Median Ltm Ebitda Multiples – Saas & Cloud 130

Total Page:16

File Type:pdf, Size:1020Kb

Median Ltm Ebitda Multiples – Saas & Cloud 130 SAAS & CLOUD M&A AND VALUATION UPDATE Q3 2017 BOSTON CHICAGO LONDON LOS ANGELES NEW YORK ORANGE COUNTY PHILADELPHIA SAN DIEGO SILICON VALLEY TAMPA CONTENTS Section Page Introduction ▪ Research Coverage: SaaS & Cloud 3 ▪ Key Takeaways 4-5 M&A Activity & Multiples ▪ M&A Dollar Volume 7 ▪ M&A Transaction Volume 8-10 ▪ LTM Revenue Multiples 11-12 ▪ Revenue Multiples by Segment 13 ▪ Highest Revenue Multiple Transaction for LTM 14 ▪ Notable M&A Transactions 15 ▪ Most Active Buyers 16-17 Public Company Valuation & Operating Metrics ▪ SaaS & Cloud 130 Public Company Universe 19-20 ▪ Recent IPOs 21-32 ▪ Stock Price Performance 33 ▪ LTM Revenue, EBITDA & P/E Multiples 34-36 ▪ Revenue, EBITDA & EPS Growth 37-39 ▪ Margin Analysis 40-41 ▪ Best / Worst Performers 42-43 Notable Transaction Profiles 44-53 Public Company Trading & Operating Metrics 54-61 Technology & Telecom Team 62 1 INTRODUCTION RESEARCH COVERAGE: SAAS & CLOUD Capstone’s Technology & Telecom Group focuses its research efforts on the follow market segments: ENTERPRISE SAAS & MOBILE & WIRELESS CONSUMER INTERNET CLOUD • Analytics / Business Intelligence • Cloud & IT Infrastructure • Cloud Computing / Storage • Communication & Collaboration • Content Creation & Management • CRM & Customer Services • ERP, Supply Chain & Commerce CONSUMER IT & E-COMMERCE • Finance & Administration TELECOM HARDWARE • Human Resources • Marketing & Advertising • Software Conglomerates • Vertical Markets 3 KEY TAKEAWAYS – M&A ACTIVITY & MULTIPLES LTM M&A dollar volume decreased significantly to $60.9B despite Private Company M&A dollar volume increasing » 2016 M&A dollar volume was buoyed by the Microsoft/Linkedin ($29B) and Quintiles/IMS Health ($14B) deals » Q2’17 M&A dollar volume of $9.1B represents a 22.7% decrease from Q1 ‘17 LTM transaction volume reached 1,040 deals as strong deal flow continues » Q2’17 saw 269 deals, up from 259 deals in the prior quarter LTM transaction volume for private targets reached 1,012 deals, slightly below the 2015 peak of 1,015 deals LTM public transaction volume increased to 28 deals, its highest level in recent years Median LTM revenue multiple paid for private companies remained consistent with 2016 at 3.8x Median LTM revenue multiple paid for public companies came in at 2.3x, reaching a five-year low Notable M&A transactions in Q2’17 ▪ Siris Capital / Synchronoss Technologies ($986M) ▪ Vista Equity Partners / Xactly ($533M) ▪ TBG Treuland / Telvent DTN ($900M) ▪ Procera / Sandvine ($426M) ▪ Oracle / Moat ($850M(1)) ▪ Sonus / Genband ($412M) ▪ Cisco / Viptela ($610M) ▪ Aurea Software (Wave Systems) / Jive ($344M) ▪ IAC (HomeAdvisor) / Angie’s List ($574M) ▪ Marlin Equity Partners / Tangoe ($305M) The most active buyers included Vista Equity Partners, j2 Global, IBM, Microsoft, Oracle, Alphabet, Salesforce, and Cisco (sorted by most active) Capstone expects robust M&A activity and attractive exit valuations to continue in the SaaS & Cloud segment in the near term » In the longer term, there is increasing risk that a market correction could negatively impact activity levels and valuation multiples (1) Deal value is inclusive of a $250M earn-out 4 KEY TAKEAWAYS – PUBLIC COMPANY METRICS 11 companies went public during Q2’17, 6 of which were added to the SaaS & Cloud 130 » All but one