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Cr ite o 101 Inve stor Pre se nta tion Ma rc h 2018 Safe har - - PowerPoint PPT Presentation

Cr ite o 101 Inve stor Pre se nta tion Ma rc h 2018 Safe har bor state me nt This presentation contains forward-looking statements that are based on our managements beliefs and assumptions and on information currently available to


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Cr ite o 101

Inve stor Pre se nta tion Ma rc h 2018

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SLIDE 2

2 •

This presentation contains “forward-looking” statements that are based on our management’s beliefs and assumptions and

  • n information currently available to management. Forward-looking statements include information concerning our possible
  • r assumed future results of operations, business strategies, financing plans, projections, competitive position, industry

environment, potential growth opportunities, potential market opportunities and the effects of competition. Forward-looking statements include all statements that are not historical facts and can be identified by terms such as “anticipates,” “believes,” “could,” “seeks,” “estimates,” “intends,” “may,” “plans,” “potential,” “predicts,” “projects,” “should,” “will,” “would” or similar expressions and the negatives of those terms. Forward-looking statements involve known and unknown risks, uncertainties and other factors that may cause our actual results, performance or achievements to be materially different from any future results, performance or achievements expressed or implied by the forward-looking

  • statements. Forward-looking statements represent our management’s beliefs and assumptions only as of the date of this
  • presentation. You should read the Company’s most recent Annual Report on Form 10-K filed on March 1, 2018, including the

Risk Factors set forth therein and the exhibits thereto, completely and with the understanding that our actual future results may be materially different from what we expect. Except as required by law, we assume no obligation to update these forward-looking statements publicly, or to update the reasons actual results could differ materially from those anticipated in the forward-looking statements, even if new information becomes available in the future. This presentation includes certain non-GAAP financial measures as defined by SEC rules. As required by Regulation G, we have provided a reconciliation of those measures to the most directly comparable GAAP measures, which is available in the Appendix slides.

Safe har bor state me nt

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SLIDE 3

3 •

Stoc k infor mation and ke y financ ials

Ticker: CRTO Stock Exchange: NASDAQ Global Market CUSIP: 226718104 Shares outstanding: 66.1M Stock Ownership*:

* On a fully-diluted basis, as of Dec 31, 2017, based on 73.7M fully diluted shares. ** At constant currency

  • 2017 Financials
  • Revenue:

$2,297M, +27% at cc**

  • Revenue ex-TAC:

$941M, +29% at cc

  • Adjusted EBITDA:

$310M, +35% at cc

  • Adj. EBITDA margin:

33% of Revenue ex-TAC

Free float, 84.7% Founders, NEOs, Management & Employees, 13.1% Idinvest & Yahoo! Japan, 2.2%

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4 •

A global c ompany with sc ale

User identifiers matched in the Criteo Shopper Graph Clients Countries Sales transactions analyzed in 2017 Ads served in 2017 Criteos in R&D, tech & business intelligence Employees Offices worldwide

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5 •

Manage me nt te am

Jean-Baptiste Rudelle Executive Chairman and Co-Founder, 48 K-Mobile, Lucent, Roland Berger Eric Eichmann Chief Executive Officer, 50 Living Social, Rosetta Stone, McKinsey & Co. Dan Teodosiu Chief Technology Officer, 51 Google, Microsoft, Hewlett-Packard Mollie Spilman Chief Operating Officer, 50 Millenial Media, Yahoo!, Advertising.com, Time Warner Benoit Fouilland Chief Financial Officer, 53 SAP, Business Objects Jonathan Opdyke Chief Strategy Officer, 41 HookLogic, Xerox, Beyond Interactive Tom Aurelio Executive Vice President, Human Resources, 52 Priceline, GE, Symantec, CheerNetworks Patrick Wyatt Senior Vice President Product Management, 35 Yahoo!, Estin & Co.

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6 •

Build the highe st pe r for ming and ope n Comme r c e Mar ke ting E c osyste m Conne c t shoppe r s to the things the y ne e d and love De live r pe r for manc e at sc ale to par tic ipating r e taile r s and br ands

Our vision

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7 •

Comme r c e mar ke ting is de e ply r

  • ote d in our

DNA

Technology Performance Scale Global Presence

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8 •

We ar e an e nable r and a pione e r

We brought performance-based personalized marketing to display in 2008

We have since pioneered the industry in many ways… 2008

First CPC model in display

Real-time Creative Optimization

AOV Optimizer

Privacy by Design

Facebook Exchange

Universal Match

Apple-compliant solution

Travel Segments in Engine Conversion Rate Optimizer

4.5B products imported from merchants everyday

TOP!

