THE NEW ZEALAND CONSUMER MARKET
FOR CUT FLOWERS IN THE 90's
Charles G Lamb 1
Dennis J Farr
Patrick J McCartin3
Research Report No. 212
January 1992
Agribusiness & Economics Research Unit
PO Box 84
lincoln University
CANTERBURY
Telephone No: (64) (3) 325 2811
Fax No: (64) (3) 325 3847
2
3
Charles G Lamb is a Senior Lecturer in Marketing in the Department of Economics
and Marketing at Lincoln University.
Dennis J FaIT is a Lecturer in the Department of Horticulture at Lincoln University.
Patrick J McCartin is a Private Computer Consultant.
ISSN 1170 7682
AGRIBUSINESS & ECONOMICS RESEARCH UNIT
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policy.
AERU MANAGEMENT COMMITTEE 1992
Professor A C Bywater, B.Sc., Ph.D.
(Professor of Farm Management)
Professor A C Zwart, B.Agr.Sc., M.Sc., Ph.D.
(Professor of Marketing)
R L Sheppard, B.Agr.Sc. (Hons), B.B.S.
(Assistant Director, AERU)
•
AERU STAFF 1992
Director
Professor AC Zwart, B.Agr.Sc., M.Sc., Ph.D.
Assistant Director
R L Sheppard, B.Agr.Sc. (Hons), B.B.S.
Research Officers
G Greer, B.Agr.Sc. (Hons)
T P Grundy, B.Sc. (Hons), M
Research Officers
J R Fairweather. B.Agr.Sc., BA, M.A., Ph.D.
S. S. F. Gilmour, BA, MA (Hons)
T. M. Ferguson, B.Com. (Ag)
Secretary
J Clark
CONTENTS
Page
(i)
UST OF TABLES
(iii)
LIST OF FIGURES
(v)
PREFACE
(vii)
ACKNOWLEDGEMENTS
(ix)
SUMMARY
CHAPTER 1
CHAPTER 2
INTRODUCTION
1
1.1 Influences on Consumer Purchase and New Zealand's
Changing Society
1
RESEARCH METHODOLOGY
3
2.1
2.2
2.3
2.4
The Sample
The Questionnaire
The Interviews
The Analysis
3
3
3
4
2.4.1
2.4.2
2.4.3
Univariate and Bivariate Analysis
Multivariate Analysis
Cluster Descriptions
4
4
4
2.4.3.1
2.4.3.2
2.4.3.3
2.4.3.4
2.4.3.5
5
5
5
6
2.4.3.6
2.4.3.7
Cluster One: Older Males, Less Active
Cluster Two: Young Actives
Cluster Three: Single Women (20-50)
Cluster Four: Outdoor Men
Cluster Five: Middle-Aged and Older
Housewives
Cluster Six: Young Males
Cluster Seven: Middle -Aged
2.5 Factor Descriptions
6
6
6
7
CHAPTER 3
SURVEY RESULTS
9
3.1 Introduction
3.2 General Purchase Behaviour
3.2.1 Frequency of Purchase
9
9
9
3.3
3.4
3.5
3.6
3.7
3.8
3.9
3.10
Reasons for Flower Purchase
Major Competitors for Cut Flowers
Popular Flower Types and Colours
Cost of Most Recent Purchase
Purchase Outlet
Quality and Price Perceptions of VariOllS Outlets
Why Individuals do not buy Cut Flowers
Summary
10
12
14
15
16
17
18
19
20
REFERENCES
APPENDIX ONE
QUESTIONNAIRE
21
APPENDIX TWO
TECHNICAL DETAILS
31
LIST OF TABLFS
Page
No.
1
2
3
4
5
6
7
8
Frequency of Cut Flower Purchase
Reasons for Cut Flower Purchase
Alternatives for Cut Flowers by Reason for Cut Flower Purchase
Most Popular Flower Types
Favourite Flower Colour
Amount Spent on Most Recent Cut Flower Purchase
Outlet of Last Flower Purchase
Reasons for Not Buying Cut Flowers
A2-1 Cluster Demographic Description
A2-2 Demographics of General Purchase Patterns
A2-3 Frequency of Flower Purchase and Associated
Demographic/Psychographic Details of Cut Flower Buyers
A2-4 Cluster Description of Reasons for Buying Cut Flowers
A2-5 Cluster Description of Most Popular Flower Types
A2-6 Cluster Description by Amount Spent on Most Recent
Cut Flower Purchase
A2-7 Outlet Cut Flower Purchased from by Frequency of Purchase
and Cost of Purchase
A2-8 Cluster Description by Outlet of Last Flower Purchase
A2-9 Demographic and Psychographic Details of Those not
Buying Cut Flowers
i
10
11
13
14
15
16
17
18
32
34
35
36
37
38
39
40
41
LIST OF FIGURES
Page
No.
A2-1
Perceptions of Respective Retail Outlets
iii
42
PREFACE
The Agribusiness & Economics Research Unit (AERU) has a close relationship with the
Department of Economics & Marketing and assists with research within the Department and
the publication of research results. This Research Report presents the results of research
carried out in the Marketing Section of the Department and represents the outcome of
research which was undertaken through the use of marketing undergraduates in the course
of their study during 1989.
The practical application of research techniques by
undergraduates is seen as a central part of teaching in the marketing skills area.
The AERU is pleased to be able to publish the results of the work both from the point of
view of presenting material of relevance to investors in the cut flower industry and in the
practical demonstration of the use of research techniques to analyse consumer demand.
A C Zwart
DIRECTOR
v
ACKNOWLEDGEMENTS
The author wishes to acknowledge the considerable time and effort put in by the following
undergraduate and postgraduate students. Apart from carrying out the interviews, they also
participated in the design and coding of the questionnaire.
CAdam
M Aitchison
EAng
P Bishop
L Brooks
T Chaffey
A Chambers
L Chin
D Clark
R Clark
P Caddaro
S Crosson
W Dodson
A Domingo
W Dowling
A Drayton
KEllett
D Ellison-Smith
E Fermin
M Francis
H Fraser
C Hamilton
B Hargreaves
M Harris
G Hay
S Hayes
R Hill
E Heywood
E Jervis Holguin
P Jones
F Kalma
C Kyle
J Lake
A Lamers
R Ludbrook
C MacDonald
G McFelin
R McIntosh
R McMillan
S Neal
B Nugroho
A Plunket
GRoss
J Roy
BRyan
H Scott
R Small
G Stevens
R Stewart
J Swinbum
RSyme
M Thomas
E Ward-Smith
S Waters
A Wilkinson
Thanks also to Ms S Clemes for entering the data.
G G Lamb
September 1991
vii
SUMMARY
This report presents infonnation about cut flower purchase behaviour and was obtained from
a survey of Christchurch households. Whilst primarily being a segmentation study, a
comparison is also made with a Dutch consumer research programme.
The focus for this segmentation study was lifestyle segments with differing purchase patterns
being observable across the different groups. These purchase patterns include frequency of
purchase, retail outlet, price sensitivity as well as reason for purchase. In analysing reason
for purchase, attention has been paid to the importance of "situation" or "occasion" as a
purchase detenninant.
Other information presented in this report included popularity of flower variety and colour
preferences. The study concludes with possible suggestions for alternative marketing
strategies targeted at the different market segments.
ix
CHAPTER 1
INTRODUCTION
Production of cut flowers in New Zealand is generally believed to have increased several-fold
during the past decade. Support for this belief can be gained from statistics of annual value
of export cut flowers over this period, which show steady growth. It can be presumed that
there must have been growth in sales on the local New Zealand market also, but there does
not appear to be any published data to show this. If the cut flower industry is to continue
successful development, it is desirable that a sound local market is established as well as
continued growth in exports. Such aims will be more readily achieved if adequate, reliable
information is available.
At present there is very little published information about the New Zealand cut flower market
in terms of either its structure or purchaser behaviour. A small survey of the public in
Christchurch by Kissel (1988) provided some initial information about flower purchase
behaviour and this was useful in determining approaches used in the study described in this
report. Van Tilburg (1984), in a very comprehensive study of consumer behaviour in choice
of cut flowers and pot plants in the Netherlands, has drawn some useful conclusions with
respect to that market. For example about 36% of households were habitual buyers,
purchasing flowers about once per week. Seventy-five percent of flower purchases were for
the home and 25% for gifts. In addition, Chrysanthemums were the most popular flower
type, making up 25% of total purchases, while only five other crops, freesias, tulips, roses,
carnations and daffodils, accounted for 60%. All other flowers made up less than 20% of
total purchases.
The main objective of this study was to determine whether such patterns as shown by Van
Tilburg can be found in a culture such as that in New Zealand. In addition we aimed to
determine if there are particular market segments which can be defined in terms of cut flower
purchase behaviour.
Such information will enable industry participants to better understand the attitudes towards,
and perceptions of, cut flower products by New Zealanders. As a result it should be possible
to develop marketing strategies, appropriate for those segments identified, as a means of
establishing a more clearly defined and sound local market.
This paper continues by describing the influence on consumer behaviour of changes in New
Zealand society, and then describes a methodology for developing a market segmentation
strategy for the cut-flower market.
1.1
Influences on Consumer Purchase and New Zealand's Changing Society
It has become accepted in recent years that the average consumer is a sophisticated and
complex individual. Understanding and explaining influential factors on consumer choice
behaviour has become more important for the marketing manager wishing to improve his
business performance.