opened above their offer price but post-IPO performance has been mixed with 5 of the six ending the quarter below their opening price Q2’17 SaaS & Cloud 130 saw a median increase of 11.3% while the NASDAQ posted a gain of 3.9% » The Q2’17 SaaS & Cloud 130 continued to perform strongly as companies reported strong results » The SaaS & Cloud 130 gained 25.8% in the LTM period, underperforming against the NASDAQ’s increase of 26.8% Median LTM revenue multiple jumped to 5.7x in Q2’17 from 5.1x in Q1’17, representing a five-year high » Only 2 segments in the SaaS & Cloud 130 traded below a median revenue multiple of 5.0x Median LTM EBITDA multiple came in at 21.8x, reaching a five-year high Strong stock performances in Q2’17 increased the median LTM P/E multiple to 40.1x compared to 35.8x in Q1’17, representing a five-year high Median revenue growth rate decreased to 21.7% after several years of increasing growth » Revenue growth is expected to slow slightly to a median of 20.7% over the next twelve months Median EBITDA growth rate decreased to 20.1% in LTM 6/30/17, however additional growth expected for NTM as many companies reap the benefits of increased scale driving higher profits Median EPS growth rate increased to 27.7%, representing a five-year high as companies continue to post strong earnings Median gross margins have remained relatively constant for the past five years, increasing slightly in LTM 6/30/17 to 68.5%, representing a five-year high » ERP, Supply Chain & Commerce, commanded the highest gross margin at 76.1% as most of their expenses are operational Median EBITDA margin increased to 14.4% in Q2’17, reversing a five-year decline 5 M&A ACTIVITY & MULTIPLES LTM M&A DOLLAR VOLUME LTM M&A dollar volume decreased significantly to $60.9B despite Private Company M&A dollar volume increasing » 2016 M&A dollar volume was driven by the Microsoft/Linkedin ($29B) and Quintiles/IMS Health ($14B) deals » LTM M&A dollar volume dropped due to the lack of megamergers in 2017 Q2’17 M&A dollar volume of $9.1B represents a 22.7% decrease from Q1 ‘17 $120,000 $100,000 $80,000 $81,327 $60,000 $29,763 $40,000 $28,619 TotalTransaction Value $20,136 $24,028 $20,849 $20,000 $27,900 $27,814 $31,095 $26,208 $22,968 $24,298 $0 2012 2013 2014 2015 2016 LTM Total Private $ Total Public $ 7 LTM M&A TRANSACTION VOLUME BY SEGMENT LTM transaction volume reached 1,040 deals as strong deal flow continues » Q2’17 saw 269 deals, up from 259 deals in the prior quarter Vertical Market is by far the largest segment by deal count, representing 40% of LTM transaction volume, though Cloud & IT infrastructure saw over 150 deals LTM 1200 1000 422 420 800 413 295 600 232 112 90 224 98 95 38 57 60 23 62 26 Transactions 400 80 52 14 57 21 66 19 52 59 47 40 42 41 25 27 37 23 40 47 37 55 40 57 43 26 54 55 17 36 55 200 50 37 31 22 32 44 42 25 82 137 125 151 98 101 117 39 77 66 0 52 49 2012 2013 2014 2015 2016 LTM Analytics / Business Intelligence Cloud & IT Infrastructure Cloud Computing / Storage Communication & Collaboration Content Creation & Management CRM & Customer Service ERP, Supply Chain & Commerce Finance & Administration Human Resources Marketing & Advertising Vertical Market 8 LTM M&A TRANSACTION VOLUME BY DEAL SIZE – PRIVATE TARGETS Private Company M&A activity and valuations continue to grow LTM transaction volume for private targets reached 1,012 deals, slightly below the 2015 peak of 1,015 deals Median