Daily RTB: 55bn bid requests,1.2bn wins Product Category level CPC bidding

600 TB

  • f Data analyzed

everyday

Largest Hadoop cluster in Europe Dynamic product banners Engine Optimized Segments

Passback

Sizeless creatives

Onetag App Deep linking Unique User Value Prediction

Mobile Ad Formats

App advertising Native Ads

Adaptive Revenue Optimizer

Kinetic Design

Facebook Dynamic Ads

Direct Bidder

Identity Graph

Interest Map

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9 •

Me asur able pe r for manc e is what we c ar e about

2,800 employees focus on client sales and profits as key metrics of success

CPC model

Transparent performance information in 24/7 client interface

Constant

  • ptimization
  • f campaigns

Continuous tracking

  • f sales

Established post-click attribution

Maximize Client Sales

Client Service Teams R&D and Product Teams

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10 •

We have built a lar ge ne twor k with powe r ful e ffe c ts

1.2B+

individual shoppers matched

18,000

commerce and brand clients

Thousands

  • f publishers

Machine-learning technology

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11 •

T hr e e ke y asse ts suppor t our Comme r c e Mar ke ting E c osyste m

Commerce Data & Shopper Graph Consumer Reach 17,000+

Retailers & Commerce ~1,000 Brands 1,000’s Direct publishers 6x Shopper Engagement* $600B+ Annual online sales 1.2B+ Individual shoppers matched in our Shopper Graph

Brand Funding $29B

Annual post-click sales

Mass Personalization Technology

* Our average click-through rate, or the ratio of clicks generated by our advertisements over the number of advertising impressions we purchased ("CTR"), was over 0.84% in 2017, which represents a factor

  • f over six times the average click-through rate on Standard Media of

0.14%, as measured by the DoubleClick display benchmark tool for March-April 2017.

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12 •

We ar e a global c ompany

Campaigns in countries

  • ffices in

countries nationalities

Boston

2012

Barcelona

2014

Tokyo

2011

Singapore

2013

São Paulo

2011

Shanghai

2016

Palo Alto

2009

New York

2011

Chicago

2012

London

2008

Madrid

2014

Paris

2005

Stockholm

2010

Milan

2012

Munich

2010

Amsterdam

2011

Beijing

2013

Seoul

2010

Sydney

2011

Dubai

2015

Moscow

2014

San Francisco

2014

Osaka

2014

Los Angeles

2015

Miami

2015

Istanbul

2015

Toronto

2015

New Delhi

2016

Grenoble

2014

Ann Arbor

2016

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Mar ke t and T r e nds

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14 •

We b and mobile have c hange d shopping be havior

  • f shoppers

showroom and webroom shoppers visit 2+ retailer sites when shopping online

  • f commerce

transactions involve mobile

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15 •

Suc c e ss fac tor s have c hange d for r e taile r s – and br ands

Shopper Data

  • Mass scale
  • Granularity
  • Real-time accessibility

Activation of Data

  • Predictive technology
  • Real-time dynamic optimization
  • Reach at scale
  • Great real estate
  • Merchandising

YESTERDA Y TODA Y

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16 •

Data- dr ive n mar ke ting is c r itic al for r e taile r s – and br ands

Technology / AI Media Brands Others Others

Others Granular shopper information at massive scale Partial, fragmented, unstructured view of the shopper Data

Others

Offline Online

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17 •

Comme r c e Mar ke ting is quic kly e me r ging as the ne xt big mar ke ting c ate gor y

Ce nte r s on inspir ing pe ople to buy things Me asur e d by pe r for manc e – dir e c tly dr iving sale s and pr

  • fits

Not limite d to digital

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18 •

Comme r c e mar ke ting is our c or e busine ss

Criteo’s original technology was a product recommendation engine for retail This engine formed the basis of Criteo Dynamic Retargeting Primarily applied to online commerce: retail, travel and classifieds Expanding to include data cooperative across retailers to build an omni-retailer solution Extending to include offline data for a full omni-channel solution

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We ar e the le ade r in Comme r c e Mar ke ting.

Commerce Marketing focuses on inspiring people to buy things and is measured by performance, directly driving sales and profits for marketers.