1
2
These influential factors, often referred to as environmental (Loudon and Della Bitta), are
things such as culture, social class, family influence as well as changing demographic and
life style patterns. For example, van Tilburg's study highlights some major differences in
flower purchase behaviour between New Zealand and the Netherlands. One explanation for
this difference is the obvious cultural diversity between the two countries.
Another environmental factor which Engel et al (1990) consider important is situational
influence on consumption. Examples of this in flower purchase behaviour would be buying
roses on Valentines Day or flowers for a funeral. The effect of situational determinants on
cut-flower purchase behaviour is explicitly described in later sections of this report.
In order to take account of these environmental factors, other than situation, it is important
to initially discuss the changes in New Zealand which are likely to have some impact on
businesses through the 1990's.
In a study by Feigler et al in 1990, the impact of change in New Zealand Society was
highlighted. It was noted that there has been a marked shift from the restless, fast-pace days
of the 1980's. That was a decade of yuppies and dine's, of significant and rapid change, of
wealth polarisation, of high fliers and BMW's, and of technology affecting and fragmenting
families. The 1990's is recognised for the eclectic shift in life style, the move to family and
quality of life. Technology in the 90's is being used to simplify life styles. There is a move
from confrontation and self-focus of the 80' s to co-operation and enjoyment in the 90' s. The
days of high income and no children are passing as couples in their 30's, previously dines,
are now deciding to have children, with a consequent greater choice of family-work-career
alternatives. Consumers are purchasing more products which relate to their interests, family
and enjoyment of life eg health, fitness, and food. Quality of products and service is
becoming more important.
Whilst it has become more recently recognised that solely relying on demographics as a basis
for market segmentation is unwise, the characteristics of the population, and changes in these
characteristics, is still very important. In recent years New Zealand has experienced a
reduction in the rate of population growth as well as a move towards an older population.
There has also been a reduction in the size of households and a change in family
relationships. This is exemplified with the increase in ex nuptial births and children staying
longer at home. The northern-urban drift continues, and, as well as an increase in the
average educational level of the population, the continued increase of women in the work
force is noticeable.
All of these changes in society will have a major impact on the sale of goods and services
in New Zealand throughout the 1990's. The implication for producers, wholesalers and
retailers is the necessity to take account of these changes in considering their future market
opportunities. In light of this necessity this study explores a market segmentation
methodology based on psychographic and demographic information from the Christchurch
urban population. The report concludes with suggestions for possible market strategy
formulation.
CHAPTER 2
RESEARCH METHODOLOGY
The research programme followed a two stage design similar to those proposed by Churchill
(l987) and Aaker et al (l986). The first exploratory stage provided an extensive background
to the cut flower industry through both qualitative techniques and searching relevant
secondary information. The qualitative approach took the form of non-directive discussions
with members from various sectors of the flower industry. This included producers,
wholesalers and retailers, and provided valuable insights into the industry and its problems.
The literature search encompassed areas such as industry statistics, trade association
information and relevant consumer studies. Following this preliminary phase, and using
information from it, a survey was designed to elicit information from the Christchurch
population.
2.1
The Sample
The population was defined as all adults in the Christchurch area aged 18 years and over.
The sampling unit from which these individuals were drawn was each household. The
planned sample of 684 households was drawn as follows:
1.
Using Wises Directory (l979), Christchurch was divided into fifty-seven suburbs.
2.
These suburbs were then allocated among five stratal.
3.
The number of interviews drawn per strata and suburb were calculated proportionately
on the number of streets per strata and suburb. From each suburb an address was
randomly selected as a starting point for the required number of interviews. Every
dwelling to the right of the start-point (on exit) was interviewed until the required
number was achieved.
2.2
The Questionnaire
A four page questionnaire of 140 variables was used after pilot testing and redrafting. The
questionnaire elicited responses regarding purchase behaviour, care, usage, quality and price
perceptions of cut flowers. Respondents were also asked to provide psychographic and
demographic information. A copy of the questionnaire is attached as Appendix One.
2.3
The Interviews
The interviews were carried out on 29th and 30th April 1989. The team of interviewers was
IThe suburbs were divided into five strata based on socio-economic data supplied by the
Sociology Department, University of Canterbury.
3
4
made up of 57 senior Lincoln College students. A total of 664 interviews were completed
of which 647 were usable after editing and coding. The final sample has a tolerable error
level of 4% at the 95% confidence interval.
2.4
The Analysis
The data was coded and edited for computer analysis. This analysis took the form of
univariate, bivariate and multivariate techniques within the SAS computer package.
2.4.1
Univariate and Bivariate Analysis
The results were initially analysed in marginal frequency form. Chi-square tests were used
to examine the relationships between variables and only those statistically significant at the
90% level of confidence are presented.
2.4.2
Multivariate Analysis
Both factor and cluster analysis were performed on the data using the SAS computer
package.
The psychographic lifestyle information collected in question twenty of the questionnaire was
used as input for the clustering method. The clustering approach taken followed the
procedure suggested by Punj and Stewart (1983). Initially an average linkage hierarchical
procedure was used which provided an indication of a candidate number of clusters and
cluster centroids, but more importantly, it identified a number of outlying cases. After
removing the outliers, a 'K' means, geometric iterative partitioning method was used on the
seven candidate number of clusters selected. Seven clusters were selected from the initial
method on the basis of variance reduction and interpretability. Descriptions of the seven
clusters are outlined below.
Factor analysis was performed on those variables which provided indications of how
respondents felt when receiving flowers. This reduced the twenty seven variables concerned
to three factors. Principal components analysis was used as a first factor method to suggest
a likely number of factors. On the basis of eigenvalue reduction and common constructs
within factors, it was decided to use a maximum likelihood factor method incorporating a
varimax rotation, on three factors. An explanation of the three resultant factors are outlined
below.
2.4.3 Cluster Descriptions
Although the clusters were developed on the basis of lifestyle activities they are also
described by their demographic characteristics. The description of each cluster relates to the
characteristics which predominate in that cluster more than the sample average. However,
it should be noted that the characteristics do vary within each cluster. For a detailed
description of the clusters refer to Appendix 2, Table A2-1. The cluster sizes are as follows:
5
Cluster
Number of Respondents
1
2
3
4
5
6
7
TOTAL
2.4.3.1
%
109
65
69
44
144
71
95
19.2
11.4
12.2
7.8
20.1
12.5
.16.8
567
100.00
Cluster One: Older Males, Less Active
This cluster is comprised of older individuals, 50 plus, predominantly males, who exhibit a
less active lifestyle. They tend to occupy themselves with passive "at-home" activity such
as gardening, reading etc. This group has the highest level of retired individuals and a large
number of beneficiaries. Cluster One's educational level is one mainly of primary and
secondary education. As expected there are a larger number of widows and widowers in this
cluster and in line with their age, income is also somewhat lower.
2.4.3.2
Cluster Two: Young Actives
This cluster exhibits an extremely active lifestyle. They are very exercise conscious, being
keen joggers, playing both solo and team sports frequently, yachting, tramping and surfing.
Cluster 2 are the most avid snow-skiers and also enjoy swimming and visiting beaches. This
group also appear to be the most social, "going out on the town" frequently, attending parties
and visiting friends. This group are also the most conscious oftheir appearance, frequently
buying fashionable clothes. Whilst their main media interest is watching TV2, a common
past time is either watching or listening to sports. This group is comprised of a large
number of males under the age of 30. Their educational level is reasonably high consisting
of university entrance, higher school certificate, degree and trade qualifications. Although
there are some students in this group, accounting for the high proportion of household
income under $10,000 per annum, the majority of cluster two are employed in
professional/managerial, clerical, sales and service areas. As a consequence this cluster also
has a high proportion of its members residing in households where gross income is over
$40,000 per annum. There is a very low level of married individuals in Cluster Two with
a consequently high proportion of single, separated and divorced individuals.
2.4.3.3
Cluster Three: Single Women (20-50)
This cluster is composed primarily of females in the 20 to 50 age group. They tend to have
a reasonably high level of education, with university entrance, higher school certificate,
degree or trade qualifications.
As a consequence the majority are employed in
professional/managerial areas or in service vocations. Cluster Three has a high percentage
of its members earning $20,000 to $30,000 per annum and also more than $45,000 per
6
annum. This group has a high percentage of single, separated and divorced members as well
as those living in defacto relationships. Members of this group frequently go walking, go
to the movies, read novels, dine out and go shopping just for fun. Whilst this cluster are
avid Listener readers, they have the lowest frequency of television viewing behaviour, of
either television channel.
2.4.3.4
Cluster Four: Outdoor Men
This group exhibits an outdoors life-style, frequently fishing, hunting, power boating and
camping. They are predominantly males in the thirty to fifty age group. They are
employed, in the professional/managerial, clerical, technical, services and tradesman
occupations. Generally, their education level is one of secondary level only. They fall
predominantly in the $30,000 to $50,000 income groups and have higher than average
married and defacto marital status.
2.4.3.5
Cluster Five: Middle-Aged and Older Housewives
This group has a high percentage (approximately 60%) of its individuals aged forty years and
over. They tend to have passive interests, working in the garden, making handcrafts and
spending time on hobbies. These individuals frequently watch TVI and read the
Christchurch Star. Whilst a number have only a secondary education with school certificate,
this group also contains a large number of individuals who have attended training college.
