34
35-54
55-64
65 or over ____________________
Q40 What is your race?
White/Caucasian
Black
Hispanic
Asian
Native American
Pacific Islander
Other
Q41 What is your gender?
Male
Female
Q42 How many children do you have?
0
1
2
3
4
5
6
7+
Q43 What is your ZIP code?
Q44 Please indicate your current household income.
Less than $20,000
$20,000 to $39,999
$40,000 to $59,999
$60,000 to $79,000
$80,000 to $99,999
$100,000 or more
Prefer not to answer
Q45 Thank you for participating in our survey! Please enjoy the Lights Festival and have a wonderful Holiday
Season!

Appendix item 2: SPSS Data Output File
1. GET
2. FILE='C:TempTemp1_MARK_311_Survey_Complete.zipMARK_311_Survey_Complete.sav'.
3. DATASET NAME DataSet1 WINDOW=FRONT.
4. ADD FILES /FILE=*
5. /FILE='C:UsersnicazaDesktopMARK_311_Survey_GNMAA_Final.sav'.
6. EXECUTE.
7. MULT RESPONSE GROUPS=$Prior_to (Q2_1 Q2_2 Q2_3 Q2_4 Q2_5 Q2_6 Q2_7 Q2_8 Q2_9 Q2_10
(1))
8. /VARIABLES=Q42(1 2)
9. /TABLES=Q42 BY $Prior_to
10. /BASE=CASES.
11.
12.
13.
14.
Notes
Output Created 26-NOV-2013 20:42:08
Comments
Input
Active Dataset DataSet1
Filter <none>
Weight <none>
Split File <none>
N of Rows in Working Data File 60
Missing Value Handling
Definition of Missing
User-defined missing values are
treated as missing.
Cases Used
Statistics for each table are
based on all the cases with valid
data in the specified range(s) for
all variables in each table.
Syntax
MULT RESPONSE
GROUPS=$Prior_to (Q2_1
Q2_2 Q2_3 Q2_4 Q2_5 Q2_6
Q2_7 Q2_8 Q2_9 Q2_10 (1))
/VARIABLES=Q42(1 2)
/TABLES=Q42 BY $Prior_to
/BASE=CASES.
Resources
Processor Time 00:00:00.02
Elapsed Time 00:00:00.02
15.
16.
17.
Notes
Comments
Input
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Missing Value Handling Definition of Missing
treated as missing.

Cases Used
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MULT RESPONSE
Q2_2 Q2_3 Q2_4 Q2_5 Q2_6
Q2_7 Q2_8 Q2_9 Q2_10 (1))
/VARIABLES=Q42(1 8)
/BASE=CASES.
Resources
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/TABLES=Q42 BY Q2_1
Q2_2 Q2_3 Q2_4 Q2_5 Q2_6
Q2_7 Q2_8 Q2_9 Q2_10
/FORMAT=AVALUE
TABLES
/STATISTICS=CHISQ
/CELLS=COUNT ROW
COLUMN TOTAL
/COUNT ROUND CELL.
Resources
Dimensions Requested 2
Cells Available 174734
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/VARIABLES=Q41(4 5)
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TOTAL
/BASE=CASES.
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$After (Q3_1 Q3_2 Q3_3 Q3_4
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Q2_7 Q2_8 Q2_9 Q2_10 (0))
$After (Q3_1 Q3_2 Q3_3 Q3_4
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Q3_10 (0))
$After
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Q2_7 Q2_8 Q2_9 Q2_10 (0))
$After (Q3_1 Q3_2 Q3_3 Q3_4
Q3_5 Q3_6 Q3_7 Q3_8 Q3_9
Q3_10 (0))
$After
/CELLS=ROW COLUMN
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Q2_7 Q2_8 Q2_9 Q2_10 (1))
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TABLES
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COLUMN TOTAL
/COUNT ROUND CELL.
Resources
54.
55. RECODE Q2_1 Q2_2 Q2_3 Q2_4 Q2_5 Q2_6 Q2_7 Q2_8 Q2_9 Q2_10 (SYSMIS=0).
56. EXECUTE.
57. RECODE Q2_1 Q2_2 Q2_3 Q2_4 Q2_5 Q2_6 Q2_7 Q2_8 Q2_9 Q2_10 Q3_1 Q3_2 Q3_3 Q3_4 Q3_5
Q3_6 Q3_7 Q3_8 Q3_9 Q3_10 Q4_2_Group Q4_2_Rank Q4_3_Group Q4_3_Rank Q4_4_Group
Q4_4_Rank Q4_5_Group Q4_5_Rank Q4_6_Group Q4_6_Rank Q4_7_Group Q4_7_Rank Q4_8_Group
Q4_8_Rank Q4_9_Group Q4_9_Rank Q4_10_Group Q4_10_Rank Q5 Q25_1 Q25_2 Q25_3 Q25_4 Q25_5