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T he Cr ite o Comme r c e Mar ke ting E c osyste m

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21 •

T he building bloc ks of the Cr ite o Comme r c e Mar ke ting E c osyste m

Privacy by Design

Product Recommendation Predictive Bidding Kinetic Design

Criteo Engine

Identity Graph Interest Map Measurement Network

Criteo Shopper Graph

Commerce Data

Product Portfolio

Criteo Customer Acquisition BET

A

Criteo Dynamic Retargeting Criteo Audience Match BET

A

Criteo Sponsored Products

Publisher Network

Direct Integration Indirect Integration

Client Platform

24/7 Client Management Center Media Retailers Real-Time Bidding Platforms

Privacy by Design

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Cr ite o Shoppe r Gr aph

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23 •

Crite o Shoppe r Gra ph: Ma ssive shopping da ta fue ls

  • ur Comme rc e Ma rke ting e c osyste m

Three trusted data collectives form the Criteo Shopper Graph

Carefully designed using our guiding principles

Two-way exchange of data Highest data security and privacy Clear and permission-based usage Value gained exceeds contribution

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24 •

Ide ntity Gra ph: ma tc hing of c ross de vic e , sa me de vic e , a nd online / offline

Criteo’s advantages

  • Over 13,000 participating clients
  • 3.7B+ identifiers matched and growing
  • Global coverage
  • +10% average uplift

Open, transparent, secure, fair

  • Encrypted and double-hashed personal

identifiable information (PII)

  • Access at no additional cost

Participation

  • Opt-in by sending hashed identifiers

via OneTag or App Events SDK

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25 •

Inte re st Ma p: shoppe r inte re st a c ross produc ts

Criteo’s advantages

  • Access to 4.5B+ products
  • Large consumer reach worldwide
  • Understand performance of

product attributes

Open, transparent, secure, fair

  • Data isolated unless opt-in
  • All data anonymized
  • No free riders
  • Contribution capped at 15% of pool
  • Access at no additional cost

Participation

  • Opt-in to share anonymized data
  • Opt-out to use client data only
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26 •

Me a sure me nt Ne twork: c onve rsion a nd sa le s a c ross re ta ile rs

Criteo’s advantages

  • SKU-level sales attribution for

brands across retailers

  • Deterministic measurement
  • Nearly 100 participating retailers

Open, transparent, secure, fair

  • All retailer data anonymized

Participation

  • When clients work with us, data within

and across retailers is aggregated

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Cr ite o E ngine

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28 •

Our E ngine solve s highly c omple x pr

  • ble ms in r

e al time

Creates Product Recommendation Personalize d creative Unique user value prediction

Client 2 Client 3 Client 4 Client 5

For each user

Internal advertiser auction Publisher/ platform bid Custom ad serving

Less than 100ms

to perform the entire process

>40,000 ads served/sec 600,000+ RTB bids/sec

Client 1

Creates Product Recommendation Personalize d creative Unique user value prediction Creates Product Recommendation Personalize d creative Unique user value prediction Creates Product Recommendation Personalize d creative Unique user value prediction

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29 •

Pr

  • duc t Re c omme ndation ac c ur

ate ly r e c omme nds the be st offe r

 Campaign goal  Visitor’s site navigation  Recency and frequency of activity  Product type, price, and category  Most viewed products on Uniqlo’s site  And much more...

The Criteo Engine recommends products based on: Products we show John John browses “Bomber Jacket”

  • n Uniqlo’s site
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30 •

Pr e dic tive Bidding de te r mine s the r ight ad oppor tunitie s

7:45 AM 8:00 AM 9:00 AM 12:30 PM 6:00 PM 9:00 PM 11:30 PM

The right bid for the right placement at the right time

User context Publisher interaction Product behavior

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31 •

Kine tic De sign de live r s pe r fe c tly br ande d ads,

  • ptimize d for

e ve r y use r

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Publishe r Ne twor k

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33 •

Publishe r Ne twor k

Media

Direct Integration

Retailers

Real-time Bidding Platforms

Indirect Integration

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Clie nt Platfor m

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35 •

Clie nt Manage me nt Ce nte r

  • Real-time monitoring and
  • ptimization of marketing efforts
  • Insights on performance and

budget

  • Granular reporting and attribution

across all products in the client’s product catalog

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Pr

  • duc t Por

tfolio

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37 •

Be ne fits

  • Drives maximum ROI with a performance-based acquisition model
  • Increases conversions of relevant new customers
  • Generates significant new revenue

What it doe s

  • Determines ideal new customer profile
  • Identifies new customers based on defined threshold
  • Predicts best places and products to convert

Use d by le ading r e taile r s Availability:

  • Q4 2017 – fashion clients in 4 key markets
  • Q1 2018 – all retail clients in 10 key markets

Cr ite o Custome r Ac quisition BE

T A

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38 •

How doe s Cr ite o Custome r Ac quisition wor k?

