Emac2012 complete

Segmenting Facebook using rural

tourists: geo-demographics, travel

motivations and activities

Juho Pesonen

[email protected]

University of Eastern Finland

EMAC 2012, May 23-25, Lisbon, Portugal

Presentation structure

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1. Introduction to the topic2. Background of the study3. Data and methods4. The results5. Discussion and conclusions

900 million!

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Theoreticalbackground•Segmentation and targeting theory as

background

– Consumer behavior is increasingly less wellexplained by socio-economic and demographiccriteria (González & Bello, 2002).

– In market segmentation data-driven methods based on motivations, benefits and activities have been popular ways to generate competitive advantage.

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- However, advertising and targeting in Facebook is mainly based on sociodemographics!

- Age, gender, geographical location and education as means to target promotions.

- Also likes and interests, work, languages, and friends of connections.

- Important factors to describe segments!

- Efficient segmentation can lead to fewer direct confrontations with competitors and the design of more suitable marketing programmes (Dibb et al.,

2002).

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- Two ways to do segmentation: a priori and post hoc segmentation (Dolnicar, 2002).

- Market segmentation studies in social media are not common.

- Correa, Hinsley and de Zúñiga (2010) studied the relationship between users’ personality and use of social media.

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- Market segmentation in the field of electroniccommerce has been called for (Brengman et al., 2005).

- More and more important topic.

- Empirical investigation on gender and agedifferences in travel motivations and activityparticipation has been called for (Jönsson & Devonish, 2008).

- What motivates people to travel and what theywant to do while travelling?

- Rural tourism as study context

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1. The goals of the study•To compare effects of age, gender and place of

residence to travel motivations and

•to compare effects of age, gender and place of residence to preferred travel activities.

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Data and methods•Data collected using banner advertisement on three rural tourism

websites in Finland.

•4.3.-31.8.2011

•Banner advertisements were clicked altogether 3684 times, resulting in 2131 responses.

– 1967 usable filled questionnaires.

– 1186 had used Facebook during one week period prior to answeringthe questionnaire.

•Respondents were asked to choose up to three most important travel motivations based on an earlier study (Bieger and Laesser 2002).

•Users were also asked to choose the travel activities they areinterested in doing during their rural holiday.

•Chi-square test to examine differences.

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Participating in

nightlife

Enjoying

comfort,

spoiling myself

Taking and

having time for

my partner

Taking and

having time for

my family

Enjoying

landscape and

nature

Enjoying the

sun and water

Gender

Male 42 (15.4%) 80 (29.4%) 109 (40.1%) 88 (32.4%) 143 (52.6%) 71 (26.1%)

Female 66 (7.3%) 331 (36.7%) 337 (37.4%) 341 (37.8%) 513 (56.9%) 271 (30.1%)

Age

Below 20 25 (33.8%) 33 (44.6%) 32 (43.2%) 10 (13.5%) 28 (37.8%) 39 (52.7%)

20s 44 (12.2%) 143 (39.5%) 161 (44.5%) 91 (25.1%) 186 (51.4%) 104 (28.7%)

30s 21 (7.6%) 89 (32.4%) 92 (33.5%) 133 (48.4%) 157 (57.1%) 71 (25.8%)

40s 8 (3.5%) 81 (35.5%) 71 (31.1%) 114 (50.0%) 141 (61.8%) 55 (24.1%)

50s 2 (1.7%) 34 (28.8%) 50 (42.4%) 40 (33.9%) 80 (67.8%) 35 (29.7%)

Atleast 60 2 (3.6%) 13 (23.2%) 25 (44.6%) 14 (25.0%) 33 (58.9%) 14 (25.0%)

Region

Southern

Finland

50 (9.8%) 174 (34,1%) 183 (35.9%) 189 (37.1%) 293 (57.5%) 167 (32.7%)

Eastern Finland 32 (8.8%) 125 (34.3%) 145 (39.8%) 134 (36.8%) 192 (52.7%) 99 (27.2%)