Q25_6 Q25_7 Q25_8 Q26_1_1 Q26_1_2 Q26_1_3 Q26_2_1 Q26_2_2 Q26_2_3 Q27 Q28_1 Q28_2 Q28_3
Q28_4 Q28_5 Q28_6 Q28_7 Q29_1 Q29_2 Q29_3 Q29_4 Q29_5 Q29_6 Q29_7 Q29_8 Q30_9 Q30_x1
58. Q30_x2 Q30_x3 Q30_x4 Q30_x5 Q30_x6 Q30_x7 Q30_x8 Q31_1 Q31_2 Q31_3 Q31_4 Q31_5 Q31_6
Q31_7 Q31_8 Q31_9 Q32_1 Q32_2 Q32_3 Q32_4 Q32_5 Q32_6 Q32_7 Q32_8 Q33 Q34_6 Q34_7 Q34_8
Q34_9 Q34_10 Q35_1 Q35_2 Q35_3 Q35_4 Q35_5 Q35_6 Q35_7 Q36_1 Q36_2 Q36_3 Q36_4 Q36_5
Q36_6 Q36_7 Q37 Q38 Q39 Q40 Q41 Q42 (SYSMIS=0).
59. EXECUTE.
60. RECODE Q44 Q45 (SYSMIS=0).
61. EXECUTE.
62. MULT RESPONSE GROUPS=$Prior_to (q2_1 q2_2 q2_3 q2_4 q2_5 q2_6 q2_7 q2_8 q2_9 q2_10 (1))
63. /FREQUENCIES=$Prior_to.
64.
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MULT RESPONSE
GROUPS=$Prior_to (q2_1
q2_2 q2_3 q2_4 q2_5 q2_6
q2_7 q2_8 q2_9 q2_10 (1))
/FREQUENCIES=$Prior_to.
Resources
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Output Created 01-DEC-2013 18:06:10
Comments
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Data C:TempMARK_311.sav
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treated as missing.
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Syntax
MULT RESPONSE
GROUPS=$After_arriving
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Q2_3 Q2_4 Q2_5 Q2_6 Q2_7
Q2_8 Q2_9 Q2_10 (1))
/VARIABLES=Q44(1 7)
/TABLES=$After_arriving BY
Q44
/CELLS=TOTAL
/BASE=CASES.
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treated as missing.
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Statistics are based on all cases
with valid data.
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VARIABLES=Q44
/STATISTICS=MEAN
MEDIAN MODE
/BARCHART FREQ
/ORDER=ANALYSIS.
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treated as missing.
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with valid data.
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VARIABLES=Q41
/STATISTICS=MEAN
MEDIAN MODE
/BARCHART FREQ
/ORDER=ANALYSIS.
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Q2_7 Q2_8 Q2_9 Q2_10 (1))
/VARIABLES=Q41(4 5)
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Input Data C:TempMARK_311.sav

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MULT RESPONSE
GROUPS=$Which_Media_Typ
es 'Which_Media_Types'
(Q35_1 Q35_2 Q35_3 Q35_4
Q35_5 Q35_6 Q35_7 (1))
/VARIABLES=Q44(1 7)
/TABLES=$Which_Media_Typ
es BY Q44
/CELLS=TOTAL
/BASE=CASES.
Resources
89.
90.
91.
Notes
Comments