Shoppers with the highest scores are targeted with personalized ads featuring the given retailer’s products to drive sales Each prospective customer is assigned a unique score across all participating retailers based on the ideal customers, that show the likelihood to convert for a given retailer New prospective customers within the Criteo Shopper Graph get isolated Participating retailers share aggregated shopping and browsing events with the Interest Map, which covers 4.5B products and browsing habits of 1.2B+ monthly shoppers, to qualify new customers

7 1 6 5

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39 •

  • Connects across web, mobile, social, and video with relevance
  • Drives traffic from store-to-web1 and web-to-store1
  • Optimizes campaigns to goals with continuous machine-learning
  • Increases mobile app install1 and engagement

Use d by le ading r e taile r s

Cr ite o Dynamic Re tar ge ting

1 In testing

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40 •

Be ne fits

  • Drives sales by re-engaging existing shoppers
  • Brings qualified traffic to a retailer’s site

What it doe s

  • Delivers personalized ads to drive engaged traffic to a retailer’s
  • nline store

Use d by le ading r e taile r s Availability:

  • All markets except for Japan

Cr ite o Audie nc e Matc h BE

T A

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41 •

How doe s Cr ite o Audie nc e Matc h wor k?

CRM data, e.g. from customer in-store loyalty programs, is “onboarded” into the Identity Graph During onboarding, the CRM data is matched with users already in the Identity Graph Online campaigns with specific objectives re- engage those CRM customers that were already found online

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42 •

Audie nc e Matc h suppor ts dive r se c ampaign obje c tive s

Top Sellers Offline to Online Loyalty Upsell New product offers Cross-Sell Upgrade Seasonal

Lapsed shoppers Offline Buyers Loyalty Card Holders Audiences that may soon churn Bundle Offer Best Candidates for Buying Targeted Cross-Sell Audiences likely to upgrade Seasonal Buyers

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43 •

  • Brand manufacturers sponsor native ads across web and app
  • n their retailers’ online stores
  • Shoppers are retained in the retailer store to buy
  • Drives sales for brand manufacturers and retailers

Par tic ipating br ands

Cr ite o Sponsor e d Pr

  • duc ts
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44 •

How doe s Cr ite o Sponsor e d Pr

  • duc ts wor

k?

John searches for “coffee makers” on a retailer’s website John’s search triggers sponsored ads on retailer site John’s click on sponsored ad leads to product page Measurable sales on retailer site

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Busine ss Mode l

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SLIDE 46

All our pr

  • duc ts ar

e pe r for manc e base d.

We deliver measurable sales and profits for commerce and brand clients.

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47 •

Dynamic Re tar ge ting r e ve nue mode l

Revenue = Clicks x CPC Traffic Acquisition Cost (TAC) = CPM x impressions Revenue ex TAC = Revenues – TAC Revenue ex-TAC margin: Approx. 40%

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48 •

Pr e dic ting the r ight bid for the highe st value c lie nt

Client 4

We take CPC bids from clients

Clients

$0.30 x 0.95% = $2.85

We convert those bids into pCPM (predicted CPM)

CPC x CTR = pCPM (predicted CPM)

Publishers

$0.50 x 0.75% = $3.75 $0.40 x 0.61% = $2.44 $0.80 x 0.45% = $3.60 $2.00

Clearing Price (CPM)

Highest bidder

Bid = α × CPC × pCTR × pCR × pAOV

Client 1 Client 2 Client 3

We buy inventory from publishers in real time

CPM = Cost per Thousand impressions, CTR = Click-through rate, CR = Conversion rate, AOV = Average Order Value

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49 •

Custome r Ac quisition r e ve nue mode l

Revenue = Clicks x CPC Traffic Acquisition Cost (TAC) = CPM x impressions Revenue ex TAC = Revenues – TAC Revenue ex-TAC margin: Approx. 40%

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50 •

Audie nc e Matc h r e ve nue mode l

Revenue = Clicks x CPC Traffic Acquisition Cost (TAC) = CPM x impressions Revenue ex TAC = Revenues – TAC Revenue ex-TAC margin: Approx. 40%

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51 •

Revenue = Clicks x CPC Traffic Acquisition Cost (TAC) = Revenue share with Retailer Revenue ex TAC = Revenue – TAC Revenue ex-TAC margin = 26%-28%

Sponsor e d Pr

  • duc ts r

e ve nue mode l

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52 •

Our busine ss mode l has unique attr ibute s

Differentiated in Marketing

Attractive Direct Sticky Elastic Demand

84%

Direct relationships with clients2

910

Net client additions per quarter1

~90%

Client retention rate3

77%

Of Revenue ex-TAC from uncapped budgets4

1 On average over the last four quarters through Q4 2017 2 Last twelve months to Q4 2017; Excluding Criteo Sponsored Products 3 On average over the last 25 quarters through Q4 2017; All products included 4 On average over the last four quarters through Q4 2017. Excluding Criteo Sponsored Products. Represents uncapped budgets of our clients, which are either contractually uncapped or so

large that the budget constraint does not restrict ad buys

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53 •

Our e xisting c lie nts c onsiste ntly inc r e ase the ir spe nd with us

Excluding Criteo Sponsored Products. This client cohort analysis tracks the quarterly spend of clients since inception of their relationship with Criteo.