transaction size for private targets increased slightly to $40M, equaling the five-year high set in 2015 100% 5 2 5 4 6 8 11 14 3 10 13 13 90% 10 12 7 16 17 11 15 80% 23 27 22 36 23 27 70% 14 16 30 60% 20 17 18 26 23 50% 18 39 28 24 40% 19 33 49 24 30% 40 20% 80 52 46 44 10% 42 42 0% 2012 2013 2014 2015 2016 LTM Total Deals 679 642 865 1015 972 1012 Deals w/ Value 212 164 182 199 158 169 Median ($M) $18 $25 $25 $40 $35 $40 $0-10M $10-25M $25-50M $50-100M $100-250M $250-500M $500M-1B $1B+ 9 LTM M&A TRANSACTION VOLUME BY DEAL SIZE – PUBLIC TARGETS LTM public transaction volume increased to 28 deals, its highest level in recent years » LTM Median deal size decreased substantially to $409M as there was only one $1B+ in Q2’17 compared to the 7 $1B+ deals in Q2’16 » Median deal size increased to $144M in Q2’17 compared to $105M in Q1’17 Q2’17 public transaction volume increased to 11 compared to 4 in Q1’17 100% 90% 6 7 7 8 80% 5 14 70% 4 1 4 5 60% 4 4 1 50% 4 2 2 40% 3 2 1 4 1 1 6 7 30% 1 2 2 2 20% 1 4 2 1 5 10% 6 4 2 2 1 1 0% 1 1 1 2012 2013 2014 2015 2016 LTM Total Deals 26 23 12 27 26 28 Median ($M) $329 $265 $706 $274 $1,536 $409 $0-10M $10-25M $25-50M $50-100M $100-250M $250-500M $500M-1B $1B+ 10 MEDIAN LTM REVENUE MULTIPLES – PRIVATE TARGETS Median LTM revenue multiple paid for private companies remained consistent with 2016 at 3.8x Q2’17 private target median revenue multiple decreased to 3.5x compared to 4.9x in Q1’17 The gap between the 25th and 75th percentile median LTM revenue multiple paid for private companies widened from 2.7x and 7.1x in 2016 to 2.2x and 7.3x in the LTM period 4.5x 4.0x 3.9x 3.8x 3.8x 3.8x 3.6x 3.5x 3.0x 2.8x 2.5x 2.0x 1.5x Median Revenue Multiple Median Revenue 1.0x 0.5x 0.0x 2012 2013 2014 2015 2016 LTM 25th % 1.4x 2.4x 2.2x 1.9x 2.7x 2.2x 75th % 4.3x 6.0x 6.0x 6.0x 7.1x 7.3x 11 MEDIAN LTM REVENUE MULTIPLES – PUBLIC TARGETS Median LTM revenue multiple paid for public companies came in at 2.3x, reaching a five-year low Q2’17 revenue multiple paid for public companies of 1.6x is well below the LTM median and the lowest multiple during the LTM period » Q2’17 saw a total of 11 deals, more than the last two quarters combined, however many deals were take-private deals as companies struggled to maintain growth, resulting in a lower median multiple of 1.3x for Q2’17 4.0x 3.5x 3.6x 3.5x 3.2x 3.2x 3.2x 2.9x 2.9x 3.0x 2.8x 2.6x 2.4x 2.5x 2.5x 2.3x 2.0x 1.5x 1.0x Median Revenue Multiple Median Revenue 0.5x 0.0x 2012 2013 2014 2015 2016 LTM 25th % 1.0x 1.3x 2.2x 0.8x 2.5x 1.1x 75th % 3.4x 4.6x 5.8x 4.5x 6.8x 3.6x All Deals $100M+ Deals 12 MEDIAN LTM REVENUE MULTIPLES BY SEGMENT – LAST 5 YEARS Median LTM revenue multiples across SaaS segments for deals in the past five years ranged from 1.7x to 4.9x » Finance & Administration achieved the highest median multiple of 4.9x, led by SAP’s acquisition of Concur Technologies and Oracle’s acquisition of NetSuite, which had revenue multiples of 12.4x and 10.3x, respectively » Cloud & IT Infrastructure achieved a median multiple of 4.7x as these companies are often acquired earlier in their revenue curve at strong multiples » More commoditized segments like Communication & Collaboration typically garner lower multiples 6.0x 4.9x 5.0x 4.7x 4.0x 4.0x 3.4x 3.3x 3.1x 3.0x 2.7x 2.5x 2.3x 2.3x 2.0x 1.7x 1.0x Median Revenue Multiple MedianRevenue 0.0x 13 HIGHEST REVENUE MULTIPLE TRANSACTIONS FOR LTM LTM Multiple Premium Enterprise Ann.
