Market ResearchBelow is an extract of the market research carried out by Martin Flammia (MD) in March 2006. Many references where sourced on the World Wide Web with special credit going to:
A lot of the actual data has been removed to cooperate with any preach of copyright. Table of ContentsMarket Research. 1 Table of Contents. 1 Summery Profile Of ThingsToDoNearYou.co.uk Visitors and Members. 2 Visitors And Members. 2 CHAID modelling of Latent Class Analysis. 2 Cluster analysis. 5 Analysis summery. 9 NRS Social Grade Definitions. 10 Population Distribution By Social Grade Of Chief Income Earner. 10 Car Ownership. 11 Participation In Exhibitions and Outings. 11 Participation In Sports And Leisure (Percentage of population 18+) 12 Frequency Of Bar And Club Going. 13 Visitors To The Theatre And Concerts. 13 Frequency Of Cinema-Going. 14 Internet User Profile (2005) 14 Internet Usage By Income (shown in %) 16 Frequency Of Internet Use. 16 Visitors research– questions & results: 17 Search Engine Directories - The Market 20 Summery Profile Of ThingsToDoNearYou.co.uk Visitors and Members.
Visitors And MembersThingsToDoNearYou.com covers a very broad range of activities and venues, so much so, that understanding patterns based on the headings they simply come under would be to diverse and complicated. A better more subjective technique would be to create groups based on the social and individual characteristics of the UK population. The two techniques used below are called the Latent Class Analysis and the Cluster analysis. The primary difference is that the former group’s respondents based on the basis of their overall pattern of activity, whilst the latter groups activates on the basis of their co-occurrence within individuals over time. [1]CHAID modelling of Latent Class Analysis.Independent variables included in the CHAID analysis
The ‘family day trippers’ (Theme-park, Zoo, Car-boot sale, Cinema, Museum, Stately home) The younger the respondent the greater the chance is of falling under this class. Higher household income across all ages is also a predicting factor. Higher educational qualifications across several age bands make a positive difference. Interestingly, martial status and number of children in the household are not significant predictors. The ‘cultural slouches’ (Pub / café, Library) Not having a motor vehicle accounts for 42% versus 19% of respondents fitting this class. Those without vehicles, educational qualifications no higher then GCSE, aged 65+ and have household incomes less then £10,430 help fit this class. Those with vehicles, age in older people are still the dominant factor but having good health, managerial / professional job, qualifications above GCSE means you less likely to be a ‘cultural slouch’ The ‘cultural consumers’ (Pub / café, Library, Cinema, Sports event as spectator) Household access to a motor vehicle and being of a younger age group are the most important predicting factor. Those without a vehicle age is also a factor with 8-15 years at 57% and those aged 45 and over 36%. Qualifications make a difference in the younger group with low and the older group having higher qualifications increasing membership. Working full time, part-time and having a higher household income with a vehicle, making a positive increase. The ‘high culture vultures’ (Stately home, Concert, Museum, Pub / café, library, Plays, The operas) Doing voluntary work surprisingly had a significant factor in this class as was to having tenure. Higher qualifications as well as being a woman increased the probability. Being in full-time employment and having higher household income helped. Surprisingly social class does not emerge as a predictive factor. The ‘heritage seekers’ (Stately homes, Museums) Having a motor vehicle, doing voluntary work, owning your own home and having a managerial / professional occupation increases probability of being a member of this class. Of the group that does not do voluntary work on average a higher income, managerial /professional occupation, areas with a relatively high unemployment rate, areas with a relatively low population density and not being between 16 and 25 years of age are predictors. 