There are a high number of beneficiaries, housewives and widows or widowers in this group.
The gross household income levels of this cluster fall predominantly in the $10,000 to
$20,000 and $25,000 to $35,000 salary ranges.
2.4.3.6
Cluster Six: Young Males
This cluster has a high percentage (65%) under the age of thirty. The group is comprised
mainly of males who frequently visit "pubs", and do not like visiting relatives or working
in the garden. These individuals are qualified to university entrance and higher school
certificate standard and vocations can be described as either tradesmen, labourers,
unemployed or students. Consequently their gross household incomes are either very low,
Le. under $10,000 per annum, or at a medium level, $35,000 to $40,000. This group
consists predominantly of individuals who are either single, separated or divorced.
2.4.3.7
Cluster Seven: Middle-Aged
This cluster has a high number of individuals in the 30 to 40 age group and also aged 50 and
over. There is a higher than average number of individuals who are retired or housewives,
and associated with this is a higher than average level of married and widowed individuals
in this group. Cluster Seven has a reasonably high level of education having a larger than
average number who have a university degree or training college qualification. This group
have quite passive life-styles, reading the Christchurch Press frequently and listening to the
National Radio programme. Cluster Seven has a high percentage of its households grossing
$35,000 to $50,000 and $60,000 plus per annum.
7
2.5
Factor Descriptions
Three distinctively different factors were identified from the twenty-seven feeling variables
which were used as input in the factor analysis.
The first factor described as a "Romantic Factor" accounted for the most variation in the
twenty-seven input variables. The main variables contributing to this factor were those
indicating feelings of being loved, feeling important, special, uplifted, thrilled, happy,
emotional, cheerful, excited, bright etc.
Factor two is one described by feelings of anger, suspicion, embarrassment, blandness and
feelings of inappropriateness.
The third factor is one associated with bereavement and highlight those variables associated
with feelings of tearfulness, sadness, depression and general feelings of "nothing".
CHAPI'ER 3
SURVEY RFSULTS
3.1
Introduction
The following section reports the findings of the survey under six general headings. These
are:
(1)
(2)
(3)
(4)
(5)
(6)
general purchase behaviour,
effects of situation on buying behaviour,
popular flower types,
cost considerations,
distributional considerations and aspects of quality,
non purchase behaviour.
Appendix two contains specific tabular results pertaining to the fmdings reported in the
following section.
3.2
General Purchase Behaviour
The majority of the population (84 percent) have purchased cut flowers at some time in the
past, and it appears that a slightly larger percentage of purchasers are female (87 percent)
rather than males (80 percent). When examined on the basis of age and by cluster it appears
that younger more active individuals are flower buyers. For instance, of those who purchase
flowers, 50 percent are aged between twenty and thirty-nine years of age. Sixty-nine percent
of flower buyers are aged between twenty and forty-nine. The clusters with the largest
buying percentages were Cluster Two (91 percent) and Cluster Three (96 percent). (See
Appendix Two, Table A2-2 for a detailed breakdown.)
3.2.1 Frequency of Purchase
The majority of the population (56 percent) purchase flowers three to four times per year or
more frequently. However only approximately 15 percent of the population purchase flowers
once per month or more often. (Table 1 refers.)
9
10
Table 1
Frequency of Cut Flower Purchase
Cluster
3
2,3
3,5
1,2,5
4,6
4,6
1,4,6
Frequency
%
Once per week
Once per fortnight
Once per month
Once every two months
3-4 times per year
Twice per year
Once per year
Less often
Don't buy
2.9
0.6
11.6
9.3
23.1
11.9
13.9
10.5
16.1
TOTAL
Valid cases
Van Tilbufg
36.0
100.0
= 646
When frequency of purchase is analysed by demographic and psychographic indications, it
is interesting to note females tend to purchase flowers with greater frequency, i.e. at least
once every two months or more often. Consequently male flower buyers purchase flowers
less frequently. It is also apparent that those aged between twenty and fifty years of age
purchase flowers with greater frequency. These individuals also exhibit fairly active lifestyles. The older, less active members of the public tend to purchase flowers less frequently,
i.e. once per year or less often. Table A2-3 in Appendix 2 provides a detailed analysis of
purchase frequency. When frequency of purchase is analysed by cluster membership it is
apparent that clusters two and three are more frequent purchasers of cut flowers. (Table A23 in Appendix 2 refers.)
A comparison is provided in Table 1 of the frequency of flower purchase observed by Van
Tilburg (1984) in his study of flower purchase in the Netherlands.
3.3
Reasons for Flower Purchase
It is considered that specific situations or occasions such as Mothers' Day, St Valentine's
Day etc are important determinants of flower purchase behaviour. In observing the reasons
for purchase of flowers, the behaviour has been divided up into "degrees" of occasion.
Zero-degree occasions are defined as those for which a number of alternatives could be given
at any time. First-degree occasions are those for which flowers are commonly given, and
second degree occasions are those for which flowers may more commonly be given. Table
2 provides a detailed analysis of reasons for cut flower purchase.
11
Table 2
Reasons for Cut Flower Purchase
Zero Degree
Occasion
Reason
%
Birthday
Impulse
As a gift
For the home
Christmas
To say 'Thank you'
15.0
5.0
Total
11.0
11.2
VT
75.0
0.7
3.4
46.3
First Degree
Occasion
For funeral
Visit hospital or someone ill
St Valentine's Day
To give female/male friend
As a romantic gift
Visit a grave
Flowers for a wedding
11.7
11.4
1.9
6.0
1.9
2.3
0.7
35.9
Second Degree
Occasion
To cheer someone up
For Mothers' Day
Anniversary
For birth of a baby
2.2
1.5
4.5
2.9
11.1
Other
100.0
Valid Responses
Note:
100.0
= 580
Percentages are expressed relative to the total number of responses. Allowance was
made for respondents to make two responses.
12
It can be seen from Table 2 those reasons for purchase which are not strongly occasionbased, Le. Zero Degree Occasions, are virtually equal in number to the occasion-based
reasons. As is indicated by a comparison to the results of Van Tilburg's (1984) study, New
Zealand has exhibited a more "occasion based" purchase behaviour.
When the segments, or clusters, are analysed by buying occasion some interesting patterns
are noted. For instance, clusters one and seven share similar purchase behaviour. This tends
to be associated with specific occasions such as funerals, hospital visits, grave visits,
anniversaries and birth of a child. Clusters two and three are more associated with zero
degree occasions. These seem to be more "one-off" impulse type purchases, such as gifts,
for the home or romantic presents. Cluster four appear to mix their purchases across
traditional flower buying occasions and occasional "non-flower" situation type purchases.
Clusters five and six are more traditional situation flower buyers. Table A2-4 in Appendix
2 describes this behaviour in more detail.
3.4
Major Competitors for Cut Flowers
It is also possible to identify the major competitive products for cut flowers for the broad
groups of reasons identified above. Table 3 provides an indication of alternative products
individuals might select instead of cut-flowers. Cut flowers have an advantage in those
purchase situations where "nothing" is cited by a larger percentage of the sample, for
example "flowers for a wedding", "visit to a grave", "for funeral, "Mothers Day", etc.
13
Table 3
Alternatives for Cut Flowers by Reason for Cut Flower Purchase
Reason
Major Alternatives2
Birthday
No specific Alternative (all have equal weighting)
Impulse
Nothing (50%) Chocolate (15%)
As a gift
Chocolate (34%) Nothing (25%) Small gift (18%) Pot Plant (7%)
For the house
Nothing (52%) Pot Plant (10%) Dried Flowers (8%)
Christmas
No specific alternative (all have equal weighting)
To say 'thank you'
Chocolate (50%) Nothing (25%) Wine (12.5%)
For funeral
Nothing (61%) Donations (12%)
Visit hospital/someone ill
Nothing (32%) Fruit (25%) Chocolate (16%) Pot Plants (7%)
St Valentine's Day
Chocolate (38%) Nothing (25%) Small gift (25%) Card (12%)
To give female/male friend
Chocolate (42%) Nothing (29%) Small gift (8%)
As romantic gift
Nothing (57%) Chocolate (29%)
Visit a grave
Nothing (100%)
Flowers for wedding
Nothing (100%)
To cheer someone up
Chocolate (25%) Nothing (17%)
For Mothers' Day
Chocolate (60%) Pot Plant (40%)
Anniversary
Chocolate (37%) Nothing (26%)
For birth of baby
Chocolate (33%) Nothing (17%) Fruit (8%) Cards (8%) Dried flowers (8%)
pot plant (8%)
Valid Cases
= 464
20nly those alternatives receiving more than 5% of total respnses for that reason are
included.
14
3.5
Popular Flower Types and Colours
It can be seen from Table 4 Carnations and Roses seem to be the most favoured type of
flower. This table compares what individuals last purchased with what their favourite types
are.
Interestingly, both VanTilburg's study and this research demonstrate a similar total
percentage of individuals purchasing five common flower types.