Average revenue per client cohort (quarterly)

Number of quarters $0 $20,000 $40,000 $60,000 $80,000 $100,000 $120,000 $140,000 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Q1-13 Q2-13 Q3-13 Q4-13 Q1-14 Q2-14 Q3-14 Q4-14 Q1-15 Q2-15 Q3-15 Q4-15 Q1-16 Q2-16 Q3-16 Q4-16 Q1-17 Q2-17 Q3-17 Q4-17

Client cohorts

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54 •

As a r e sult, a lar ge por tion of our busine ss is r e c ur r ing

2013 2014 2015 2016 2017 Existing clients New clients

88% 89% 90% 90% 92%

Revenue per client type

Includes Criteo Dynamic Retargeting, Criteo Customer AcquisitionB

E T A, Criteo Audience MatchB E T A and Criteo Sponsored Products.

Existing clients in a given year are clients that started working with Criteo prior to that given year. New clients in a given year are clients that started working with Criteo within that given year.

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Clie nts

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56 •

Dir e c t r e lationships with many pr e mium c omme r c e c ompanie s and br and manufac tur e r s

* 18,118 clients at the end of Q4 2017

  • ver 18,000 clients*

Commerce: Retail, Travel and Classifieds

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57 •

A tie r e d go to mar ke t appr

  • ac h
  • Field sales & account management
  • High value, low volume
  • Longer sales cycles
  • White glove service
  • Local in-market sales teams
  • Inside sales & account management
  • High volume, lower value
  • Shorter sales cycles
  • High degree of automation
  • Regional hubs and satellite offices

Top-tier comScore sites (typically top-50 or top-100)

  • Min. ~40k UV/month
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58 •

A lar ge oppor tunity to win ne w c lie nts

25%

Midmarket penetration

50%

Tier 1 penetration

~60,000 a ddre ssa b le c lie nts wo rldwide

in Re ta il, T ra ve l a nd Cla ssifie ds (e xc luding CSP)

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Publishe r Inve ntor y

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60 •

Dir e c t par tne r ships with high- quality publishe r s

PREFERRED ACCESS TO PREMIUM MEDIA INVENTORY ALL MAJOR PUBLIC EXCHANGES, GLOBAL AND LOCAL PREFERRED ACCESS TO RETAILER INVENTORY

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61 •

T hr e e tie r e d appr

  • ac h to me dia buying

Direct Partnership Private Auction Open Auction

RTB Ad Exchanges Custom integration

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62 •

Our two- tie r e d publishe r

  • r

ganization

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63 •

T he publishe r e nvir

  • nme nt is c onstantly e volving

Transition to Mobile Social Native Multiple Devices Header Bidding Ad Blocking

Changing consumer behavior Evolving technology

Programmatic

Our drives more value for publishers

In App

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64 •

We have always de live r e d use r

  • fr

ie ndly ads

Ad bloc king offe r s an oppor tunity for playe r s with:

  • The right business model
  • The right technology stack
  • The right expertise in user privacy
  • Premium demand

Our Position

  • Promote acceptable ad programs
  • Invest in native
  • Support an open tracking standard
  • Define standards for retargeting
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65 •

He ade r bidding c hange s the adve r tising e nvir

  • nme nt

More bidders should mean higher yields Less dependent on a single monetization platform

Allows programmatic buyers to bid for premium inventory

Impact on Publishers Impact on Programmatic Buyers

More inventory available for auction More complex bidding environment can lead to higher costs and less efficiency

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66 •

He ade r bidding c r e ate s oppor tunitie s for smar t playe r s

Short-term, temporary changes in the publisher market place More sophisticated buyers like Criteo will get a technology premium

Time

BEFORE HB GROWTH OF HB BUYERS ADJUST TO HB Unsophisticated buyers Sophisticated buyers Technology premium

Inventory cost

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67 •

  • Criteo Direct Bidder (CDB) allows Criteo to bid on publisher inventory directly through the ad

server without the need to funnel demand through Supply Side Platforms (SSPs) or exchanges.