Western Finland 12 (10.2%) 41 (34.7%) 41 (34.7%) 31 (26.3%) 73 (61.9%) 31 (26.3%)

Province of

Oulu

7 (5.5%) 55 (43.3%) 60 (47.2%) 48 (37.8%) 70 (55.1%) 27 (21.3%)

Lapland 3 (9,4%) 8 (25.0%) 11 (34.4%) 19 (59.4%) 21 (65.6%) 7 (21.9%)

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Downhill

skiing

Cross-country

skiing

Snowmobiling Canoeing Rowing Fishing Berry or

mushroom

picking

Walking /

hiking

Watching

animals (eg.

bears)

Gender

Male 46 (16.9%) 51 (18.8%) 53 (19.5%) 72 (26.5%) 132 (48.5%) 160 (58.8%) 67 (24.6%) 169 (62.1%) 81 (29.8%)

Female 169 (18.8%) 208 (23.1%) 145 (16.1%) 276 (30.6%) 504 (55.9%) 409 (45.4%) 334 (37.1%) 875 (74.9%) 397 (44.1%)

Age

Below 20 29 (39.2%) 12 (16.2%) 20 (27.0%) 29 (39.2%) 35 (47.3%) 35 (47.3%) 24 (32.4%) 36 (48.6%) 24 (32.4%)

20s 81 (22.4%) 64 (17.7%) 85 (23.5%) 136 (37.6%) 193 (53.3%) 169 (46.7%) 114 (31.5%) 266 (73.5%) 173 (47.8%)

30s 48 (17.5%) 57 (20.7%) 39 (14.2%) 84 (30.5%) 156 (56.7%) 138 (50.2%) 79 (28.7%) 198 (72.0%) 112 (40.7%)

40s 34 (14.9%) 60 (26.3%) 33 (14.5%) 61 (26.8%) 128 (56.1%) 115 (50.4%) 85 (37.3%) 177 (77.6%) 103 (45.2%)

50s 12 (10.2%) 38 (32.2%) 13 (11.0%) 20 (16.9%) 67 (56.8%) 59 (50.0%) 44 (37.3%) 89 (75.4%) 40 (33.9%)

Atleast 60 2 (3.6%) 13 (23.2%) 0 (0%) 3 (5.4%) 28 (50.0%) 26 (46.4%) 33 (58.9%) 42 (75.0%) 16 (28.6%)

Region

Southern

Finland

91 (17.8%) 120 (23.5%) 77 (15.1%) 161 (31.6%) 300 (58.8%) 246 (48.2%) 184 (36.1%) 352 (69.0%) 205 (40.2%)

Western

Finland

63 (17.3%) 78 (21.4%) 59 (16.2%) 109 (29.9%) 195 (53.6%) 173 (47.5%) 108 (29.7%) 279 (76.6%) 145 (39.8%)

Eastern

Finland

24 (20.3%) 27 (22.9%) 26 (22.0%) 41 (34.7%) 58 (49.2%) 57 (48.3%) 44 (37.3%) 83 (70.3%) 51 (43.2%)

Province

of Oulu

30 (23.6%) 20 (15.7%) 26 (20.5%) 29 (22.8%) 58 (45.7%) 66 (52.0%) 42 (33.1%) 88 (69.3%) 55 (43.3%)

Lapland 7 (21.9%) 9 (28.1%) 7 (21.9%) 9 (28.1%) 19 (59.4%) 20 (62.5%) 13 (40.6%) 24 (75.0%) 17 (53.1%)

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So what?•Socio-demographic and economic variables more

important than ever for segmentation when considering targeting messages in Facebook.

– Especially age and gender.

•Starting point for further testing

– Reducing efforts, increasing efficiency.

•We have to think new ways of targeting when doing market segmentation.

– Embracing market segmentation in online context.

Questions, comments?Thank you!

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