The ‘fit non competitors’
(Swimming, Cycling, Gym, Walking) The most important factor in this group is whether the household has access to a car, motor bike or other motor vehicle. It was then women with very good health and qualification around the A level and higher education, but below a degree that dominated. For men their economic activity being full time, part time and unemployed as opposed to retired, full-time student and long-term sick takes the lead. Men’s participation also increases the higher they are educated. The ‘sedate competitors’ (Ballgames, Golf, Bowls, Pub games) Men are more likely then women to full under this group. For both, age is the next discerning factor, the older men are more likely to participate, 65 years and over and women between 25 and 44 years. The other discriminating factor is in younger men between 16-24 years being unemployed. Women of the same age group with access to a vehicle, being married or cohabiting with children increases the chances. The ‘couch potatoes’ Age seems to be the single biggest factor, being between 8 and 15 having the lowest chance of being a ‘couch potato’ and increasing from 16-24 (53%), 25-44 (64%), 45-64 (81%) and 65+ (94%). Those in the youngest age group from households of higher income are less likely to be under this class. Among the second and third youngest age group, men also have a lower probability. Access to a motor vehicle (access = lower chance), household income (over £33,800 / annum) and educational qualification (GCSE = 55%) are further differentiators. The ‘active competitors’ (Racket sports, Athletics, Ball games) Age again is the most powerful predictor being between 8-15 years old at 42% compared to 0.1% for those over 65. The next discriminator is men being more likely then women with higher household income. Owning your own home also improved the chances. The ‘sport crazies’ (Golf, Ball games, Racket sports, Walking, Athletics, Cycling, Swimming) As might be expected age is the dominant factor with 8-15 year olds at the top. Men have a higher rate of membership at 22% for 8-15 year olds as opposed to women who in contrast are aged between 16-24 years old at 3%. Higher household income and social class raises the probability for both genders and age groups. ![](/images/figure2.jpg") Cluster analysisCluster 1 ‘Active Aerobic’ activities Activities in this cluster were primarily characterized by being physically demanding, often, though not always, containing a competitive element:
Active aerobic activities decline with age but are more common in the single person households and households with higher gross annual income. Men are more likely to do this type of activity than women, as are people from unclassifiable occupational groups (mainly students). People living in the south east of England (including London) are more likely to do ‘active aerobic’ activities than any other UK region. Home ownership and graduate status both increase the probability of doing this type of more vigorous physical activity. Cluster 2 ‘Non-active competitive’ activities This cluster comprised sports and games which, while often highly competitive in nature, could scarcely be described as physically demanding:
Men are nearly 300% more likely than women to do this type of activity, making it a almost entirely male preserve. Age has a moderate negative relationship with participation in this class of activity, though this effect diminishes toward the top end of the age range. Having a car available in the household is associated with higher levels of this type of activity, while living in the North of England, having a university degree and being married or living as married are all predictive of lower rates ‘non-active competitive’ activities. Cluster 3 ‘Outdoor competitive’ activities This cluster of activities was a mix of water / aquatic sports such as fishing and sailing other ‘outdoor’ activities with a competitive element such as motor sports and shooting:
Participation in ‘outdoor competitive’ activities is highest in households containing fewer adults and with higher gross annual income. As with ‘non-active competitive’ activities, this cluster of sports and games is done almost entirely by men, who are almost 500% more likely to do this type of activity than women. Car availability, a variable that has been consistently predictive of both cultural and sports participation, is again significant in this analysis, with car availability increasing the odds of doing ‘outdoor competitive’ activities’ by nearly 70%. The only other significant predictor of participation in ‘outdoor competitive’ activities is martial status, with people who are separated being the most likely participants. Cluster 4 ‘Outdoor non-competitive’ activities This cluster comprised as it is by winter sports, equestrianism and recreational walking:
People are more likely to do this type of activity as they grow older, although this positive relationship declines amongst the oldest members of the public. Larger households, both in terms of the number of adults and the number of children, are less likely to do this type of activity, while more affluent households have an increased probability. In contrast to the previous two clusters of activity, ‘outdoor non-competitive’ activities are more likely to be done by women, home-owners and carers. Similarly, this type of activity is done more frequently by ‘higher’ occupational groups and students and by households with access to a car or other motor vehicle. Educational qualifications increase the probability of doing ‘outdoor non-competitive’ activities, with graduates considerably more likely to do at least one of the activities in this cluster than those with no formal qualifications. Cluster 5 ‘Cultural consumer activities’ (low brow and consumer) This cluster grouped together the following activities. Visiting:
In total, eight variables were significant predictors of this type of activity at the 95% level of confidence: age; number of adults and number of children in the household; gross household income; gender; social class; car availability; and educational qualifications. This type of activity is, then associated, with being younger, having fewer adults and children in the household, being from a higher income bracket, having a higher degree, being female and having a car or other motor vehicle available. Having never worked also significantly reduces the probability of doing cultural and consumer activities. Cluster 6 ‘Arts and related activities’ (Highbrow)