  • Benefits for the publisher:
  • all of the Criteo bid goes to the publisher; none is taken by the SSP for fees

(typically 10%-20%)

  • user matching between the Publisher and Criteo is much more timely and complete than

matching reliant on a third party

  • +20-40% spend with publishers on the same inventory that was previously accessed

through RTB

  • Launched in Q2 2017, already connected to 1,500 publishers at the of Q4 2017

Cr ite o Dir e c t Bidde r : Dir e c t ac c e ss to Cr ite o’s unique de mand

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SLIDE 68

Compe titive L andsc ape

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SLIDE 69

69 •

Our se lf- r e infor c ing c ompe titive moats ar e diffic ult to r e plic ate

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SLIDE 70

70 •

Our powe r ful Shoppe r Gr aph inc lude s:

  • The Criteo Identity Graph, which connects user identities across devices and

environments

  • The Criteo Interest Map, which provides aggregated shopper intent and

purchasing data across retailers in our ecosystem

  • And, the Criteo Measurement Network, which measures sales attribution for

brands across our many retail partners Openness, transparency, security and fairness are the cornerstones of our commerce marketing ecosystem, where every participant gets more than what they contribute.

Cr ite o Shoppe r Gr aph be ne fits all par tic ipants

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71 •

Compe titive positioning in Comme r c e Mar ke ting

CLOSED OPEN WORKFLOW AUTOMATION PREDICTIVE PERFORMANCE

Note: based solely on Criteo’s qualitative assessment

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SLIDE 72

72 •

DSP Retargeting Mobile Advertising SEM Platforms Social Advertising Ad Servers Email Marketing Marketing Automation Social Media Marketing Web Content Management Data Management Platform Analytics App Measurement Data Providers Tag Management Feed Management Digital Commerce Platform

Adte c h: Paid Me dia Criteo wins 90% of head-to-head tests Mar te c h: Owne d and E ar ne d Me dia Criteo complements these vendors Data and Ope r ations Infr astr uc tur e

Cr i teo i ntegr ates wi th these tec hnol

  • gi

es

Crite o in the Adte c h/ Ma rte c h L a ndsc a pe

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SLIDE 73

73 •

10% 90%

Win r ate in he ad- to- he ad te sts* (% )

We win ove r 90% of he ad- to- he ad te sts base d on pe r for manc e

* Based on 42 head-to-head tests (38 won vs. 4 lost) tracked by Criteo on a global basis across Tier-1 and midmarket advertisers over Jan 2017-Dec 2017

Re ason for not winning te sts

2 – Agency managed spend 2 – Performance/creative reasons

42 tests

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SLIDE 74

Solid tr ac k r e c or d of e xe c ution

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SLIDE 75

75 • 7,832 8,564 9,290 10,198 10,962 11,874 12,882 14,468 15,420 16,472 17,299 18,118 Q1 2015 Q2 2015 Q3 2015 Q4 2015 Q1 2016 Q2 2016 Q3 2016 Q4 2016 Q1 2017 Q2 2017 Q3 2017 Q4 2017

50 100 150 200 250 300

Q1 15 Q2 15 Q3 15 Q4 15 Q1 16 Q2 16 Q3 16 Q4 16 Q1 17 Q2 17 Q3 17 Q4 17 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Wor ld- c lass r e te ntion and fast r e ve nue gr

  • wth

* Annual average of quarterly client retention rates, defined as the percentage of live clients during the previous quarter that continued to be live during the current quarter

Client retention rate* (%) Clients Revenue ex-TAC ($ millions)

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SLIDE 76

76 •

Ve r y pr

  • fitable and highly pr

e dic table busine ss

Revenue ex-TAC ($ millions)

20 40 60 80 100 120 140

Q1 15 Q2 15 Q3 15 Q4 15 Q1 16 Q2 16 Q3 16 Q4 16 Q1 17 Q2 17 Q3 17 Q4 17

Adjusted EBITDA ($ millions)

50 100 150 200 250 300

Q1 15 Q2 15 Q3 15 Q4 15 Q1 16 Q2 16 Q3 16 Q4 16 Q1 17 Q2 17 Q3 17 Q4 17

Actuals Guidance

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SLIDE 77

F inanc ials

slide-78
SLIDE 78

78 •

Solid financ ial tr ac k r e c or d sinc e IPO

147 238 403 534 730 941 2012 2013 2014 2015 2016 2017

1 We define Revenue ex-TAC as our revenue excluding traffic acquisition costs, or TAC, generated over the applicable measurement period. Revenue ex-TAC is not a measure calculated in accordance with U.S. GAAP. Please see the Appendices for a reconciliation of Revenue ex-TAC to Revenue, the most directly comparable GAAP measure. 2 We define Adjusted EBITDA as our consolidated earnings before financial income (expense), income taxes, depreciation and amortization, adjusted to eliminate the impact of equity awards compensation expense, pension service costs, acquisition-related costs and deferred price consideration. Adjusted EBITDA is not a measure calculated in accordance with U.S. GAAP. Please see the Appendices for a reconciliation of Adjusted EBITDA to net income, the most directly comparable GAAP measure.

