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COMMISSIONED BY ECOGRA (E-COMMERCE and ONLINE GAMING REGULATION AND ASSURANCE)
‘GLOBAL ONLINE GAMBLER SURVEY’:An Exploratory Investigation into the Attitudes and Behaviours Internet Casino and Poker Players
AUTHORS: JONATHAN PARKE, JANE RIGBYE, ADRIAN PARKE, JACQUI SJENITZER; RICHARD WOOD; BELINDA WINDER; LEIGHTON VAUGHAN WILLIAMS
IntroductionInternet Gambling Behaviour
•Despite the growth we know little about Internet gambling behaviour and who does it– Medium– Type of behaviour
•Prevalence is difficult to estimate– Most have more than one account– There may be a reluctance to be identified (e.g. National Surveys)
•Suggested profile of the Internet gambler so far:– Internet poker = 85% male (IGWB, 2004)– Internet poker = average age < 40 years old; females even younger
IntroductionInternet Gambling Behaviour
•There is a general lack of research– Biased samples (e.g. Ladd and Petry, 2002)– Focus on “pathological gambling”.
• In a period consolidation, other means of competition is now necessary (i.e. trust and brand loyalty):– Confidence and need to offer a player “shortcut”
•The aims include exploring the following:– Basic dynamics of Internet poker and casino behaviour – Player protection and social responsibility– Idiosyncratic and peripheral factors
MethodSurvey
• Internet Mediated Research (IMR) – 85 questions
•Advantages and disadvantages of this approach
•Collecting data on gamblers is a difficult task
•Largest and most representative survey to date
•Varied sources (e-mails; portals; media and eCOGRA)
•Players targeted?
•Ethical Clearance
Representation Number
Total Respondents 10865
Males 6246
Females 4517
Countries 96
Employment Sectors 37
MethodFocus Groups
Breakdown of Participant Details and Locations of Focus Groups
Country Number Gender Mean Age Age Range
USA 11 All male 31 19 - 56
UK 23 All male 27 18 - 43
Canada 18 1 female, 17 male 37 21 - 60
Germany 17 7 female, 10 male 28 20 - 45
Sweden 25 4 female, 21 male 32 17 - 60
•Key topics arising from survey – further exploration
•Advertisements were placed in a variety of sources
•Sessions usually lasted 90-120 minutes
•Details of participants include:
ResultsForms of Participation
Total Number of Respondents = 10313 Women % Men %
Video Slots 84 36.9
Video Poker 31.4 21.3
Sports Betting and Horseracing 2.5 11.8
Poker 22.1 61
Blackjack 14 20.6
Roulette 5.1 8.8
Lottery 10.3 7.3
Bingo 21.1 5.8
Other skill games (eg Backgammon and Mahjong)
8.2 4.1
ResultsGeneral Information
•The majority of online play takes place at home – Most commonly in the evening, followed by
late night, – women were significantly more likely to play
work.
•Just under half of players are influenced by the software provider when selecting sites. – Casino players were more likely – One in five players was unsure
ResultsMessage Boards and Forums
Almost 40 per cent of respondents stated they visited message boards or forums. – mostly one to three times per day.