These activities are more likely as people get older, though this effect has a tendency to diminish amongst the youngest and oldest members of society. These activities are also less likely in larger households, with the odds of going to this type of event declining by around 10% for each additional adult in the household. Income and social class are associated in ways we would probably expect; higher income and being from managerial and professional classes increases the odds of attending a high brow cultural event. Interestingly, the ‘unclassifiable’ and ‘never worked’ occupational groups are also more likely to do this sort of activity, an effect probably attributable to the fact that students make up large proportions of these groups. Being a carer increases the odds of doing this type of activity by around 23%, while owning your own home makes you around 75% more likely still. University graduates are 41% more likely to attend this type of event than those with no qualifications at all and single people have the highest probability of attending of all marital status groups. Cluster 7 ‘Heritage activities’
As we would no doubt expect, visiting sites of cultural heritage is more common as people get older though, as with high-brow activities, this effect diminishes at the top and bottom of the age range. Larger households and households containing children are also less likely to participate in this type of activity, though again, having a higher income increases the probability of a visit. ‘Higher’ occupational groups are considerably more likely to be heritage visitors, as are ‘unclassifiable’ individuals – again, probably a ‘student’ and young people effect. Region appears as a significant predictor, with people living in the south east (including London) and the south west around 40-45% more likely to visit than those in other UK regions. Housing tenure and educational level are again strong predictors of visiting behaviour; owning your own home and being a university graduate increase the probability of a visit by 57% and 75% respectively. Cluster 8 ‘Family outdoors’
Lastly, this type of activity is least likely amongst the oldest members of society and in households with larger numbers of adults in them. Households from lower income brackets, men and those who have never worked are all less likely to do this type of activity. Having a car available in the household makes visits more likely, as does living in the North or the South East (including London). Carers were, again, more likely to visit this type of event. With regard to education, this type of activity was most common amongst those with intermediate level qualifications. Analysis summeryIf we take both models into account the general patterns below have emerged:
NRS Social Grade DefinitionsThese are the standard social grade classifications and shall be used in the following research. A) Upper Middle Class – Higher managerial, administrative or professional B) Middle Class – Intermediate managerial, administrative or professional C1) Lower Middle Class – Supervisory or clerical, and junior managerial, administrative or professional C2) Skilled Working Class – Skilled manual workers D) Working Class – Semi and unskilled manual workers E) Those at lowest level of subsistence – Lowest grade workers Population Distribution By Social Grade Of Chief Income Earner.Men  Women  Here we observe that the most common social grade of chief income earner for both men and women is lower middle class - Supervisory or clerical, and junior managerial, administrative or professional, followed by middle class and skill working class. Car Ownership
Car ownership, a high determining factor for participation in sporting and cultural activities is accounted for in 76.9% of all households. Participation In Exhibitions and Outings
Here we can observe the most common forms of participation in exhibitions and outings, with Museums, Beauty spot/Gardens, Stately homes/Castles, Theme parks, Art galleries, Zoo’s and Nature reserves being the most dominant. Participation In Sports And Leisure (Percentage of population 18+)
Here we observe the most common forms of participation in sports and leisure with Swimming, Cycling, Football, Golf and Snooker being the most dominant. Frequency Of Bar And Club Going
Here we can observe that male predominantly attend bars and night clubs. Bars are most frequently attended on a daily basis by age group 35-49 and a social grade of C1 (Lower middle class), while night clubs are attended predominantly on a weekly basis by age group 18-24 and social grade C1. Visitors To The Theatre And Concerts
The patterns that emerged here seem to be that males are more likely to visit a concert around jazz, pop and rock whilst females would prefer a ballet or contemporary dance. The age groups vary slightly, but seem too dominant more for ages 35-54, except for in Pop & Rock concerts. To backup findings earlier this type of activity does seem to be more for a higher social class. Frequency Of Cinema-Going
Cinema going does seem to be generally an all round activity. You can observe a slight increase in age group 4-14, the higher social classes and females. Internet User Profile (2005)
 To simply describe the profile of the most common internet user would be male, between the age’s of 35 and 44 and be of lower middle class. Internet Usage By Income (shown in %)
This chart helps compound the theory that users of ThingsToDoNearYou.co.uk are most likely to be people on higher incomes of greater than £30,000. Frequency Of Internet Use This tells us that internet users will use the net most frequently on a daily basis. [1] Dr Patrick Sturgis, University of Surry, Dr Jonathan Jackson, London School of Economics (Nov 2003). Examining participation in sporting and cultural activities [online.] Available: www.culture.gov.uk/images/research/DCMSphase2report.pdf [accessed 14 April 2006] |
