Plan for Today
- Continue with auctions
- Sponsored Search
- The VCG auction
- The FCC Incentive Auction
Plan for Today Continue with auctions Sponsored Search The VCG - - PowerPoint PPT Presentation
Plan for Today Continue with auctions Sponsored Search The VCG auction The FCC Incentive Auction Last time A Iii c 17g I is highest bidder price auction i winner winner pays her bid 2nd price archeni winner is highest bidder
Last
time
17g
I
price auctioni
winner
is highest bidder
winner pays her bid
2nd price archeni
winner is highest bidder
winner pays 2ndhighest bid
How to
bid
Model
each bidder bids to
maximize
expected
utility
givenbeliefs aboutothers
ViIneceivesitem
pi
utilityof
bidders
value
payment
Vickrey auction
2nd price
anchen
truthful
also called
strategy
proof
dominantstrategy incentivecompatible
Dsic
it is
a dominant strategy to
bid your value
also
individually rational
IR
bidder's utility guaranteedto
be nonnegative
maximizes
also
called
surplus
total
happiness of all
participants
sum of
utilities
utilityof bidder i utilityof
auctioneer
n
wi Ii
wins
F
I
1st price auction
no
dominant strategies
analyzed byassuming each player's
value
was
drawn from
distribution
F
Showed that if
F
is
uniform
0 too
then
par
L
is
a
Bayes
Nash
equilibrium far h
2
F
utility ofbidding pCyj1ohenp6yp
pay
RevenneEquivalence
Thm
µ
Vin
F
fi then
for any anchor
sit
in
equilibrium
item
allocated
to
bidden uf
highest
value and payment of
a
player
cuh
valve Oiso
has
same expected
revenue
Posters newspapers magazines Billboards television
Price depends on how many people your advertisement is shown to. (whether or not they look at it, or care about it) “Half the money I spend on advertising is wasted; the trouble is, I don’t know which half” Andrew Wanamaker, advertising pioneer
Complicated negotiations with high monthly premiums, forms a barrier to entry for small advertisers.
Slot One Slot Two Ad A Ad B Ad C
“Most people don’t realize that all that money comes in pennies at a time” Hal Varian, Google Chief Economist
How are these ads different than the ads in the offline media?
Model
perkeyword
auction
Bidders
advertisers who have
astanding bid
keyword
Auction
some
K
1
Slots
notidentical
Cj
Probof aclick
slot
j
l
K
vii
adverts's
value
for
a
click
CTR rate
allqualities
are sated
due to gualitygad
d
l
l
bidder i's ad
Prob of
click
Value
to
bidder
i
gets
his
ad
placed
in
slot's
vi
Cj
exp
exp
v
g
Generalized Second
Price
aH
loBi
bid
a
click to
slot j payment
is
next
highest bid
A B C
Slots
Advertisers
Click-through rates
1 0.4
Value per click
7 6 1
1 2
No slot
values
PPC
bids
c
6
At
cz
I
6
1
0.4
Cz
Example
bidder
I
2
3
values
0.99
in this example
Y bidder
1
bids
below9
then his utility will
be higher than it
was
biddingtruthfully
Truthful anchor
VCG
auction
chooses
maximize socialwelfare
V S Vy S
social welfare of
an
allocation
EIvicspcis
slot i
is assigned to
C
Cz Cz
YIximizing
allocation
charge each
bidder
the
externality
her presence
Imposes
IBidduliT
Whats
w
be
way
bidder1 in archer
i
a
VCE paymentfor bidder I
charge bidder
loss
incur becauseof her Ktl
cute
O
ai
i
c c
Ci
i
2
VCG payment for
bidder
KH
ci
i
a
Vi in jts
CG auction for
sponsored search T
aipi
ftp.bjccji 5
Geta bid from each bidder
w
Relabel bids
so
b
by
bn
for i
I
K
assignbidderi
to
ihslots
bit GiI bitafinicity
for i
h K
for each click
chargebidderi
KH
PPC
pi
I
b Kj
c
j
VCG.is
truthful
IR
andwelfare maximizing
Progg tmtfeness
Fix
bids
let
bj
denotejthhighest
bid except
me
my value
slot k
Ckbk
K S
Ca Ca be 1 cable
V
Li
A value
as
movefrom i
to slot
i 1
i
i
l
cm
c
bi I 0 price
want to
do
this
if
v
bi
i
S
V
b by
valuations
CTRs
the GSP
auction
has
an equilibrium
same allocation
payments
as
VCG
VCGpaying
p
no
sweeping
revenue comparison between
GSP
VCE
Facebooky what bidders
can bid on
Various
events
placement
size
format ofads
evaluating quality
vi Cj
more appropriate model
bidder has
value far
each eventtype difficult
for
advertisers
to figure out CTRs
high quality outcomes
advertisers happy biddig
easy
CG fully general
n
participants
finite set of
each agent i
has private
valuation
v
w
Fw c R
vilwt fauegsjntjpr.e.int
aemsw
F
choose
C
argmax Ebilw
w C I 5
1
Lettnis
07
P
j bjlwT
ui
view'T
pi
View t.F.bjw9
wmeoxfpbo.tw
choose bin t.wo.GL
to
maximize
vi
w t
bjlw
X
Userinterface for bidding
allow bidders
band eventsthey
allow
bidders
to specify budget
Computational requirements
Pa
total
value others valve O
getif a matinee
theyget
5
wana
5
Pb
3 1
4