Total number of respondents = 4509 % Total
1 To find out about promotional offers 64.6 2911
2 To get general information best worst/sites 53.4 2409
3 General read 40.5 1824
4 To catch up on news and events 36.7 1653
5 To get betting tips 21.5 970
6 To air my views 20.3 916
For general chat with other players 20.2 909
Results - Internet CasinoTypical Player Profile
The typical Internet casino player is likely to:• Be female (54.8%)
• Aged 46-55 (29.5%)
• Play 2-3 times per week (37%)
• Have visited > 6 casinos in the preceding three months (25%)
• Have played for 2-3 years (22.4%)
• Play for between 1-2 hours per session (26.5%)
• Wager between $30-$60 (18.1%) per session
• Play video slots (80.9%) of which they consider bonus games to be the most important aspect of the game
Results - Internet CasinoEstimated Monthly Financial Performance
lose m
ore
than $
50
000
lose $
250
00
-$5
00
00
lose $
100
00
-$2
50
00
lose $
500
0-$
10
00
0
lose $
250
0-£
50
00
lose $
100
0-$
25
00
lose $
500
-$1
00
0
lose $
250
-$5
00
lose $
100
-$2
50
lose $
50-$
10
0
lose $
25-$
50
lose $
10-$
25
lose le
ss th
an
$1
0
I bre
ak e
ve
n
win
less th
an
$1
0
win
$1
0-$
25
$2
5-5
0
win
$5
0-$
100
win
$1
00-$
250
win
$2
50-$
500
win
$5
00-$
100
0
win
$1
000
-$25
00
win
$2
500
-$50
00
win
$5
000
-$10
000
win
$1
000
0-$
25
00
0
win
$2
500
0-$
50
00
0
win
more
tha
n $
50
00
0
Estimated Monthly Financial Outcome
800
600
400
200
0
Co
un
t
Results - Internet CasinoMotivation
•Although, money is considered to be important in making Internet casino play enjoyable, – It was often considered as a secondary intrinsic motivation – The least common motivation for gambling was to socialise – Gender differences in motivation were confirmed
• Important factors in determining the where players choose to play:– Bonuses (76.6%)– Game Variety (62.1%)– Deposit Method (56.8%)
Results - Internet PokerTypical Player Profile
• Be male (73.8%)
• Be aged 26-35 (26.9%)
• Play 2-3 times per week (26.8%)
• Have visited > 6 poker sites in the preceding three months (25%)
• Have played for 2-3 years (23.6%)
• Play for between 1-2 hours per session (33.3%)
• Play one (24.1%) or two (24%) tables at a time
• Play both cash games and tournaments (34%)
• Play at big-blind (minimum stake) levels of $0.50 to $2.00 (61.2%)
• Play with 6-10% of their bankroll at a table at anyone time (23%)
The typical Internet poker player is likely to:
lose
more
than
$50
000
lose
$2
5000
-$50
00
0
lose
$1
0000
-$25
00
0
lose
$5
000-$
100
00
lose
$2
500-£
500
0
lose
$1
000-$
250
0
lose
$5
00-$
10
00
lose
$2
50-$
50
0
lose
$1
00-$
25
0
lose
$5
0-$
100
lose
$2
5-$
50
lose
$1
0-$
25
lose
less th
an
$10
I bre
ak e
ven
win
less th
an $
10
win
$1
0-$
25
$2
5-5
0
win
$5
0-$
100
win
$1
00
-$250
win
$2
50
-$500
win
$5
00
-$100
0
win
$1
00
0-$
25
00
win
$2
50
0-$
50
00
win
$5
00
0-$
10
00
0
win
$1
00
00-$
25
000
win
$2
50
00-$
50
000
win
mo
re th
an $
500
00
Estimated Monthly Financial Outcome
1,000
800
600
400
200
0
Co
un
t
Results - Internet PokerEstimated Monthly Financial Performance
Results - Internet PokerBankroll Management and Profitability
more than 75%
41-75%21-40%11-20%6-10%2-5%less than 2%
Percentage of Bankroll Played Used at a Table at Any One Time
2.00
1.50
1.00
0.50
0.00
-0.50
-1.00Mea
n M
on
thly
Fin
anci
al O
utc
om
e fo
r In
tern
et
Po
ker
Pla
yers
(sc
ore
s b
ased
on
cat
ego
ry
mem
ber
ship
an
d p
laye
r's
ow
n e
stim
ates
)
Complex Relationship Between Percentage of Bankroll Played at Any One Table and the Estimated Monthly Financial Outcome
Results - Internet PokerMulti-tabling and Profitability
more than 6654321
Number of Tables Played at Any One Time
4.00
2.00
0.00Mean
Mo
nth
ly F
inan
cia
l O
utc
om
e f
or
Inte
rne
t P
oke
r P
laye
rs (
sco
res
ba
se
d o
n c
ate
go
ry
me
mb
ers
hip
an
d p
laye
r's
ow
n e
sti
mate
s)
Complex Relationship Between Number of Tables Played at a Time and the Estimated Monthly Financial Outcome
Results - Internet PokerOther Findings
• Men - more likely to – play more frequently, – have longer sessions, – play with a larger percentage of their bankroll, – play higher stakes, – play at more than one table simultaneously, and – use the chat function.