Recommended publications
  • HW&Co. Landscape Industry Reader Template
    TECHNOLOGY, MEDIA, & TELECOM QUARTERLY SOFTWARE SECTOR REVIEW │ 3Q 2016 www.harriswilliams.com Investment banking services are provided by Harris Williams LLC, a registered broker-dealer and member of FINRA and SIPC, and Harris Williams & Co. Ltd, which is authorised and regulated by the Financial Conduct Authority. Harris Williams & Co. is a trade name under which Harris Williams LLC and Harris Williams & Co. Ltd conduct business. TECHNOLOGY, MEDIA, & TELECOM QUARTERLY SOFTWARE SECTOR REVIEW │ 3Q 2016 HARRIS WILLIAMS & CO. OVERVIEW HARRIS WILLIAMS & CO. (HW&CO.) GLOBAL ADVISORY PLATFORM CONTENTS . DEAL SPOTLIGHT . M&A TRANSACTIONS – 2Q 2016 KEY FACTS . SOFTWARE M&A ACTIVITY . 25 year history with over 120 . SOFTWARE SECTOR OVERVIEWS closed transactions in the . SOFTWARE PRIVATE PLACEMENTS last 24 months OVERVIEW . SOFTWARE PUBLIC COMPARABLES . Approximately 250 OVERVIEW professionals across seven . TECHNOLOGY IPO OVERVIEW offices in the U.S. and . DEBT MARKET OVERVIEW Europe . APPENDIX: PUBLIC COMPARABLES DETAIL . Strategic relationships in India and China HW&Co. Office TMT CONTACTS Network Office UNITED STATES . 10 industry groups Jeff Bistrong Managing Director HW&CO. TECHNOLOGY, MEDIA & TELECOM (TMT) GROUP FOCUS AREAS [email protected] Sam Hendler SOFTWARE / SAAS INTERNET & DIGITAL MEDIA Managing Director [email protected] . Enterprise Software . IT and Tech-enabled . AdTech and Marketing . Digital Media and Content Services Solutions Mike Wilkins . Data and Analytics . eCommerce Managing Director . Infrastructure and . Data Center and . Consumer Internet . Mobile [email protected] Managed Services Security Software EUROPE Thierry Monjauze TMT VERTICAL FOCUS AREAS Managing Director [email protected] . Education . Fintech . Manufacturing . Public Sector and Non-Profit . Energy, Power, and . Healthcare IT . Professional Services . Supply Chain, Transportation, TO SUBSCRIBE PLEASE EMAIL: Infrastructure and Logistics *[email protected] SELECT RECENT HW&CO.
    [Show full text]
  • Auditing Offline Data Brokers Via Facebook's Advertising Platform
    Auditing Offline Data Brokers via Facebook’s Advertising Platform Giridhari Venkatadri Piotr Sapiezynski Elissa M. Redmiles Northeastern University Northeastern University University of Maryland Alan Mislove Oana Goga Michelle L. Mazurek Northeastern University Univ. Grenoble Alpes, CNRS, University of Maryland Grenoble INP, LIG Krishna P. Gummadi MPI-SWS ABSTRACT then selling this information to third-parties such as banks, insur- Data brokers such as Acxiom and Experian are in the business of ance companies, political campaigns, and marketers. The collection collecting and selling data on people; the data they sell is commonly practices of data brokers have been the subject of an ongoing pri- used to feed marketing as well as political campaigns. Despite the vacy debate. For example, data brokers typically only make data ongoing privacy debate, there is still very limited visibility into data available to clients who purchase it, and not to the users who it is collection by data brokers. Recently, however, online advertising actually about [20]. Even worse, public-facing web sites run by data services such as Facebook have begun to partner with data brokers— brokers [10] that purport to reveal the data only report a fraction to add additional targeting features to their platform— providing of what they actually have [19, 47]. In fact, outside of a few niche avenues to gain insight into data broker information. areas (e.g., credit reports), people in the U.S. have limited if any In this paper, we leverage the Facebook advertising system—and rights to determine the provenance of, correct, or even view the their partnership with six data brokers across seven countries—in data these companies have on them [38].