Table 4
Most Popular Flower Types
Cluster
6,3,2
4,1
7,5,4
7,4,1
6,3,1
6,1
7,3
7,6,4
6,5,2
6,5,4,3,1
3
6
6
2
7,4
Flower Type
Leucodendron
Roses
+
Chrysanthemums
Carnations
+
Lillies
Daffodils
+
Tulips
+
Daisies
Gladiolus
Gypsophila
Orchids
Freesias
+
Geraniums
Iris
Aster
Protea
Dahlia
Cornflowers
Limonium Caspea
Violets
Jonquil
Mixed Bunch
Posie Bowl
Spring flowers
Whatever's in season
Other
+
Valid responses
Note:
Last Purchase
=
= 61.2
TOTAL
Favourite Type
0.6
20.6
6.9
37.8
0.9
1.6
0.3
2.2
1.9
4.0
3.0
0.9
0.2
0.2
0.5
0.2
0.5
0.3
0.2
0.2
0.2
12.2
0.2
1.3
1.9
1.2
0.2
33.5
5.4
25.2
3.2
4.9
2.0
2.2
1.9
1.4
3.3
4.6
0.2
1.1
1.0
0.4
1.8
0.4
0.1
1.0
0.2
0.2
0.0
1.7
4.2
2.2
100.0
100.0
630
Van Tilburg
*
25.0
*
*
*
*
* = 60.0
1250
Percentages expressed relative to the total number of responses. Allowance was made for
respondents to make more than one choice.
15
When those popular flower types and the cluster characteristics are looked at in detail it is
apparent that roses, daffodils, daisies, orchids, freesias, violets and iris are more preferred
by cluster two and cluster three. Whilst clusters four and five share a similar liking of
carnations and freesias, Cluster four also prefers chrysanthemums, lillies, spring flowers and
freesias. Cluster six, as with clusters one and two, likes roses but also shows a demand,
greater than the average population, for daffodils, tulips, gladiolis, orchids, and freesias.
Clusters one and seven with its older core population has a varied preference for flower
types. (Table A2-5 in Appendix 2 refers.)
Table 5 indicates that red, pink and yellow are the most preferred flower colours.
Table 5
Favourite Flower Colour
Colour
%
Red
Pink
Yellow
White
Blue
Purple
Orange
Pastels
Bright
Other
No specific favourite
32.2
19.6
15.3
8.9
TOTAL
3.9
3.7
3.0
1.4
0.4
1.9
9.7
100.00
Valid Response = 980
Note:
Percentages are expressed relative to the total number of responses. Respondents
could indicate more than one preferred colour.
3.6
Cost of Most Recent Purchase
As is apparent from Table 6 the majority of the buying population (53 percent) spend less
than $10.00 on an average flower purchase.
16
Table 6
Amount Spent on Most Recent Cut Flower Purchase
Amount
%
$1.00 to $4.99
$5.00 to $9.99
$10.00 to $14.99
$15.00 to $19.99
$20.00 to $24.99
$25.00 to $29.99
$30.00 to $34.99
$35.00 to $39.99
$40.00 to $44.99
$45.00 to $49.99
$50.00 to $59.99
$60.00 to $69.99
$70 and over
Don't know
Don't remark
23.8
29.6
8.7
4.8
5.9
6.3
3.7
3.0
2.3
0.2
3.0
0.6
1.1
2.0
--.iJl
100.00
Valid cases = 538
When purchase behaviour and frequency of purchase are analysed together, those individuals
purchasing flowers more frequently, Le. once every two months or more often (24 percent
of the population) generally spend less on each purchase, Le. $15.00 or less. Those who
purchase flowers less frequently, Le. twice per year or less often (36 percent of the
population) tend to spend more ($25.00 plus) on each purchase.
Clusters one and five exhibit similar flower expenditure behaviour by tending to spend less
on cut flowers. Clusters six and seven have medium to high expenditure levels on cut
flowers with clusters two and three exhibiting lower to medium flower expenditure patterns.
(Table A2-6 refers.)
3.7
Purchase Outlet
The most popular distributional outlet for purchasing cut flowers is a florist. When
respondents were questioned where they most recently purchased from it was apparent that
florists, followed by dairy's and road-side stalls were the most popular. Table 7 provides
an indication of the relative market share of cut flower outlets.
17
Table 7
Outlet of Last Flower Purchase
Cluster
Outlet
%
7,2
7,6,3,1
6,5,4,3,1
3,1
5,3
5,4,2
1
3,5,7
Florist
Dairy
Roadside Stall/Grower
Flower Barrow
Supermarket
Service Station
Restaurant
Other
57.9
17.1
12.4
4.3
3.6
3.0
0.2
---.L.2
TOTAL
100.00
Valid Cases
= 532
When analysed by frequency of purchase and dollar amount spent, the choice of cut flower
outlet follows a particular pattern. For instance, growers, road-side stalls, dairies and flower
barrows tend to be used for more frequent purchases, i.e. for purchases made once per
month or more often. Florists tend to be more popular for less frequent purchases, three to
four times per year and less often. There is a similar pattern when outlet is analysed by
amount spent on cut flowers. In this situation buyers spending under $15.00 tend to buy
from supermarkets, growers, road-side stalls, dairies and flower barrows. Those individuals
spending $25.00 or more on cut flowers almost exclusively purchase from florists. Table
A2-4 in Appendix 2 provides further information.
It is apparent that clusters three and five consider convenience and availability important
purchasing from supermarkets, stalls, fruit shops, dairies and service stations.
Clusters two and seven patronise florists more than the average population with cluster seven
also buying from dairies and fruit shops. Clusters one and six are similar in purchasing from
growers and dairies more than the average member of the population. Refer to Table A2-8
in Appendix 2 for a detailed explanation.
3.8
Quality and Price Perceptions of Various Outlets
Respondents were asked to provide an indication of expected cut flower quality and price of
various distributional outlets. To do this the respondents had to indicate on a 7 point scale
what quality and price of cut flowers they would expect from various outlets. The mean
value of each of these attributes was calculated and acted as input into a perceptual map.
18
Also included on the map are the relative market shares as shown in Figure 2-1 of Appendix
2.
It is noticeable from this that there are two general clusters of outlets, with florists being
established on their own. Supermarkets, dairies and petrol stations are one group clustered
at a medium perceived level of price and quality. Road-side stalls, growers, flower barrows
and restaurants are clustered on a similar medium-high perceived quality level, however, this
group vary a great deal on perceived price. Florists are singularly isolated with the highest
level of quality and price.
3.9
Why Individuals do not buy Cut Flowers
The single largest reason for individuals not buying cut flowers is the fact they grow their
own. (Table 8 refers.)
TABLE 8
Reasons for Not Buying Cut Flowers
Reason
%
Grow Own
Not interested
Too expensive
No need
Not a flower person
Allergic
Don't like flowers
Never thought of it
Other
36.9
8.1
TOTAL
Valid responses
6.3
16.2
5.4
1.8
4.5
6.4
14.4
100.0
= 111
From Table A2-9 in Appendix 2 it is apparent that older individuals particularly in clusters
one and five grow their own flowers and this tends to be a major factor in them not buying
flowers. It is also noticeable that it is mainly males who are not interested, don't like
flowers or don't perceive a need to buy them. When asked whether or not they intended
buying flowers in the future only 12 percent of the sample emphatically stated that they
would not. These individuals tended to be males who were aged over 60. These non future
buyers were in clusters one and seven. Again, the major reason for probably not buying in
the future related to individuals growing their own flowers. Similarly it was predominantly
19
males who definitely did not want to receive flowers at any time in the future. However,
these individuals tended to be in the thirty to sixty age group and were predominantly in
clusters one, four, six and seven.
3.10
Summary
The findings presented in this report provide information useful in the development of
marketing for the cut flower industry. By targeting appropriate segments (clusters) and using
a strategy more oriented to the individual cluster, there should be improvement in sales.
For example the following broad strategies would be appropriate.
Clusters two and three show a tendency for more frequent purchase, being primarily for nonoccasion based reasons. These individuals could be targeted in the low to medium price
range primarily by florists and those retailers with a greater convenience coverage e.g.
roadside stalls, flower barrows, dairies, supermarkets etc.
These motivations and
psychographic details provide ample opportunity for a promotion programme to be
developed.
Clusters one and seven show a tendency of less frequent purchase primarily for very specific
occasions e.g. funerals, hospital visits or birth of a child. Whilst they would purchase for
some occasions from a florist, they also are convenience and cost conscious often buying
from growers or dairies and generally spending small to medium amounts on each purchase.
Clusters five and six are similar in their type of purchase being more occasion determined
e.g. hospital visits, i.e. a gift for a partner or friend; for mothers day or birth of a child.
These two clusters do however vary a little with cluster five purchasing a little more
frequently but perhaps spending less on each purchase than cluster six. Both of these clusters
exhibit similar "convenience" behaviour purchasing from supermarkets, growers, dairies,
stalls, service stations and fruit shops.
Cluster four tends to purchase less often for a wide range of reasons, however, their
expenditure is quite low. They also tend to be "convenience" buyers.
These examples indicate the value of such segmentation study for product positioning,
pricing, promotion and distributional strategies.
REFERENCES
Aaker, D A, Day, G S (1986), "Marketing Research", Wiley, 3rd edition.
Churchill, G A (1987), "Marketing Research. Methodological Foundations". Dryden Press,
NY, 4th edition.
Engel, J F, Blackwell, R D, and Miniard, P W (1990), "Consumer Behaviour", The
Dryden Press, 6th Edition, Chap 7 pp 204-221.
