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 management’s beliefs and assumptions and on information currently available to management. Forward-looking statements include information concerning our possible or 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. 2 •
Stoc k infor mation and ke y financ ials Ticker: CRTO • 2017 Financials • Revenue: $2,297M, +27% at cc** Stock Exchange: NASDAQ Global Market • Revenue ex-TAC: $941M, +29% at cc CUSIP: 226718104 • Adjusted EBITDA: $310M, +35% at cc Shares outstanding: 66.1M • Adj. EBITDA margin: 33% of Revenue ex-TAC Stock Ownership*: Founders, Idinvest & Yahoo! Japan, 2.2% NEOs, Management & Employees, 13.1% Free float, 84.7% 3 • * On a fully-diluted basis, as of Dec 31, 2017, based on 73.7M fully diluted shares. ** At constant currency
A global c ompany with sc ale Ads served in 2017 Clients Criteos in R&D, tech & business intelligence Sales transactions analyzed in 2017 Employees User identifiers matched in the Criteo Shopper Graph Countries Offices worldwide 4 •
Manage me nt te am Jean-Baptiste Eric Eichmann Benoit Fouilland Rudelle Chief Executive Chief Financial Executive Chairman Officer, 50 Officer, 53 and Co-Founder, 48 Living Social, SAP, K-Mobile, Lucent, Rosetta Stone, Business Objects Roland Berger McKinsey & Co. Mollie Spilman Jonathan Chief Operating Opdyke Officer, 50 Chief Strategy Millenial Media, Officer, 41 Yahoo!, HookLogic, Xerox, Advertising.com, Beyond Interactive Time Warner Patrick Wyatt Tom Aurelio Dan Teodosiu Senior Vice Chief Technology Executive Vice President Product Officer, 51 President, Human Management, 35 Google, Microsoft, Resources, 52 Yahoo!, Estin & Co. Hewlett-Packard Priceline, GE, Symantec, CheerNetworks 5 •
Our vision Build the highe st Conne c t shoppe r s De live r pe r for manc e pe r for ming and ope n to the things the y at sc ale to Comme r c e Mar ke ting ne e d and love par tic ipating E c osyste m r e taile r s and br ands 6 •
Comme r c e mar ke ting is de e ply r oote d in our DNA Technology Performance Scale Global Presence 7 •
We ar e an e nable r and a pione e r 2008 We have since pioneered the industry in many ways… First CPC model in display Mobile Ad Formats App advertising Engine Optimized Segments Product Category level Identity Graph Passback Adaptive Universal CPC bidding Revenue Privacy by Design Largest Hadoop Optimizer Match Kinetic cluster in Europe Design 600 TB We brought Facebook of Data analyzed Conversion Rate performance-based everyday Sizeless personalized Dynamic Optimizer creatives Native Ads marketing Ads to display in 2008 Apple-compliant Interest Map Daily RTB: 55bn bid solution requests, 1.2bn wins Travel Segments in Engine Real-time Facebook TOP ! Dynamic product banners Onetag Bidder Direct Creative Exchange App Deep linking Unique User Optimization 4.5B products imported from merchants everyday Value Prediction AOV Optimizer 8 •
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 Established post-click attribution R&D and Product Teams Client Service Teams Continuous CPC tracking model of sales Maximize Client Sales Transparent performance Constant information in optimization 24/7 client of campaigns interface 9 •
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 Machine-learning technology Thousands of publishers 10 •
T hr e e ke y asse ts suppor t our Comme r c e Mar ke ting E c osyste m $29B Annual post-click sales 6x Shopper Mass 17,000+ Engagement* Personalization Retailers Technology ~1,000 & Commerce Brands Commerce Data Brand & Shopper Funding Graph $600B+ Annual online sales Consumer Reach * Our average click-through rate, or the ratio of clicks generated by our 1,000’s 1.2B+ advertisements over the number of advertising impressions we Direct publishers purchased ("CTR"), was over 0.84% in 2017, which represents a factor Individual shoppers matched of over six times the average click-through rate on Standard Media of 11 • 0.14%, as measured by the DoubleClick display benchmark tool for in our Shopper Graph March-April 2017.
We ar e a global c ompany Amsterdam Stockholm Toronto 2011 2010 2015 London Grenoble Ann Arbor Moscow 2008 2014 2016 2014 Chicago Paris Munich Seoul 2012 Boston 2005 2010 2010 Beijing San Francisco 2012 Istanbul Milan Madrid 2013 2014 2015 Tokyo New York 2012 2014 Barcelona Palo Alto 2011 2011 2014 Osaka 2009 Shanghai Dubai Miami 2016 2014 2015 2015 Los Angeles New Delhi 2015 2016 Singapore 2013 Campaigns in countries São Paulo Sydney 2011 offices in countries 2011 nationalities 12 •
Mar ke t and T r e nds
We b and mobile have c hange d shopping be havior of commerce of shoppers shoppers visit 2+ transactions showroom retailer sites when involve mobile and webroom shopping online 14 •
Suc c e ss fac tor s have c hange d for r e taile r s – and br ands TODA Y YESTERDA Y Shopper Data Activation of Data • Mass scale • Predictive technology • Great real estate • Granularity • Real-time dynamic optimization • Merchandising • Real-time accessibility • Reach at scale 15 •
Data- dr ive n mar ke ting is c r itic al for r e taile r s – and br ands Media Others Technology / AI Brands Others Others Data Offline Online Granular shopper information at massive scale Others Partial, fragmented, unstructured view of the shopper 16 •
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 Not limite d to digital Ce nte r s on inspir ing Me asur e d by pe ople to buy things pe r for manc e – dir e c tly dr iving sale s and pr ofits 17 •
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 18 •
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.
T he Cr ite o Comme r c e Mar ke ting E c osyste m
T he building bloc ks of the Cr ite o Comme r c e Mar ke ting E c osyste m Criteo Criteo Criteo Criteo Product Customer Dynamic Audience Sponsored Portfolio Acquisition BET A Retargeting Match BET A Products Privacy by Design Client 24/7 Client Management Center Platform Direct Integration Indirect Integration Publisher Media Retailers Real-Time Bidding Platforms Network Criteo Engine Product Recommendation Predictive Bidding Kinetic Design Privacy by Design Criteo Identity Graph Measurement Network Interest Map Shopper Graph Commerce Data 21 •
Cr ite o Shoppe r Gr aph
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