    [Show full text]
  • The Book of Apigee Edge Antipatterns V2.0
    The Book of Apigee Edge Antipatterns Avoid common pitfalls, maximize the power of your APIs Version 2.0 Google Cloud ​Privileged and confidential. ​apigee 1 Contents Introduction to Antipatterns 3 What is this book about? 4 Why did we write it? 5 Antipattern Context 5 Target Audience 5 Authors 6 Acknowledgements 6 Edge Antipatterns 1. Policy Antipatterns 8 1.1. Use waitForComplete() in JavaScript code 8 1.2. Set Long Expiration time for OAuth Access and Refresh Token 13 1.3. Use Greedy Quantifiers in RegularExpressionProtection policy​ 16 1.4. Cache Error Responses 19 1.5. Store data greater than 512kb size in Cache ​24 1.6. Log data to third party servers using JavaScript policy 27 1.7. Invoke the MessageLogging policy multiple times in an API proxy​ 29 1.8. Configure a Non Distributed Quota 36 1.9. Re-use a Quota policy 38 1.10. Use the RaiseFault policy under inappropriate conditions​ 44 1.11. Access multi-value HTTP Headers incorrectly in an API proxy​ 49 1.12. Use Service Callout policy to invoke a backend service in a No Target API proxy 54 Google Cloud ​Privileged and confidential. ​apigee 2 2. Performance Antipatterns 58 2.1. Leave unused NodeJS API Proxies deployed 58 3. Generic Antipatterns 60 3.1. Invoke Management API calls from an API proxy 60 3.2. Invoke a Proxy within Proxy using custom code or as a Target 65 3.3. Manage Edge Resources without using Source Control Management 69 3.4. Define multiple virtual hosts with same host alias and port number​ 73 3.5.
    [Show full text]
  • The Rise of Data Capital
    MIT TECHNOLOGY REVIEW CUSTOM Produced in partnership with The Rise of Data Capital “For most companies, their data is their single biggest asset. Many CEOs in the Fortune 500 don’t fully appreciate this fact.” – Andrew W. Lo, Director, MIT Laboratory for Financial Engineering “Computing hardware used to be a capital asset, while data wasn’t thought of as an asset in the same way. Now, hardware is becoming a service people buy in real time, and the lasting asset is the data.” – Erik Brynjolfsson, Director, MIT Initiative on the Digital Economy as retailers can’t enter new markets and security. The pursuit of these Executive Summary without the necessary financing, they characteristics drives the reinvention Data is now a form of capital, on the can’t create new pricing algorithms of enterprise computing into a set of same level as financial capital in terms without the data to feed them. In services that are easier to buy and of generating new digital products nearly all industries, companies are use. Some will be delivered over the and services. This development has in a race to create unique stocks of Internet as public cloud services. implications for every company’s data capital—and ways of using it— Some corporate data centers will be competitive strategy, as well as for before their rivals outmaneuver them. reconfigured as private clouds. Both the computing architecture that Firms that have yet to see data as a raw must work together. supports it. material are at risk. New capabilities based on this new Contrary to conventional wisdom, The vast diversity of data captured architecture, such as data-driven data is not an abundant resource.