Feigler, B, Lawson, R, Mueller-Heumann, G, and Rumnel, A (1989), "New Zealand into
the 1990's: A Comprehensive Survey of New Zealanders' Opinions and Lifestyles",
Readers Digest Ltd, November.
Kissel, R (1988), Market Survey Canterbmy Commercial Flower Growers' Association,
MAP Tech, Lincoln.
Loudon, D and Della Bitta, A J (1988), "Consumer Behaviour. Concepts and Applications" ,
McGraw Hill, 3rd edition, Part 3, pp 163-349.
Punj, D and Stewart, D W (1983), "Cluster Analysis in Marketing Research: Review and
Suggestion for Application", Journal of Marketing Research, 20 pp 134-148.
Tilburg, A van (1984), "Consumer Choice of Cut Flowers and Pot Plants: A Study Based
on Consumer Panel Data of Households in the Netherlands", Agricultural University
Wageningen Papers 84-2.
Wises Post Office Directory (Volume 4, 1979).
20
APPENDIX ONE
QUESTIONNAIRE
21
22
Questionnaire No.
c=J
1989 CUT FLOWER SURVEY
Good morning/afternoon, I am from Lincoln College Marketing Department.
We are doing
a survey about the cut flower market. Would you help us by answering a few questions.
Ask to speak to someone in the household who is aged 18 years or over.
If this is not
possible thank the respondent and close the interview.
FOR OFFICE
USE
1.
2.
(a)
Have you ever purchased cut flowers?
IF NO, GO TO QUESTION 3.
(b)
About how often would you buy fresh cut flowers?
Once per month [
Once per week [ ]
Once every two months [ ]
3-4 times per year [ ]
Twice per year [ ]
Less often [ ]
Once per year [ ]
No [ ]
o
o
What was the reason(s) for buying the flowers?
••••••••••••••••••••••••••••••••••••
11II
•
11II
••••••••••••••••••••••••••
(b)
What else could you have purchased instead of flowers for this
purpose?
(NOTE: PROBE FOR UP TO THREE POSSIBLE ALTERNATIVES.)
(c)
Why were flowers appropriate?
(d)
What type of flowers did you buy in this instance?
(e)
How were the flowers presented, e.g., bouquet, cut bunch,
prepackaged, etc.
.
11II
••••••••••••••••••••••••••••••••
(f)
Could you recall, very approximately, about how much they cost?
(g)
What outlet did you buy these flowers from?
GO TO QUESTION 4.
Why have you never purchased cut flowers?
•
4.
Yes [ ]
Would you please think back to the last time you purchased cut flowers.
(a)
3.
(TICK)
•••••••••••••••••••••••••••••••••••
11II
••••
0
••••••••••••••••••••••••••••
B
Are you likely to buy flowers at any time in the future?
Yes [ ]
Don' t know [ ]
No [ ]
IF NO, WHY NOT? .••.....•.............•..........................
IF NO, GO TO QUESTION 6.
o
Line 1
23
5.
I would now like to give you a card (GIVE RESPO
NDENT CARD A) and ask
you what sort of quali ty of cut flowe rs YOU WOULD
EXPECT if you bough t
them at the follow ing outle ts. Pleas e indic ate
with the appro priate
numbe r from the card.
(a)
(b)
(c)
6.
(a)
Gates Sales of Comm ercial Growe r (Road -Side Stall
) [ J
Dairy
J
Super marke t
[J
Flori st
J
Flowe r Barrow [ ]
In a Resta urant
]
Petro l Statio n [ J
I would also like you to take the secon d card and
give an
indic ation of the price of flowe rs you would expec
t if you were
to purch ase flowe rs from the follow ing outle ts.
Pleas e
indic ate with the appro priate numbe r from the card.
Dairy
[ J
Super marke t
[J
Gate. Sales of Comm ercial Growe r (Road -Side Stall
)
Flori st
[ J
Flowe r Barrow [ ]
In a Resta urant [ ]
Petro l Statio n [ J
How long would you expec t any cut flowe rs you buy
to last?
Have you ever been given flowe rs or purch ased them
for
yours elf?
Yes [ ]
No [ ]
IF NO, GO TO QUESTION 7.
o
o
Line 2
Think ing back to the last time you eithe r recei
ved flowe rs from
someo ne else or purch ased them for yours elf.
(b)
Who did you recei ve them from?
(NOTE: PROBE FOR GENDER AND
RELATIONSHIP OF THE GIVER IF NOT IMMEDIATELY OBVIO
US.)
(C)
What was the reaso n(s) for being given /purc hasin
g the flowe rs?
(d)
Give respo ndent CARD C and ask them to indic ate
how they felt
about gettin g/rec eivin g flowe rs in this situa tion
[ ]
(e)
Tick any or all of the follow ing which would descr
ibe how
you felt about gettin g/buy ing the flowe rs at that
time.
I felt speci al
[ J
I felt loved
I was suspi cious
[ J
I felt angry
I felt embar rassed
[ ]
I felt tearf ul
I felt impor tant
[ ]
I felt amuse d
I felt uplif ted
[ ]
I felt happy
I thoug ht it INapp ropria te [ ]
I felt sad
I felt confu sed
[ ]
I felt surpr ised
I felt thrill ed
[ ]
I thoug ht it appro priate
I was being thoug ht of
[J
I felt emoti onal
I felt cheer ful
[ ]
I felt brigh t
I felt depre ssed
[ ]
They cheer ed me up
I felt nothi ng
[ )
It made me remem ber
I felt excit ed
[ J
I felt bland
I thoug ht it would brigh ten up the place
[ )
o
CD
o
[
[
[
[
[
[
[
[
[
[
[
[
[
J
J
]
]
]
]
]
)
]
)
)
]
)
'--
Line 3
24
7.
Would you like to be given flowers at some time in the future?
Yes [ ]
No [ ]
Don' t know [ ]
IF NO, WH'Y NOT?
8
••••••••••••••••••••••••••••••••••••••••••••
IF NO, GO TO QUESTION 13.
8.
Tick any or all of the following which you would do when you receive
flowers, i.e., how you would look after them.
Keep in a cool place
Put them in a vase and leave them
Cut the stems
Put vinegar in water
Change the water every few days
Burn the stems
Recut the stems every few days
9.
[
[
[
[
[
[
[
Put them in cold water
Hammer the stems
Put salt in the water
Keep them in a warm place
Put them in warm water
Add a preservative to
the water
]
]
]
]
]
]
]
[
[
[
[
[
[
]
]
]
]
]
]
'--
Give respondent CARD D and ask them to indicate how they would rate
the statements using the scale on the card.
(a)
(b)
(c)
(d)
(e)
(f)
Means more to me ...
Only like particular types
Makes place brighter
Quality varies
Flowers are luxury
Flowers are feminine
[
[
[
[
[
[
]
]
]
]
]
]
Line 4
10. What are your favourite types of flower?
RECORD AS STATED.)
(ALLOW FOR THREE TYPES AND
o
o
o
l.
2.
3.
11. What are your favourite flower colours?
(RECORD FIRST TWO GIVEN.)
o
o
l.
2.
12. What characteristics do good quality flowers have?
(RECORD FIRST THREE.)
l.
.........................................................
2.
.
3.
..
.
.
13. Do you grow flowers in your garden?
14. Gender of respondent.
Male [ ]
Yes [ ]
Female [ ]
No [ ]
o
o
o
o
o
Line 5
25
15. To what age group do you belon g?
Under 20 [ ]
20 - 30 [ ]
30 - 40 [ ]
40 - 50
50 - 60
[]
60 and over [ ]
Will not discl ose
o
16. What is your occup ation?
o
o
o
17. What is the highe st level of educa tiona l quali
ficati on you have
attain ed?
,.
.
18. What is your marit al statu s?
19. What is your house hold's appro ximat e gross annua
l incom e?
less than $10,0 00 [ ]
$10-$ 15,00 0 [ ]
$15-$ 20,00 0
$20-$ 25,00 0 [ ]
$25-$ 30,00 0 [ ]
$30-$ 35,00 0
$35-$ 40,00 0 [ ]
$40-$ 45,00 0 [ ]
$45-$ 50,00 0
$50-$ 55,00 0 [ ]
$55-$ 60,00 0 [ ]
over $60,0 00
Don' t know [ ]
Will not disclo se [ ]
o
20. On the follow ing scale indic ate how often
you under take the
follow ing activ ities?