Revenue ex-TAC1 ($M) Adjusted EBITDA2 ($M)

+45% CAGR

High growth Expanding profitability

22 42 105 143 225 310 2012 2013 2014 2015 2016 2017

+70% CAGR

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SLIDE 79

79 •

225 310

2016 2017

730 941

2016 2017

F ast, pr

  • fitable gr
  • wth and str
  • ng c ash flow

ADJUSTED EBITDA ($M) FREE CASH FLOW ($M)

+29%* +35%* +80%

76 137

2016 2017

REVENUE EX-TAC ($M)

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SLIDE 80

80 •

Str

  • ng financ ial le ve r

age

As % of Revenue ex-TAC FY 2013 FY 2014 FY 2015 FY 2016 FY 2017 Revenue ex-TAC 100% 100% 100% 100% 100% Other cost of Revenue* 7.9% 6.6% 6.1% 6.4% 6.9% Gross margin 92.1% 93.4% 93.9% 93.6% 93.1% R&D* 14.9% 12.5% 13.4% 14.2% 14.7% S&O* 43.6% 39.9% 39.8% 35.3% 34.8% G&A* 16.0% 14.8% 13.8% 13.2% 10.7% Adjusted EBITDA 17.5% 26.2% 26.9% 30.8% 32.9% Revenue ex-TAC margin** 40.3% 40.8% 40.4% 40.6% 41.0%

* Cost of revenue and operating expenses are expressed on a Non-GAAP basis, which excludes the impact of equity awards compensation expense, pension service costs, depreciation and amortization, acquisition-related costs, restructuring and deferred price consideration. ** As a % of revenue

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SLIDE 81

81 •

T e c hnology innovation Br

  • ade r

Supply Upse lling inc r e me ntal pr

  • duc ts and

c hanne ls Ope r ating e xc e lle nc e and pr

  • duc tivity

Str

  • ng dr

ive r s for fur the r

  • pe r

ating le ve r age

spending budgets at limited incremental costs

Powe r e d by a c ombina tion of

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SLIDE 82

82 •

Robust ope r ating c ash flow e nable s smar t inve stme nt

INVEST DEVELOP & GROW CASH SCALE PROFITS SMART INVESTING

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SLIDE 83

83 •

Our financ ial str uc tur e offe r s signific ant fle xibility

* Based on a $2B+ market capitalization, pursuant to the 2017 AGM authorization to issue up to 15,6m shares ** For M&A and equity grants to employees

Strong balance sheet

1,211 1,531

  • Dec. 2016
  • Dec. 2017

Total assets (in $M) Financial liabilities (in $M)

Very low debt

  • Dec. 2016
  • Dec. 2017

86 4 Cash & cash equivalents (in $M)

Significant cash pile

270 414

  • Dec. 2016
  • Dec. 2017

>25%

  • f assets

$414M

cash

As of December 31, 2017

€350M

committed financing

$500M

equity raise capacity*

Share buy-back

authorization**

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SLIDE 84

84 •

Capital alloc ation: Re inve stme nt and M&A to dr ive gr

  • wth

– –

  • Organic

growth M&A

* Average for fiscal years 2013, 2014, 2015, 2016 and 2017

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SLIDE 85

Gr

  • wth

Str ate gy

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SLIDE 86

86 •

  • Evolve go-to-market strategy for Tier 1 and midmarket
  • Further scale midmarket operations worldwide
  • Drive international expansion of

Criteo Sponsored Products Gr

  • w the e c osyste m

Inc r e ase the value for c lie nts and par tne r s

  • Enhance core technology
  • Leverage our powerful Shopper Graph
  • Upsell new products
  • Broaden supply of quality inventory

Our gr

  • wth str

ate gy is base d on two str

  • ng pillar

s

slide-87
SLIDE 87

87 •

We inve st in gr

  • wing ar

e as in Comme r c e Mar ke ting

Criteo Shopper Graph, built on data pooling among ecosystem participants, is the foundation of all new product investments

  • Look alikes*
  • App Install*

Flexible audience-targeting platform Omnichannel marketing

  • In-App
  • Video

Incremental inventory

  • CRM onboarding*
  • Store-to-web retargeting*

Marketing

  • bjectives

Shopping environments Media

* Prospective

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SLIDE 88

88 •

T e c hnology and ne w supply dr ive gr

  • wth fr
  • m e xisting c lie nts

Technology Innovation New Supply

Revenue ex-TAC uplift (%)

Conversion Optimization

+20% uplift

Dynamic Creative Optimization

+10% uplift +8% uplift

Revenue Optimization

+6% uplift

RTB integration improvement

+36% uplift

in Japan

+5% uplift

Worldwide

+10% uplift

Native

+3% uplift

Selected significant examples over time…

Note: the uplift in Revenue ex-TAC from technology innovation corresponds to the increase in Revenue ex-TAC for Criteo on a representative sample of clients, where clients use the corresponding new Engine feature on 50% of their user pool and do not use the corresponding new Engine feature on the other 50% of their user pool, pursuant to a proven 50/50 A/B test methodology. The uplift in Revenue ex-TAC from new sources of inventory supply and new channels corresponds to the increase in Revenue ex-TAC for Criteo on a representative sample of clients, comparing the Revenue ex-TAC generated from those clients before and after the introduction of such new source of inventory supply or new channel.