    [Show full text]
  • Manpreet Singh
    MANPREET SINGH SUMMARY OF EXPERTISE ​ ​ ● 1 Year of Co-op experience at SAP as SLT/HANA Product support Engineer. ● 2+ years of full time experience in US IT firm named Cognizant as Java and ESB Developer. ● Broad understanding of Machine Learning, AI and hands on with latest developments in IoT. ● Experience in Penetration Testing, Intrusion Detection, Digital forensics and Risk Management. ● Sound Knowledge and Experience in Google API Management Platform named Apigee. ● Well acquainted with knowledge related to IT Infrastructure and SOA architecture. ● Good organizational, analytical, problem-solving skills and a great team player. ACADEMIC & PROFESSIONAL DEVELOPMENT Master of Engineering (Sep 2017 - Apr 2019) University of Victoria, Canada ​ Electrical and Computer Engineering Bachelor of Technology (Aug 2011 - May 2015) LPU, Punjab, India Electronics and Communication Engineering TECHNICAL SKILLS Enterprise Tools SAP SLT, Apigee Edge, SAG webMethods, Soap UI, Splunk, SNow Penetration Testing Tools Nessus, Zenmap, Wireshark, Hydra, Burp-suite, Metasploit Programming C++, Java, Python Database MySQL Web Development Wordpress, HTML5, CSS3 Network TCP/IP, OSI Model, WLAN/LAN technologies Operating System Windows, Linux (Kali), Mac OS, iOS, Android Interpersonal Leadership, Teamwork, Time Management, Communication WORK EXPERIENCE Software Dev QA Engineer 1 (August 2019- Present) Fortinet Technologies, Burnaby, BC Canada. ● Work as Software developer for various security interfaces. ● Work as QA engineer for testing the code in production and development. Product Support Engineer (Sept 2018 – August 2019) SAP, Vancouver, Canada SAP Landscape Transformation Replication Server (SLT) Engineer ● Worked as a SLT product support engineer; handling Configurations, Troubleshooting and Incident Handling for top SAP clients. ● Handled (VH) priority issues for real business problems using live troubleshooting sessions for Max Attention Customers like Apple, Porsche, Coca-Cola.
    [Show full text]
  • From Legi(Macy to Informed Consent: Mapping Best Prac(Ces and Iden
    From legimacy to informed consent: mapping best pracces and idenfying risks A report from the Working Group on Consumer Consent May 2009 PEN paper 3 About the Working Group The Working Group on Consumer Consent is a project convened by the Information Systems & Innovation Group of the London School of Economics and Political Science and administered by 80/20 Thinking Ltd, based in London UK. The Working Group aims to bring together key industry players, consumer experts and regulators to achieve the following goals: • To better understand the implications of the Article 29 Working Party Opinion on data protection issues related to search engines (April 2008) and its potential impact on the processing of personal information in the non-search sectors. • To foster dialogue between key stakeholders to map current practices relating to notification and consent. • To inform regulators about limitations and opportunities in models and techniques for informed consent for the processing of personal information. • To help inform all stakeholders on aspects of the pending Article 29 Opinion on targeted advertising planned in 2009. Membership The members of the Working Group included: AOL, BT, Covington & Burling, eBay, Enterprise Privacy Group, Facebook, the Future of Privacy Forum, Garlik, Microsoft, Speechly Bircham, Vodafone, and Yahoo! We also sought comments from a number of privacy commissioners and regulators from across Europe. Methodology, Meetings, and Outreach We have been actively engaging with policy-makers and regulators since the creation of the group. This networking not only enhances the quality of the research, but also goes some way to identify and prepare the audience for our discussion papers.