Input
Filter <none>
Weight <none>
Split File <none>
treated as missing.
Cases Used
Syntax
MULT RESPONSE
/VARIABLES=Q35_5(0 1)
Q44(1 7)
/TABLES=Q35_5 BY Q44
/CELLS=TOTAL
/BASE=CASES.
Resources
92.
93.
94.
Notes
Comments
Input
Filter <none>
Weight <none>
Split File <none>
treated as missing.
Cases Used
Syntax
MULT RESPONSE
Q2_3 Q2_4 Q2_5 Q2_6 Q2_7
Q2_8 Q2_9 Q2_10 (1))
/VARIABLES=Q5(0 1)
/TABLES=Q5 BY
$After_arriving
/CELLS=TOTAL
/BASE=CASES.
Resources
95.
96.
97.
Notes
Comments
Input
Filter <none>
Weight <none>
Split File <none>

treated as missing.
Cases Used
Syntax
MULT RESPONSE
Q3_3 Q3_4 Q3_5 Q3_6 Q3_7
Q3_8 Q3_9 Q3_10 (1))
/VARIABLES=Q5(0 1)
/TABLES=Q5 BY
$After_arriving
/CELLS=TOTAL
/BASE=CASES.
Resources
98.
99.
100.
Notes
Comments
Input
Filter <none>
Weight <none>
Split File <none>
treated as missing.
Cases Used
Syntax
MULT RESPONSE
Q3_3 Q3_4 Q3_5 Q3_6 Q3_7
Q3_8 Q3_9 Q3_10 (1))
/VARIABLES=Q5(0 1)
Q5
/CELLS=TOTAL
/BASE=CASES.
Resources
101.
102.
103.
Notes
Comments
Input
Filter <none>
Weight <none>
Split File <none>

treated as missing.
Cases Used
Syntax
CROSSTABS
/TABLES=Q3_6 BY Q5
/FORMAT=AVALUE
TABLES
/STATISTICS=CHISQ
/CELLS=COUNT COLUMN
/COUNT ROUND CELL.
Resources
104.
105.
106.
Notes
Comments
Input
Filter <none>
Weight <none>
Split File <none>
treated as missing.
Cases Used
Syntax
CROSSTABS
/TABLES=Q3_3 BY Q5
/FORMAT=AVALUE
TABLES
/STATISTICS=CHISQ
/CELLS=COUNT TOTAL
/COUNT ROUND CELL.
Resources
107.
108.
109.
Notes
Comments
Input
Filter <none>
Weight <none>
Split File <none>
Missing Value Handling Definition of Missing
treated as missing.

Cases Used
Syntax
CROSSTABS
/TABLES=Q3_3 BY Q5
/FORMAT=AVALUE
TABLES
/STATISTICS=CHISQ
/CELLS=COUNT COLUMN
/COUNT ROUND CELL.
Resources
110.
111. MULT RESPONSE GROUPS=$Prior 'Prior' (Q2_1 Q2_2 Q2_3 Q2_4 Q2_5 Q2_6 Q2_7 Q2_8 Q2_9
Q2_10 (1))
112. /VARIABLES=Q5(0 1)
113. /TABLES=$Prior BY Q5
114. /CELLS=TOTAL
115. /BASE=CASES.
116.
117.
118.
119.
120. Multiple Response
121.
122.
123.
Notes
Comments
Input
Filter <none>
Weight <none>
Split File <none>
treated as missing.
Cases Used
Syntax
MULT RESPONSE
Q2_2 Q2_3 Q2_4 Q2_5 Q2_6
Q2_7 Q2_8 Q2_9 Q2_10 (1))
/VARIABLES=Q5(0 1)
/CELLS=TOTAL
/BASE=CASES.
Resources
124.