(SPEC IFY APPROPRIATE NUMBER BESID E ACTIV ITY.)
never
rarel y
occas ional ly
frequ ently very frequ ently
Line 6
1---------------1---------------1---------------1---------------1
2
3
4
5
1
Go for walks
[ ]
Go joggi ng
[ ]
Watch or listen to sport s
[ ]
Work in the garde n
[ ]
Visit pubs
[ ]
Snow ski
[ ]
Visit relat ives
[ ]
Read novel s
[ ]
Watch telev ision (chan nel 1) [ ]
Read the Chch Star
[ ]
Go tramp ing
[ ]
Play solo sport s
[ ]
Read the Chch Press
[ ]
Liste n to stere o
[ ]
Spend time on a hobby
[ ]
Go shopp ing for fun
[ ]
Watch telev ision (chan nel 2) [ ]
Exerc ise
[ ]
Liste n to Natio nal Radio Progra mme
Go to the movie s
Go fishin g
Buy fashio nable cloth es
Atten d parti es
Go hunti ng
Go yacht ing
Go out on the town
Dine out
Go power boati ng
Go campi ng
Play team sport s
Go swimm ing
Make handc rafts
Visit friend s
Go surfin g
Atten d conce rts
Visit the beach
Read the Liste ner
[ ]
[ ]
[ ]
[ ]
[ ]
[ ]
[ ]
[ ]
[ ]
[ ]
[ ]
[ ]
[ ]
[ ]
[ ]
[ ]
[
[
]
]
'--
END OF DATA MARKER
o
Line 7
INTERVIEWER NAME:
DATE:
TIME:
RESPONDENT PHONE NO:
26
CARD A
Qual itv
Very
Poor
Neith er
Poor Nor Good
Very
Good
1--- ----- 1--- ----- 1--- ----- 1--- ----- 1--- ----1 ----- --1
1
2
3
4
5
6
7
27
CARD B
Price
Very
Low
Reas onab le
Very
High
1--- ----- 1--- ----- 1--- ----- 1--- ----- 1--- ----1 ----- --1
1
2
3
4
5
6
7
28
CARD C
On the fol low ing sc ale ,
be ing giv en flo we rs in th ple ase in di ca te how mu ch bu yin g or
is sit ua tio n me an t to yo
u.
It me ant
no thi ng
to me
1------------1------------1------------1
1
2
3
4
It me ant
a gr ea t
de al
------------1
5
29
CARD D
Ple ase se lec t the num ber
clo se ly sho ws how yo u fee of the fol low ing sc ale wh ich mo st
l ab ou t the fol low ing sta
tem en ts.
Str on gly
Di sag ree
Di sag ree
Ne utr al
Ag ree
1------------1------------1------------1
1
2
3
Str on gly
Ag ree
------------1
4
5
(a)
When som eon e giv es me flo
if the y had giv en me we rs it me ans mo re to me tha n
an oth er typ e of gi ft,
ch oc ola tes , a ca rd , etc .
e.g .,
(b)
I on ly re all y lik e a pa rti
cu lar typ e of flo we r.
(c)
Ha vin g flo we rs aro un d the
ho use
br ig ht er and mo re ple as an
t.
(d)
Th e qu ali ty of
gr ea t de al.
(e)
Flo we rs are a lux ury ite m.
(f)
Flo we rs are a ve ry fem ini
ne thi ng .
cu t
flo we rs
I
ma kes the pla ce see m
ha ve rec eiv ed va rie s a
APP END IX TWO
TECH NICA L DETAILS
31
32
TABLE A2-1
Cluste r Demographic Description
Cluster
Sample
(Average)
1
2
45.0
55.0
51.0
49.0
66.2
33.8
30.4
69.6
WND
6.2
25.6
22.2
17.6
9.3
18.0
1.1
0.0
11.9
11.0
20.2
18.4
35.8
2.8
23.1
43.1
29.2
3.1
0.0
0.0
1.5
Occupation
Prof/M gr
Trades/ lab
Cler/Sales & Svc
Technical
Service Ind
Unemployed
Retired
Housewife
Studen t
Self Employed
Beneficiary
Other
WND
8.2
8.9
8.2
3.4
16.3
3.4
15.1
23.3
8.9
1.9
0.9
0.9
0.7
6.4
9.2
6.4
2.7
9.2
4.6
36.7
19.3
0.9
1.8
1.8
0.0
0.9
Education
Primar y only
Secondary only
School Cert
UElHS C
Trg Col
Trade Qual
Degree
Other
WND
4.4
25.1
17.0
21.8
2.0
9.7
14.7
2.8
2.6
12.6
34.0
20.4
12.6
0.0
3.4
8.7
2.9
4.9
Gender
Male
Females
Age
< 20
20-29
30-39
40-49
50-59
60+
3
4
5
6
68.2
31.8
12.3
87.7
69.0
31.0
45.3
54.7
7.2
43.5
29.2
20.3
5.8
0.0
0.0
6.8
13.6
31.8
27.3
4.6
15.9
0.0
0.9
14.0
24.6
20.2
13.2
26.3
0.9
14.1
50.7
18.3
15.5
1.4
0.0
0.0
1.1
16.8
25.3
16.8
11.6
27.4
1.1
13.9
10.8
12.3
3.9
21.5
6.2
0.0
3.1
27.7
1.5
0.0
0.0
0.0
13.0
4.4
8.7
7.3
26.1
2.9
1.5
18.8
13.0
1.5
0.0
1.5
1.5
13.6
18.2
11.4
4.6
15.9
0.0
20.5
11.7
2.3
0.0
0.0
2.3
0.0
1.8
1.8
4.4
1.8
17.7
0.0
14.2
51.3
27.7
1.8
1.8
0.0
0.9
8.5
16.9
11.3
1.4
14.1
9.9
0.0
9.9
18.3
5.6
1.4
2.8
0.0
7.6
8.7
7.6
4.4
14.2
1.1
20.7
27.2
5.4
1.1
0.0
1.1
1.1
0.0
10.9
7.8
50.0
0.0
12.5
17.2
0.0
1.6
1.5
13.0
10.1
27.5
1.4
14.5
26.1
1.5
4.4
2.3
32.6
16.3
14.0
2.3
16.3
11.6
2.3
2.3
5.7
28.7
25.0
15.7
2.8
7.4
5.6
7.4
1.9
2.9
27.1
15.7
24.3
0.0
10.0
18.6
0.0
1.4
1.1
24.7
16.9
16.9
6.7
10.1
20.2
2.3
1.1
(continued)
7
33
TABLE A2-1 (continued)
Cluster
Sample
(Average)
1
2
3
4
5
6
7
Gross Household
Income (000)
<$10
$10-$14.9
$15-$19.9
$20-$24.9
$25-$29.9
$30-$34.9
$35-$39.9
$40-$44.9
$45-$49.9
$50-$54.9
$55-$59.9
$60+
Don't know
WND
7.2
10.9
6.4
8.3
7.8
7.4
7.8
8.3
4.6
2.7
2.1
6.0
9.4
11.1
7.3
18.4
7.3
8.3
5.5
5.5
5.5
7.3
1.8
0.9
0.9
3.7
13.8
13.8
12.3
3.1
1.5
10.8
6.2
6.2
4.6
9.2
7.7
1.5
3.1
16.9
10.8
6.2
5.8
2.9
2.9
10.1
10.1
8.7
7.3
8.7
8.7
7.3
5.8
10.1
7.3
4.4
0.0
9.1
4.6
6.8
6.8
11.4
15.9
15.9
6.8
0.0
0.0
2.3
9.1
11.4
4.4
19.3
14.0
7.0
11.4
9.7
6.1
3.5
3.5
1.8
1.8
0.0
8.8
8.8
16.9
5.6
5.6
11.3
8.5
5.6
8.5
5.6
4.2
4.2
1.4
4.2
7.0
11.3
4.3
8.5
3.2
5.3
5.3
6.4
10.6
12.8
3.2
3.2
2.1
8.5
7.5
19.2
Marital Status
Married
Single
Sep/Div
Defacto
Widow(er)
60.8
23.3
5.9
1.4
8.7
70.1
7.5
6.5
1.9
14.0
30.8
60.0
6.2
1.5
1.5
52.9
33.8
7.4
4.4
1.5
75.0
11.4
2.3
4.6
6.8
67.5
10.5
5.3
0.0
16.7
39.4
50.7
8.5
0.0
1.4
77.7
8.5
4.3
0.0
9.6
Valid Cases
Note:
= 567
All figures are percentages.