    [Show full text]
  • Google Cloud Whitepaper
    1 Table of contents Introduction 3 The compliance landscape for UK health and social care data 4 Legislation governing UK health data 4 Overview of NHS Digital in England 6 Overview of the Use of Public Cloud Guidance 6 Overview of the DSP Toolkit 7 Google Cloud Platform information governance overview 8 Google Cloud Platform’s approach to security and data protection 8 The Shared Responsibility Model 12 How Google Cloud Platform meets NHS Information Governance requirements 13 Data Security Standard 1 13 Data Security Standard 2 20 Data Security Standard 3 22 Data Security Standard 4 22 Data Security Standard 5 25 Data Security Standard 6 26 Data Security Standard 7 29 Data Security Standard 8 31 Data Security Standard 9 32 Data Security Standard 10 33 How Google Cloud Platform helps customers meet their DSP Toolkit requirements 34 Google Cloud Platform products to help with compliance 34 Google Cloud Platform Terms of Service and Conditions 37 Additional Resources to help Google Cloud Platform customers 37 Conclusion 38 2 Disclaimer This document was last updated in O ctober 2020 a nd is for informational purposes only. Google does not intend the information or recommendations in this document to constitute legal advice. Each customer must independently evaluate its own particular use of the services as appropriate to support its legal compliance obligations. Since Google is continually improving security and other features for our customers, some of the policies, procedures, and technologies mentioned in this document may have changed. Please visit cloud.google.com/security/compliance or contact your Google Cloud Account Representative to check for updated information.
    [Show full text]
  • Secret Consumer Scores and Segmentations: Separating Consumer 'Haves' from 'Have-Nots' Amy J
    University of Missouri School of Law Scholarship Repository Faculty Publications 2014 Secret Consumer Scores and Segmentations: Separating Consumer 'Haves' from 'Have-Nots' Amy J. Schmitz University of Missouri School of Law, [email protected] Follow this and additional works at: http://scholarship.law.missouri.edu/facpubs Part of the Law and Society Commons, and the Legal Remedies Commons Recommended Citation Amy J. Schmitz, Secret Consumer Scores and Segmentations: Separating "Haves" from "Have-Nots", 2014 Mich. St. L. Rev. 1411 (2014) This Article is brought to you for free and open access by University of Missouri School of Law Scholarship Repository. It has been accepted for inclusion in Faculty Publications by an authorized administrator of University of Missouri School of Law Scholarship Repository. SECRET CONSUMER SCORES AND SEGMENTATIONS: SEPARATING "HAVES" FROM "HAVE-NOTS" Amy J Schmitz* 2014 MICH. ST. L. REV. 1411 ABSTRACT "Big Data" is big business. Data brokers profit by tracking consumers' information and behavior both on- and offline and using this collected data to assign consumers evaluative scores and classify consumers into segments. Companies then use these consumer scores and segmentationsfor marketing and to determine what deals, offers, and remedies they provide to different individuals. These valuations and classifications are based on not only consumers 'financial histories and relevant interests, but also their race, gender, ZIP Code, social status, education,familial ties, and a wide range of additional data. Nonetheless, consumers are largely unaware of these scores and segmentations, and generally have no way to challenge their veracity because they usually fall outside the purview of the Fair Credit Reporting Act (FCRA).
    [Show full text]
  • Economic and Social Impacts of Google Cloud September 2018 Economic and Social Impacts of Google Cloud |
    Economic and social impacts of Google Cloud September 2018 Economic and social impacts of Google Cloud | Contents Executive Summary 03 Introduction 10 Productivity impacts 15 Social and other impacts 29 Barriers to Cloud adoption and use 38 Policy actions to support Cloud adoption 42 Appendix 1. Country Sections 48 Appendix 2. Methodology 105 This final report (the “Final Report”) has been prepared by Deloitte Financial Advisory, S.L.U. (“Deloitte”) for Google in accordance with the contract with them dated 23rd February 2018 (“the Contract”) and on the basis of the scope and limitations set out below. The Final Report has been prepared solely for the purposes of assessment of the economic and social impacts of Google Cloud as set out in the Contract. It should not be used for any other purposes or in any other context, and Deloitte accepts no responsibility for its use in either regard. The Final Report is provided exclusively for Google’s use under the terms of the Contract. No party other than Google is entitled to rely on the Final Report for any purpose whatsoever and Deloitte accepts no responsibility or liability or duty of care to any party other than Google in respect of the Final Report and any of its contents. As set out in the Contract, the scope of our work has been limited by the time, information and explanations made available to us. The information contained in the Final Report has been obtained from Google and third party sources that are clearly referenced in the appropriate sections of the Final Report.
