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PUSHING BACK: Supply Side ChallengeArtem RodichevBusiness Development Manager

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We specialize in solving the complex challenges around building real-time advertising platforms at scale. Over the past 10 years IPONWEB has pioneered custom ad-tech technology for more than 100 companies globally.

IPONWEB IS A GLOBAL TECHNOLOGY COMPANY

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Programmatic Ecosystem Shifts

Trading Practices

SUPPLY SIDE CHALLENGES

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2014 IAB Programmatic Adverting Study

• Ad-tech revenues – 55%• Publishers – 45%

Programmatic has shifted a lot of the money that was on the table from publishers to (ad-tech) intermediaries.

In terms of previous charges

Ad Tech Revenue

Previous Tech Cost

55%30%

25%

NetworkCharges

ProgrammaticTax

=

PROGRAMMATIC CAPITAL SHIFT

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SHIFT TO AUDIENCE BUYINGPremium Publishers Long-Tail Publishers

Image via AudienceXpress

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Huge Publishers with scale are packing their inventory with data, moving revenues away from publishers without substantial data assets

DATA PACKAGING

Other 11 %Twitter

8 %

Google23 %

Facebook58 %

Other 23 %

Twitter6 %

Google20 %

Facebook51 %

Source: MAGNAGLOBAL, eMarketer

2014 2018

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Programmatic Ecosystem Shifts

Trading Practices

SUPPLY SIDE CHALLENGES

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PROGRAMMATIC Pricing Distribution

REVE

NU

E %

CPM

IMPR

ESSIO

N %

10 %

30 %

40 %

50 %

20 %

10 %

0 %

20 %

0 % $1 $2 $3Above

$4 $10$5 $8 $9$6 $7

1ST LOOK

AVERAGE PROGRAMMATIC FIRST LOOK

$3.00

$1.05

OVERALL CPM PRICING

PRIC

E

Source: ExchangeWire 2014

30% Sales > $4

15% Sales > $7.5

7% Sales > $9

“1st Look” and “Programmatic Guaranteed” schemes are often mispriced

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$7.00$6.60$6.30$6.00

BUY SIDE PRESSURE

$3.00$2.80$1.70$0.50

Non-Submitted Bid

Subm

itted

Bid

s

DSP

1D

SP 2

WIN

NIN

G B

ID

2ND

PRIC

E FAIR

2N

D P

RICE

$6.61$7.00

$3.01

DSP Internal Auction

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GAMING THE AUCTION

Charging the median between 1st & 2nd Price

WIN

NIN

G B

ID

MED

IAN

PRI

CE

SECO

ND

PR

ICE

Easy to Detect and Avoid

BID

1) Add Small Random Component to Bid

2) Detect Correlation

3) Eliminate the Gap

TIME BID MEDIAN PRICE SECOND PRICE

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How to find $X that is best for publisher?

INDEPENDENT CLEARING PRICE

Bid Probability Density

IMP Not Sold Bidder Wins and Pays $X

Floor @ $X

Bid CPM$1 $10

Floor should not depend on the bid value

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OPTIMAL FLOOR PRICING

Best $X

FLOOR $5$1 $10

Impressions Not Sold

Expected Payout

Bid Probability Density

Expected Payout (X) = X P (bid > X)

Optimal Bid Equation: P(bid>X) – X P(bid=X) = 0

Maximum Payout X P(bid>X) = 0ddX

Maximising Payout

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• Bid Density Γ(2,$3.00)• Typical Bid $3.00• Average Bid $6.00• 2nd Price Floor $0.00• Optimal Floor $4.85

EXAMPLE

AUCTION

• Traditional 2nd Price• 50% Cheat• Optimal Auction

CPM

$0.01$3.00 – Until Busted$2.53

$3.00 $4.85

Global Cartel

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SUPPLY SIDE TACTICS

Data Protection

Optimal Auction

Own Your Territory

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