34
TABLE A2-2
Demographics of General Purchase Patterns
Sample Average
Purchase Cut Flower
Yes
No
Gender
Male
Female
80.0
86.5
20.0
13.5
71.0
86.2
88.1
88.0
86.8
73.5
66.7
29.0
13.8
11.9
12.0
13.2
26.5
33.3
73.4
90.8
95.7
86.4
86.0
73.2
85.3
26.6
9.2
4.3
13.6
14.0
26.8
14.7
Age
<20
20-29
30-39
40-49
50-59
60+
WND
Cluster
1
2
3
4
5
6
7
Valid Cases
= 567
35
TABLE A2-3
Frequency of Flower Purchase and Associated
Demographic/Psychographic Details of Cut Flower Buyers
Once/
week
Once/
fortnight
Once/
mth
Frequency (%)
Once/
3-4/yr
2 mths
2/yr
l/yr
Less Often
Sample
Average
3.4
0.7
13.7
10.6
29.9
13.9
15.4
12.4
Gender
Male
Female
3.4
3.3
0.5
0.7
10.3
16.3
8.8
11.9
30.9
29.3
15.2
13.0
16.2
14.8
14.7
10.7
4.0
2.4
5.4
5.7
0.0
1.3
0.0
0.0
0.0
1.8
0.0
0.0
1.3
0.0
28.0
17.6
14.4
10.2
15.2
4.0
25.0
4.0
11.2
9.9
13.6
10.9
9.3
0.0
24.0
33.6
29.7
25.0
37.0
28.0
25.0
8.0
16.0
10.8
14.8
10.9
17.3
25.0
24.0
10.4
14.4
17.1
17.4
18.7
25.0
8.0
8.8
13.5
13.6
8.7
20.0
0.0
1.3
3.4
12.1
2.6
3.1
1.9
0.0
0.0
0.0
0.0
5.3
1.0
0.0
0.0
10.0
20.3
21.2
13.2
10.2
13.5
11.1
7.5
11.9
16.7
5.3
13.3
11.5
6.2
33.8
35.6
25.8
26.3
31.6
21.2
30.9
15.0
10.2
13.6
18.4
13.3
15.4
13.6
15.0
10.2
9.1
15.8
14.3
17.3
24.7
17.5
8.5
1.5
13.2
13.3
19.2
13.6
Age
<20
20-29
30-39
40-49
50-59
60+
WND
Cluster
1
2
3
4
5
6
7
Valid Cases
= 474
TABLE A2-4
Cluster Description of Reasons for
(J'
Birth-
Impulse
Occasion
Gift
day
Sample
Average
Buyin~ Cut
Flowers
Z' Occasion
1° Occasion
For
home
Xmas
Thank
You
Funeral
Hospital
Illness
Valentine
Day
Give
Male
IFemale
Romantic
Gift
Visit
Grave
Wedding
Cheer
Up
For
Mother's
Day
Anniversary
Birth
of
Child
17.6
4.6
10.2
12.3
0.9
3.7
13.4
13.0
1.9
6.3
1.6
2.5
0.9
2.8
1.2
4.4
2.8
1
16.7
2.8
12.5
8.3
0.0
4.2
18.1
15.3
0.0
4.2
0.0
4.2
0.0
2.8
1.4
5.6
4.2
2
19.6
0.0
14.3
21.4
3.6
3.6
8.9
3.6
3.6
5.4
3.6
0.0
0.0
5.4
0.0
5.4
1.8
3
19.7
9.8
13.1
16.4
0.0
4.9
6.6
8.2
3.3
6.6
3.3
1.6
0.0
1.6
0.0
4.9
0.0
4
22.2
8.3
2.8
16.7
0.0
2.8
5.6
16.7
5.6
5.6
0.0
5.6
0.0
0.0
2.8
2.8
2.8
5
12.6
3.4
8.0
16.1
0.0
5.7
19.5
17.2
0.0
2.3
0.0
3.4
0.0
2.3
3.4
1.1
4.6
6
20.8
6.3
6.3
2.1
4.2
2.1
8.3
16.7
4.2
14.6
4.2
0.0
0.0
4.2
0.0
4.2
2.1
7
17.4
4.3
11.6
5.8
0.0
1.4
18.8
l3.0
0.0
8.7
1.4
2.9
1.4
2.9
0.0
7.2
2.9
Cluster
TABLE A2-5
Cluster Description of Most Popular Flower Types
TYPE
Roses
Camations
Chrys
Lillies
Daffs
Tulips
Daisies
Spring
Gladis
Gypsoph
Orchids
Freesias
Violets
Iris
Aster
Protea
Dahlias
55.0
22.7
3.2
I.1
2.5
I.1
2.0
0.9
I.1
0.5
3.2
4.8
0.2
0.5
0.5
0.2
0.5
1
48.0
18.7
8.0
2.7
5.3
2.7
1.3
0.0
1.3
0.0
1.3
6.7
0.0
1.3
1.3
0.0
1.3
2
68.4
19.3
0.0
0.0
1.8
1.89
1.8
0.0
0.0
0.0
5.3
0.0
1.8
0.0
0.0
0.0
0.0
3
67.3
18.2
0.0
0.9
3.6
0.0
3.6
0.0
0.0
0.0
1.8
3.6
0.0
1.8
0.9
0.0
0.0
4
42.4
30.3
9.1
3.0
0.0
0.0
0.0
3.0
3.0
0.0
0.0
9.1
0.0
0.0
0.0
0.0
0.0
5
53.1
26.5
3.1
0.0
1.0
1.0
2.0
1.0
0.0
1.0
4.1
6.1
0.0
0.0
1.0
0.0
0.0
6
58.3
14.6
2.1
0.0
4.2
2.1
2.1
0.0
2.1
0.0
6.3
4.2
0.0
0.0
0.0
2.1
2.1
7
48.6
29.7
1.4
2.7
1.4
0.0
2.7
2.7
2.7
1.4
2.7
4.1
0.0
0.0
0.0
0.0
0.0
Sample
Av
Cluster
TABLE A2-6
Cluster Description by Amount Spent on Most Recent
Cut Flower Purchase
AMOUNT
$1$4.99
$5$9.99
$10$14.99
$15$19.99
$20$24.99
$25$29.99
$30$34.99
$35$39.99
$40$44.99
$45$49.99
$50$59.99
$60$69.99
$70+
26.6
31.5
9.8
5.3
6.2
6.6
3.9
3.0
2.7
0.2
3.2
0.7
0.9
1
29.6
33.8
7.0
2.8
9.9
8.5
1.4
1.4
1.4
0.0
2.8
0.0
1.4
2
19.0
37.9
10.3
5.2
8.6
3.4
1.7
0.0
5.2
1.7
1.7
1.7
3.4
3
28.1
32.8
6.3
6.3
4.7
3.1
4.7
4.7
4.7
0.0
1.6
1.6
1.6
4
12.1
48.5
15.2
6.1
0.0
9.1
6.1
3.0
0.0
0.0
0.0
0.0
0.0
5
32.6
29.3
9.8
6.5
3.3
6.5
3.3
2.2
2.2
0.0
4.3
0.0
0.0
6
24.4
28.9
8.9
6.7
6.7
11.1
4.4
4.4
2.2
0.0
0.0
2.2
0.0
7
25.3
20.0
13.3
4.0
8.0
6.7
6.7
5.3
2.7
0.0
8.0
0.0
0.0
Sample
Av
Cluster
00
(V)
TABLE 2-7
Outlet Cut Flower Purchased from by Frequency of Purchase and Cost of Purchase
Outlet
Sample Average
Florist
Supennarket
Grower Road!
Side Stall
Dairy
Flower
Barrow
Service
Station
Fruit Shop
Restaurant
Other
56.8
3.2
12.4
15.9
4.7
3.2
1.3
0.2
1.1
37.5
66.7
41.5
44.0
60.3
65.6
64.8
61.4
0.0
0.0
4.6
10.0
1.4
1.6
1.4
5.3
18.8
33.3
15.4
12.0
14.2
14.1
5.6
8.8
25.0
0.0
26.2
18.0
14.9
7.8
14.1
14.0
12.5
0.0
7.7
8.0
3.6
3.1
1.4
5.3
0.0
0.0
3.1
8.0
2.1
3.1
5.6
0.0
6.3
0.0
0.0
0.0
1.4
0.0
2.8
1.8
0.0
0.0
0.0
0.0
0.0
0.0
1.4
0.0
0.0
0.0
1.5
0.0
1.4
3.1
0.0
0.0
25.2
39.6
61.9
87.0
89.0
93.0
88.0
100.0
91.7
100.0
100.0
100.0
100.0
8.1
3.7
2.4
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
20.7
15.7
11.9
8.7
7.4
3.5
11.8
0.0
8.3
0.0
0.0
0.0
0.0
30.6
23.9
11.9
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
7.2
5.2
9.5
4.4
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.8
9.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
3.6
0.8
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.9
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.8
0.8
2.4
0.0
3.7
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Frequency
Once/week
Once/fortnight
Once/Month
Once 2 months
3-4/year
2/year
l/year
Less often
Cost of Purchase
$1-4.99
$5-9.9
$10-14.99
$15-19.99
$20-24.99
$25-29.99
$30-34.99
$35-39.99
$40-44.99
$45-49.99
$50-59.99
$60-69.99
$70 plus
Valid cases
= 474
TABLE A2-8
Cluster Description by Outlet of Last Flower Purchase
OUTLET
Florist
Super Market
Grower
Dairy
Stall
Flower Barrow
Service Station
Fruit Shop
Restaurant
58.3
3.3
3.7
16.2
9.0
4.8
3.3
1.3
0.2
1
52.6
3.9
7.9
17.1
7.9
7.9
0.0
1.3
1.3
2
66.7
1.8
1.8
15.8
5.3
3.5
5.3
0.0
0.0
3
9.4
9.4
3.1
21.3
25.0
15.6
3.1
3.1
0.0
4
44.4
2.8
5.6
16.7
13.9
2.8
13.9
0.0
0.0
5
56.4
5.3
1.1
13.8
10.6
4.3
6.4
2.1
0.0
6
59.6
1.9
7.7
17.3
9.6
3.8
0.0
0.0
0.0
7
67.1
1.3
2.6
18.4
5.3
2.6
0.0
2.6
0.0
Sample Average
Cluster
TABL E A2-9
Demo eraph ic and Psych oerap hic Details of Those not Burln e Cut
Flowers
Reason
Grow Own
Not
Interested
Too
Expensive
No Need
Not Flower
Person
Allergic
Don't Like
Flowers
Never
Thought of
Other
Sample Average
36.6
7.5
6.5
18.3
3.2
1.1
5.4
5.4
16.1
Gender
Male
Female
27.5
47.6
11.8
2.4
3.9
9.5
23.5
11.9
3.9
2.4
1.9
0.0
7.8
2.4
3.9
7.1
15.7
16.7
Age
< 20
20-29
30-39
40-49
50-59
60+
WND
0.0
15.0
20.0
25.0
100.0
66.7
0.0
10.0
5.0
13.3
0.0
0.0
7.4
50.0
0.0
20.0
13.3
0.0
0.0
0.0
0.0
60.0
10.0
20.0
33.3
0.0
3.7
50.0
0.0
5.0
6.7
0.0
0.0
3.7
0.0
0.0
0.0
0.0
0.0
0.0
3.7
0.0
0.0
20.0
0.0
0.0
0.0
3.7
0.0
10.0
10.0
13.3
0.0
0.0
0.0
0.0
20.0
15.0
13.3
42.0
0.0
11.1
0.0
Cluster
1
2
3
4
5
6
7
48.3
0.0
33.3
16.7
56.3
10.5
50.0
10.3
0.0
0.0
0.0
0.0
15.8
7.1
3.5
0.0
33.3
0.0
6.3
10.5
7.1
6.9
33.3
0.0
66.7
12.5
21.1
21.4
6.9
16.7
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
7.1
3.5
16.7
0.0
0.0
6.3
10.5
0.0
6.9
16.7
0.0
0.0
12.5
0.0
0.0
13.8
16.7
33.3
16.7
6.3
31.6
7.1
Valid Cases
= 474
42
Figure 2- 1
Perceptions of R es pe ct iv e R
etail Outlets
Qu ali ty
HIGH
7 .. .. -- -- -- -- -- -- -- -- --
-- -- -- -- -.
