Brand Tribalism UKAIS 2011

Brand Tribalism

Exploration of Virtual CommunitiesUKAIS 2011 – Pasi Tuominen – University of Hertfordshire

A part of Doctoral Thesis Managing Services Reputation

Word of mouth

Tribalism

Reputation

Brand

Leading Academic Research

Bagozzi (2000)

Bordieu (1989)

Cova (1996, 1997, 2007)

Cova & Salle (2008)

D’Alesandro (2001)

Grönroos (2006)

Kozinets (1999, 2004, 2007)

Maffesoli (1996, 2007)

Definitions and key characteristics

a group of people emotionally connected by similar consumption values and usage (Cova, 1997)

Definitions and key characteristics

social association are the most important influence on an individual’s consumption decision. (i.e. Bagozzi 2000, Cova 2002)

Definitions and key characteristics

use the social “linking value” of products and services to create a community and express identity. (Cova, 1997)

Definitions and key characteristics

shared consumption is the postmodern consumer’s means of creating a social link and building bridges between individuals (Cova & Salle, 2008; Simmons, 2008).

The Need To Connect

…Maslow: "Love and belongingness is a basic human need.” This feeling begins with our need to connect to something/someone.

Why Do We Connect?

…we connect around shared interests. Music. Film. Fashion. Business. Literature. Gaming. Photography. Sports. etc. etc. etc.

Location Used To Be Everything

…tribes used to be limited to location.

12 tribes of Israel

The Digital Tribe

…is no different from offline tribes.

… NO Boundaries ?

Tribal Eco-System

… social networking platforms allow tribes to form devoid of boundaries with common interests.

Social Networking

… is hardly a new idea. It is at the heart our democratic roots.

Study Design

… 180 day netnographic data collection, analysis and comparison of blog posts, reviews, tweets and facebook conversations.

Study Design – Hotels Hotel Chain 1 Hotel Chain 2 Hotel Chain 3

No. Of Hotels 46 56 24

No. Of Rooms 7 330 10 272 4 735

Sold Nights 1 471 866 2 326 136 1 022 318

FB Fans 1 629 2 610 7 917

Men 34 31 27

Women 66 69 73

13-17 6,4 % 5,3 % 2,8 %

18-24 6,8 % 7,8 % 7,7 %

25-34 33,5 % 32,2 % 39,6 %

35-44 28,9 % 34,0 % 37,1 %

45-54 18,2 % 15,2 % 10,3 %

55+ 6,2 % 5,5 % 2,5 %

Company Created Content 11 21 60

User Generated Content 8 86 95

Likes 71 131 1246

Comments 4 9 24

Study Design – Restaurants

Restaurant FB people like this www visitors www visits monthly active FB users

Restaurant 1 462 7514 9140 182Restaurant 2 417 25553 31503 79Restaurant 3 385 5007 7557 232Restaurant 4 321 5801 6760 125Restaurant 5 182 7285 8618 87Restaurant 6 357 4125 4996 114Restaurant 7 787 7895 10490 429Restaurant 8 1310 5390 6328 906Restaurant 9 830 8876 12774 263Restaurant 10 419 6229 7654 263Restaurant 11 397 3553 4341 357Restaurant 12 681 12893 15424 380Restaurant 13 1329 5926 7827 344Restaurant 14 368 4393 5763 273Restaurant 15 351 3471 5004 281Restaurant 16 845 4686 5516 181Restaurant 17 182 10497 12690 140Restaurant 18 685 6829 8673 180Restaurant 19 5333 9624 11226 661Restaurant 20 1468 9334 12180 385Restaurant 21 169 7495 8352 60Restaurant 22 332 2963 3618 89

KEY FINDINGS - Distribution of FB Fans

• Chain 3 has over 42% of ”hotel followers” in Finland

• Individual /private hotels attract significantly more followers (for the remaining 68%)

Internati

onal Chain

Local

Boutique

Local

Upscale

Boutique

Chain 1

Laplan

d Resort

Hotel

Chain 2

Chain 3

0

1000

2000

3000

4000

5000

6000

7000

8000

KEY FINDINGS – FB Activity

• The size of hotel / hotel chain has not relation to tribe size

• The amount of Company Created Content has no (or very small) relation to activity of the followers

• The type of CCC has significant correlation to activity

Hotel Chain 1 Hotel Chain 2 Hotel Chain 30

2000

4000

6000

8000

10000

12000

No. Of roomsFB FansCCCLikes

KEY FINDINGS – Reactions to Company Created Content

• Hotel Chain 3 followers created 2.1 times the amount of content

• Chain 3 followers reacted to Company Created Content 3.3 times more often

• 65% of the reactions of Chain 1 postings were negative

• Significant correlation (R² .828) was detected between the likings and chain 3’s entertainment valued stimulus.

0

10

20

30

40

50

60

70

80

Chain 1Chain 2Chain 3

*509 *93

KEY FINDINGS – Distribution of the tribe conversation during an average week

• FB provides platform for week-end ”party” planning

•Other platforms for re-living and sharing the experiences

•Dating, trends and music created Positivive effect

•Products, prices etc. had a negative influence to conversation

Monday

Tuesd

ay

Wed

nesday

Thursd

ayFri

day

Saturd

ay

Sunday

0

5

10

15

20

25

FacebookNon-Facebook

Conclusions – implications to management…

… First. Shut Up & Listen

Leading a Virtual Tribe

… monitoring… measuring… long term… diverse channel / platform selection… infotainment… courage to fail

Leader of a Tribe has

… to stand out by being the voice, emulator and human form of the idea by constantly listening then participating in as many active conversations as possible.

Because… Tribes Buy

…brands help make an impact in a tribe with tools, products and services that facilitate peoples needs, aspirations and desires.

Selling To Tribes

… it is possible to win the popularity contest by being: honest. present. helpful. smart.

Grab Your Tribe-Share

…When you find the tribe that understands and loves you – you will have won the popularity contest we call market share.

Thank You !

pasi.tuominen@live.fi

p.p.tuominen1@herts.ac.uk