125.
126. [DataSet1] C:TempMARK_311.sav
127.
128.
129.
Case Summary
Cases
Valid Missing Total
N Percent N Percent N Percent
$Prior*Q5 26 43.3% 34 56.7% 60 100.0%
130.
131.
$Prior*Q5 Crosstabulation
Did you use
the Holiday
Guide for
the Lights
Festival?
No
Priora
Prior to the Lights Festival, which activities did you plan on participating in?
(Select all that ap...-Lights Festival Lane
Count 3
% of Total 11.5%
(Select all that ap...-BMO Harris Bank Stage
Count 1
% of Total 3.8%
(Select all that ap...-Tree Lighting Parade
Count 2
% of Total 7.7%
(Select all that ap...-Fireworks Spectacular
Count 1
% of Total 3.8%
(Select all that ap...-In-Store Events
Count 0
% of Total 0.0%
(Select all that ap...-Shopping
Count 0
% of Total 0.0%
(Select all that ap...-Canned Food Drive
Count 0
% of Total 0.0%
(Select all that ap...-Holiday Carol
Count 0
% of Total 0.0%
(Select all that ap...-Other
Count 1
% of Total 3.8%
Total
Count 4
% of Total 15.4%
132.
Did you use
the Holiday
Guide for the
Lights
Festival?
Yes
Priora
Count 14
% of Total 53.8%
Count 7
% of Total 26.9%
Count 17
% of Total 65.4%
(Select all that ap...-Fireworks Spectacular
Count 8
% of Total 30.8%

(Select all that ap...-In-Store Events
Count 3
% of Total 11.5%
(Select all that ap...-Shopping
Count 11
% of Total 42.3%
(Select all that ap...-Canned Food Drive
Count 1
% of Total 3.8%
(Select all that ap...-Holiday Carol
Count 1
% of Total 3.8%
(Select all that ap...-Other
Count 1
% of Total 3.8%
Total
Count 22
% of Total 84.6%
133.
Total
Priora
Prior to the Lights Festival, which activities did you plan on participating in? (Select
all that ap...-Lights Festival Lane
Count 17
% of Total 65.4%
all that ap...-BMO Harris Bank Stage
Count 8
% of Total 30.8%
all that ap...-Tree Lighting Parade
Count 19
% of Total 73.1%
all that ap...-Fireworks Spectacular
Count 9
% of Total 34.6%
all that ap...-In-Store Events
Count 3
% of Total 11.5%
all that ap...-Shopping
Count 11
% of Total 42.3%
all that ap...-Canned Food Drive
Count 1
% of Total 3.8%
all that ap...-Holiday Carol
Count 1
% of Total 3.8%
all that ap...-Other
Count 2
% of Total 7.7%
Total
Count 26
% of Total 100.0%
134.
Percentages and totals are based on respondents.
a. Dichotomy group tabulated at value 1.
135.
136. CROSSTABS
137. /TABLES=Q2_3 BY Q5
138. /FORMAT=AVALUE TABLES
139. /STATISTICS=CHISQ
140. /CELLS=COUNT COLUMN
141. /COUNT ROUND CELL.
142.
143.
144.
145.
Notes

Comments
Input
Filter <none>
Weight <none>
Split File <none>
treated as missing.
Cases Used
Syntax
CROSSTABS
/TABLES=Q2_3 BY Q5
/FORMAT=AVALUE
TABLES
/STATISTICS=CHISQ
/CELLS=COUNT COLUMN
/COUNT ROUND CELL.
Resources
146.
147.
148.
Notes
Comments
Input
Filter <none>
Weight <none>
Split File <none>
treated as missing.
Cases Used
Syntax
MULT RESPONSE
Q2_2 Q2_3 Q2_4 Q2_5 Q2_6
Q2_7 Q2_8 Q2_9 Q2_10 (1))
$Which_Media_Types
'Which_Media_Types' (Q35_1
Q35_2 Q35_3 Q35_4 Q35_5
Q35_6 Q35_7 (1))
/TABLES=$Prior BY
$Which_Media_Types
/CELLS=TOTAL
/BASE=CASES.
Resources
149.
150.
151.
Notes

Comments
Input
Filter <none>
Weight <none>
Split File <none>
treated as missing.
Cases Used
Syntax
CROSSTABS
/TABLES=Q2_3 BY Q35_5
/FORMAT=AVALUE
TABLES
/STATISTICS=CHISQ
/CELLS=COUNT COLUMN
/COUNT ROUND CELL.
Resources
152.
153.
154.
156.
157.
158.
Notes
Comments
Input
Filter <none>
Weight <none>
Split File <none>
treated as missing.
Cases Used
Syntax
MULT RESPONSE
Q3_3 Q3_4 Q3_5 Q3_6 Q3_7
Q3_8 Q3_9 Q3_10 (1))
/VARIABLES=Q5(0 1)
Q5
/CELLS=TOTAL
/BASE=CASES.
Resources
159.