*
Flo ris t
/ (57.9%)
6R/S Sta ll
(12.4%)
5-
Supermarket
(3.6%)
*
*
Flower
* Bar
row
*/ Re(0.1staura%) nt
(4.3%)
I
~
I
Dairy
(17 .1% )
*
Pet rol
Sta tio n
(3.0%)
21-
LOW
1
L -_ _---1 I
1
LOW
2
--!. -
3
-.L -
4
-l.-
~I
5
6
Perceived Pr ic e
Av era ge pre fer en ce of 53 9
res po nd en ts
in Ch Ch Ho us eh old Su rve y,
Ma y 19 89
__J
7
HIGH
43
MAR KET
SEGM ENT
DETAll.S FOR STRATEGY DEVELOP:MENT
Clusters 2 and 3
More frequent purchasers, primarily impulse type buying or
non occasion based purchasing. Target low to medium prices.
Outlets using convenience (wide availability) and quality as
positioning statement. Promotion aimed at appropriate sources
(print media eg More, North and South). Advertising must
have appropriate creative content.
Clusters 1 and 7
Purchase less frequently for primarily specific occasions. Whilst
often purchase from a florist convenience of availability very
important. Tend to be more cost conscious. Less frequent
purchasers. Promotion message more appropriate to
tradition - and occasion.
Cluster 5
Tends to be more occasion based than impulse. While this
group tend to purchase slightly more frequently than average
they spend a little less than average on each purchase. This
group are very convenience oriented purchasing mainly from
outlets such as service stations, supermarkets, fruit shops etc.
Media advertising would be a Womens Weekly type of
approach.
Cluster 6
Whilst also exhibiting occasion based buying characteristics,
these individuals tend to purchase for non traditional occasions
eg birthdays, to cheer someone up, for romance, or to friend of
the opposite gender etc. They tend to spend a medium
amount on each purchase but infrequently. Media promotion
should be thought of as Hot Rod, Rugby News, or Body Builder
type of approach.
Cluster 4
This group purchases infrequently often spending quite a small
amount on each purchase for a wide range of reasons,
generally from convenience outlets. They could be thought of
as the Southern Man and a Rod and Gun type media approach.
This group would not appear to be a very profitable segment to
target.
RESEARCH REPORT
182
A Financial and Economic Survey 01 South Auckland Town
Milk Producers i1nd Factory Supply Dairy Farmers, 198485, n G Moffitt. 1986
183
An Economic Survey 01 New Zealand Town Milk
Producers, 1984-85, R G Moffitt. 1986
184
An Economic Survey 01 NZ Wheatgrowers: Financial
Analysis, 1984-85; R.D Lough. PJ McCartin. 1986
185
The Ellect on Horticulture 01 Dust and Ash: Proposed
Waikato Coal-Fired Power Station, PR McCrea. October
1986
186
A Study 01 the Determinants 01 Fattening and Grazing
Farm Land Prices in New Zealand, 1962 to 1983. PG
Seed. RA Sandrey. B.D. Ward. December 1986
•
187
Farmers' Responses to Economic Restructuring in
Hurunui and Clutha Counties: Preliminary Analysis 01
Survey Data. JR Fairweather. July 1987
188
Survey 01 NZ Farmer Intentions and Opinions, OctoberDecember 1986. J.G Pryde. PJ McCartin. July 1987
189
Economic Adjustment in New Zealand: A Developed
Country Case Study of Policies and Problems, R G
Lattimore. July 1987
197
Demand for Wool by Grade
A. C. Zwart, T. P. Grundy, November 1988
198
Financial Market Liberalisation in New Zealand: an
Overview, A. L. St Hill, December 1988.
199
An Economic Evaluation of Coppice Fuelwood
Production for Canterbury, J. R. Fairweather, A. A.
Macintyre, April 1989
200
An Economic Evaluation of Biological Control of RoseGrain Aphid in New Zealand, TP. Grundy, May 1989
201
An Economic Evaluation of Biological Control of
Sweet Brier, T P. Grundy, November 1989
202
An Economic Evaluation of Biological Control of
Hieracium, T P. Grundy, November 1989
203
An Economic Evaluation of the Benefits of Research
into Biological Control of Clematis Vitalba, G. Greer, R.
L. Sheppard, 1990.
204
The Q Method and Subjective Perceptives of Food in
the 1990s, J. R. Fairweather 1990
205
Management Styles of Canterbury Farmers: a study of
goals and success from the farmers' point of view. J. R.
Fairweather, N: C. Keating, 1990
206
Tax Shields: their implications for farm project investment,
risk and return. P. A. McCrea, T P. Grundy, D. C. Hay, 1990
190
An Economic Survey
of New Zealand Town Milk
Producers 1985-86, A.G. Moffitt, November 1987.
191
The Supplementary Minimum Price Scheme: a Retrospective Analysis, G.A. Griffith, T.P. Grundy,
January 1988
207
192
New Zealand Livestock Sector Model: 1986 Version.
Volumes 1 and 2, T.P Grundy, R.G. Lattimore, A.C. Zwart,
March 1988.
Public Drinking and Social Organisation in Methven and Mt
Somers. J. R. Fairweather and H. Campbell, 1990.
208
Generations in Farm Families: Transfer of the Family Farm
in New Zealand. N. C. Keating, H. M. Little, 1991
An Economic Analysis of the 1986 Deregulation of the
New Zealand Egg Industry, J. K. Gibson, April 1988.
209
Determination of Farmland Values in New Zealand: the
Significance of Financial Leverage, G. A. Anderson, G. A.
G. Frengley, B. D. Ward, 1991.
210
Attitudes to Pests and Pest Control Methods R. L.
Sheppard, L. M. Urquhart, 1991.
211
Administered Protection in the United States During the
1980's: Exchange Rates and Institutions, D. A. Stallings, 1991.
212
The New Zealand Consumer Market
For Cut Flowers in the 90s,
C. G. Lamb, D. J. Farr, P. J. McCartin, 1992
124
Some Recent Changes in Rural Society in New
Zealand, J. R. Fairweather, July 1989
125
Papers Presented at the Fourteenth Annual
Conference of the N.Z. Branch of the Australian
Agricultural Economics Society, Volumes 1 and 2,
October 1989
193
194
Assistance totheTourist Industry, A. Sandrey, S. Scanlan,
June 1988.
195
Milk Purchasing: a consumer survey in Auckland and
Christchurch, R.L. Sheppard, July 1988.
196
Employment and Unemployment in Rural Southland,
J. R Fairweather, November 1988.
DISCUSSION PAPERS
116
Government Livestock Industry Policies: Price
Stabilisation and Support, G. Griffith, S. Martin, April
1988
117
The NZ Sheepmeat Industry and the Role of the NZ Meat
Producer's Board, A. Zwart, S. Martin, March 1988
118
Desirable Attributes of Computerised Financial Systems
for Property Managers, P. Nuthall, P. Oliver, April 1988
126
Marketing Boards and Anti-Trust Policy, E. McCann, R.
G. Lattimore, 1990.
119
Papers Presented at the Twelfth Annual Conference of
the NZ Branch of the Australian Agricultural Economics
Society, Volumes 1 and 2, April 1988
127
Marketing of Agricultural and Horticultural Products selected examples, K. B. Nicholson, 1990
120
Challenges In Computer Systems for Farmers,
P. Nuthall, June 1988
128
121
Papers Presented at the Thirteenth Annual Conference
of the N.Z. Branch of the Australian Agricultural
Economics Society, Volumes 1 and 2, November 1988
A Review of the Deregulation of the NZ Town Milk
Industry, R. G. Moffitt, R. L. Sheppard, November 1988.
Methven and Mt. Somers: Report on Socio-Economic
History and Current Social Structure. H. R. Campbell, J. R.
Fairweather, 1991
122
123
Do our Experts Hold the Key to Improved Farm
Management? P. L. Nuthall, May 1989
129
Proceedings of the Rural Economy and Society Section
of the Sociological Association of Aotearoa (NZ),
April 1991
130
Evolutionary Bargaining Games
J. K. D. Wright, May 1991
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