• Around 12% of Internet poker players gender swap– Those who “always” perform significantly worse financially
• Winning money was reported as most important motivator - however, when exploring this further in focus groups, – makes the game meaningful, – money was a secondary motivator and that – many would still continue to play if losing long term
Results – International DifferencesMonthly Financial Performance (Casino)
Results – International DifferencesMonthly Financial Performance (Casino)
ResultsLuck, Skill and Superstition
•41% of respondents reported to have a lucky number,– more likely to be female and younger players
•Women and Internet casino players were more likely have a lucky charm
• Internet poker players - lucky items of clothing.
Top 5 Lucky Charms
Rank Charm Number of Responses
1 Photo of Pet or Loved One 48
2 Buddha Statue 43
3 Casino Chip 39
4 Coin 36
5 Rock/Stone 36
Neutral or UnbiasedUse Gambler's FallacyBelief in Lucky Streaks
Use of Cognitive Biases in Internet Gambling
1.50
1.00
0.50
0.00
-0.50Me
an
Mo
nth
ly F
ina
nc
ial O
utc
om
e f
or
Inte
rne
t P
ok
er
Pla
ye
rs (
sc
ore
s b
ase
d o
n c
ate
go
ry
me
mb
ers
hip
an
d p
lay
er'
s o
wn
esti
ma
tes
)
Perceived Monthly Financial Outcome For Internet Poker Players According to Cognitive Bias
ResultsCognitive Biases
ResultsPlayer Protection and Fairness
• Over a third had a dispute – Most likely older or casino – No differences
• The most common problems experienced by players were being disconnected or software malfunctions.– Non-payment was the least common concern among players.
• Players felt that there was a need for regulation in most areas including: transparency, uniformity and responsiveness.
• Around half of all respondents felt that online gambling software was fair and random.
ResultsPlayer Protection and Fairness
• Customer service of this industry was marginally better than other industries– women being more positive
• The majority of players take action– to avoid being subjected to cheating (87%)– 88% to 91% consider 3rd party reports on payout percentage and randomness
to be at least somewhat important
• The body which was reported most frequently to have resolved disputes was eCOGRA (49.7%)
• eCOGRA – interesting case study for importance of awareness– From 28% awareness to only 4.6% who would not look for seal
ResultsResponsible Gambling
The players take:
• Hospitality E-mails
• Information Sharing
• Limits
• Affordability Checks
• Youth Protection
• Financial Statements
• Source of Income
• Nothing can be done
Between 51% to 75% (across all five features) of players stated that they would consider some responsible gaming elements at least “quite useful”.
1. Regular financial statements (75%)
2. Self-set time limit (51%)
Focus Groups:– “players own responsibility” but– “improve trust and brand”
Discussion
•Gender differences– Growth in acceptance as a bona fide pastime – Differences in motivation– Locus of control
•Age differences– A cohort or age effect?– A result of:
•Social networks;Time;Media coverage
• Internet casino– Draw of the bonus– Financial performance (hard to predict)
•Resistant to chasing; unbiased style of betting; motivations
Discussion
• Internet poker– Forums – outside of play but important to the game– Bankroll Management – less is more– Multi-tabling – more is more– Financial Performance: (in addition to the above)
• Resistant to chasing;
• More sites;
• Music;
• Boredom is costly
•Responsible Gambling– Players do not favour restriction– Several ideas suggested for protection
• Difficult to implement
• Future research needed (protective but not affecting enjoyment)
Discussion•Fairness and Player Protection
– Players characterised buy uncertainty, mistrust and a lack of understanding
– till important to players nevertheless!– Evidence suggest a need to develop and maintain standards
•Few bodies
• Identifiable
•eCOGRA as a case study
– Customer service performing well
•Future Research– Examine motivation further– Strategic play– Problem gambling and protective features– Prevalence
Conclusion
We now have some idea what we are talking about!–We know a lot more about who, what, where and when–We know a little more about why–We have a useful framework to guide:
•Future research
•Corporate strategy
•Policy and regulation