160.
162.
163.
164.
Case Summary
Cases
Valid Missing Total
$After_arriving*Q5 26 43.3% 34 56.7% 60 100.0%
165.
166.
$After_arriving*Q5 Crosstabulation
Did you use
the Holiday
Guide for
the Lights
Festival?
No
After_arrivinga
After arriving at the Lights Festival, which activities do you now plan on
participating in? (Select...-Lights Festival Lane
Count 4
% of Total 15.4%
participating in? (Select...-BMO Harris Bank Stage
Count 1
% of Total 3.8%
participating in? (Select...-Tree Lighting Parade
Count 2
% of Total 7.7%
participating in? (Select...-Fireworks Spectacular
Count 2
% of Total 7.7%
participating in? (Select...-In-Store Events
Count 0
% of Total 0.0%
participating in? (Select...-Shopping
Count 0
% of Total 0.0%
participating in? (Select...-Canned Food Drive
Count 0
% of Total 0.0%
participating in? (Select...-Holiday Carol
Count 0
% of Total 0.0%
participating in? (Select...-BMO Community Art Project
Count 0
% of Total 0.0%
participating in? (Select...-Other
Count 0
% of Total 0.0%
Total
Count 4
% of Total 15.4%
167.
Did you use
the Holiday
Guide for
the Lights
Festival?
Yes
After_arrivinga
Count 7
% of Total 26.9%
Count 7
% of Total 26.9%
Count 17
% of Total 65.4%

Count 13
% of Total 50.0%
Count 6
% of Total 23.1%
Count 15
% of Total 57.7%
Count 3
% of Total 11.5%
Count 3
% of Total 11.5%
Count 2
% of Total 7.7%
Count 1
% of Total 3.8%
Total
Count 22
% of Total 84.6%
168.
Total
After_arrivinga
Count 11
% of Total 42.3%
Count 8
% of Total 30.8%
Count 19
% of Total 73.1%
Count 15
% of Total 57.7%
Count 6
% of Total 23.1%
Count 15
% of Total 57.7%
Count 3
% of Total 11.5%
Count 3
% of Total 11.5%
Count 2
% of Total 7.7%
Count 1
% of Total 3.8%
Total
Count 26
% of Total 100.0%
169.
Percentages and totals are based on respondents.
a. Dichotomy group tabulated at value 1.
170.
171. CROSSTABS
172. /TABLES=Q5 BY Q3_3
173. /FORMAT=AVALUE TABLES
174. /STATISTICS=CHISQ
175. /CELLS=COUNT COLUMN
176. /COUNT ROUND CELL.

177.
178.
179.
180.
Notes
Comments
Input
Filter <none>
Weight <none>
Split File <none>
treated as missing.
Cases Used
Syntax
CROSSTABS
/TABLES=Q5 BY Q3_3
/FORMAT=AVALUE
TABLES
/STATISTICS=CHISQ
/CELLS=COUNT COLUMN
/COUNT ROUND CELL.
Resources
181.
182.
183.
Notes
Comments
Input
Filter <none>
Weight <none>
Split File <none>
treated as missing.
Cases Used
Syntax
CROSSTABS
/TABLES=Q5 BY Q3_6
/FORMAT=AVALUE
TABLES
/STATISTICS=CHISQ
/CELLS=COUNT COLUMN
/COUNT ROUND CELL.
Resources
184.

185.
186.
188.
189.
190.
Notes
Comments
Input
Filter <none>
Weight <none>
Split File <none>
treated as missing.
Cases Used
Syntax
MULT RESPONSE
Q2_2 Q2_3 Q2_4 Q2_5 Q2_6
Q2_7 Q2_8 Q2_9 Q2_10 (1))
/VARIABLES=Q41(4 5)
/CELLS=TOTAL
/BASE=CASES.
Resources
191.
192.
194.
195.
196.
Case Summary
Cases
Valid Missing Total
$Prior*Q41 54 90.0% 6 10.0% 60 100.0%
197.
198.
What is
your
gender?
Male
Priora
Count 9
% of Total 16.7%
Count 8
% of Total 14.8%
Count 12
% of Total 22.2%

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