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SLIDE 89

89 •

Offe ring da ta - drive n solutions a c ross the e ntire shoppe r journe y

  • Criteo Customer Acquisition BETA
  • Criteo Audience Match BETA
  • New audience targeting offerings
  • Criteo Sponsored Products
  • Criteo Dynamic Retargeting
slide-90
SLIDE 90

90 •

L ar ge mar ke t

  • ppor

tunity Cle ar str ate gy Compe titive moats Pr

  • ve n

tr ac k- r e c or d Attr ac tive financ ial pr

  • file

Compe lling inve stme nt the sis

Co mme rc e Ma rke ting is q uic kly e me rg ing a s the ne xt b ig ma rke ting c a te g o ry Build the hig he st pe rfo rming a nd o pe n c o mme rc e ma rke ting e c o syste m T e c hno lo g y Sc a le a nd ne two rk e ffe c ts Ope nne ss Stro ng c lie nt g ro wth with 90% re te ntio n E xc e e de d g uida nc e 17 q ua rte rs in a ro w F a st g ro wth Inc re a sing pro fita b ility Stro ng c a sh flo w

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SLIDE 91

VP, Head of Investor Relations 32, rue Blanche 75009 Paris +33 1 7621 2166 e.lassalle@criteo.com Director, Investor Relations 387 Park Ave South, 12th Floor New York, NY 10016 +1 917 837 8617 f.edelmann@criteo.com

F r ie de r ike E de lmann E douar d L assalle Inve stor Re lations Contac ts: IR@Cr ite o.c om

slide-92
SLIDE 92

Appe ndix

slide-93
SLIDE 93

93 •

($ in thousands) Q1’16 Q2’16 Q3’16 Q4’16 Q1’17 Q2’17 Q3'17 Q4’17 Revenue 401,253 407,201 423,867 566,825 516,667 542,022 563,973 674,031 Less: Traffic acquisition costs 238,755 240,969 247,310 341,877 306,693 322,200 329,576 397,087 Revenue ex-TAC 162,498 166,232 176,557 224,948 209,974 219,822 234,397 276,944

Re ve nue e x- T AC r e c onc iliation

($ in thousands) 2016 2017 Revenue 1,799,146 2,296,692 Less: Traffic acquisition costs 1,068,911 1,355,556 Revenue ex-TAC 730,235 941,136

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SLIDE 94

94 •

Adjuste d E BIT DA r e c onc iliation

($ in thousands) Q1’16 Q2’16 Q3’16 Q4’16 Q1’17 Q2’17 Q3'17 Q4'17 2016 2017 Net income

18,527 13,339 14,724 40,740 14,518 7,505 22,269 52,368 87,329 96,659

Adjustments: Financial (income) expense

1,317 94 570 (1,435) 2,333 2,094 2,886 2,221 546 9,534

Provision for income taxes

7,944 4,450 7,574 13,161 4,201 3,665 7,858 15,927 33,129 31,651

Equity awards compensation expense

8,370 7,695 13,965 13,229 14,940 14,918 22,028 20,464 43,259 72,351

Pension service costs

129 131 132 133 290 299 320 321 524 1,231

Depreciation and amortization expense

12,516 13,300 14,771 16,190 20,167 22,306 23,755 24,570 56,779 90,796

Acquisition-related costs

  • 148

1,793 980 6

  • 2,921

6

Acquisition-related deferred price consideration

40 44 3 (3)

  • 85
  • Restructuring
  • 3,299
  • 40,057
  • 7,356

Total net adjustments

30,316 25,862 38,808 42,255 41,936 46,581 56,847 67,560 137,243 212,925

Adjusted EBITDA

48,843 39,201 53,532 82,995 56,454 54,086 79,116 119,928 224,572 309,584

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SLIDE 95

95 •

F r e e c ash flow r e c onc iliation

($ in thousands) Q4 2016 Q4 2017 2016 2017 CASH FROM OPERATING ACTIVITIES 71,658 79,002 153,470 245,458 Acquisition of intangible assets, property, plant and equipment (30,163) (47,367) (85,133) (121,642) Change in accounts payable related to intangible assets, property, plant and equipment 7,182 21,891 7,752 13,131 FREE CASH FLOW 48,677 53,526 76,089 136,947