    [Show full text]
  • Department of Defense Enterprise Devsecops Initiative
    Headquarters U.S. Air Force I n t e g r i t y - S e r v i c e - E x c e l l e n c e How did the Department of Defense move to Kubernetes and Istio? Mr. Nicolas Chaillan Chief Software Officer, U.S. Air Force Co-Lead, DoD Enterprise DevSecOps Initiative V2.5 – UNCLASSFIED Must Adapt to Challenges Must Rapidly Adapt To Challenges I n t e g r i t y - S e r v i c e - E x c e l l e n c e 2 Must Adapt to Challenges Work as a Team! Must Adapt To Challenges I n t e g r i t y - S e r v i c e - E x c e l l e n c e 3 Must Adapt to Challenges Work as a Team! A Large Team! Must Adapt To Challenges I n t e g r i t y - S e r v i c e - E x c e l l e n c e 4 Must Adapt to Challenges With Various TechnologiesWork as a Team! A Large Team! Must Adapt To Challenges I n t e g r i t y - S e r v i c e - E x c e l l e n c e 5 Must Adapt to Challenges With Various Technologies Work as a Team! A Large Team! Must AdaptBring To Challenges It With Us! I n t e g r i t y - S e r v i c e - E x c e l l e n c e 6 Must Adapt to Challenges With Various Technologies Work as a Team! Even To Space! A Large Team! Must AdaptBring To Challenges It With Us! I n t e g r i t y - S e r v i c e - E x c e l l e n c e 7 Must Adapt to Challenges With Various Technologies Work as a Team! To Space! A Large Team! MustWith Adapt a FewBring To Sensors! Challenges It With Us! I n t e g r i t y - S e r v i c e - E x c e l l e n c e 8 With Their Help! Must Adapt to Challenges With Various Technologies Work as a Team! To Space! A Large Team! MustWith Adapt a FewBring To Sensors! Challenges It With Us! I n t e g r i t y - S e r v i c e - E x c e l l e n c e 9 What is the DoD Enterprise DevSecOps Initiative? Joint Program with OUSD(A&S), DoD CIO, U.S.
    [Show full text]
  • Enterprise Procurement with GCP Marketplace Spend Smart, Procure Fast, and Help Your Development Team Succeed
    Enterprise Procurement with GCP Marketplace Spend smart, procure fast, and help your development team succeed Be development’s strategic business partner Google Cloud offers a robust, enterprise-tailored, and vetted set of business solutions that will help establish you as a development ally. Spend strategically with options that can draw down your GCP committed spend, and enable your developers to procure directly from GCP Marketplace. Lastly, simplify multi-cloud billing with Orbitera Cloud Billing and Cost Management. Benefits ● Solutions are vetted by Google for security “We use GCP Marketplace to sell our vulnerabilities. Deployment options for industry-leading security solutions and for GCP, on-prem, and multi-cloud. purchasing because they support enterprise procurement with features such as private ● Solutions offer deployment templates so pricing and subscriptions." they launch quickly into the destination environment. Jane Chung VP Public Cloud ● Flexible and consolidated billing models Palo Alto Networks that fit your business needs. What’s new? Partner spotlight Free trial capability for Kubernetes, SaaS, and VM solutions. Subscription and private pricing options for some paid solutions. Anthos applications which can be deployed on-prem and in Google Cloud. For more information visit ​cloud.google.com/marketplace Features No Separate Billing Relationships Flexible Pricing Get solutions to your team fast by eliminating the Get individualized solution pricing quotes with need for separate billing agreements for partner private pricing. Subscription and usage-based solutions. Purchases from GCP Marketplace billing models fit various business needs. have Google as the seller of record. Retire Committed Spend Integrated Solutions Solutions procured through GCP Marketplace Remove deployment headaches with solutions may count toward GCP committed spend, if you that are tightly integrated with GCP and feature have a GCP spend agreement.
    [Show full text]
  • Formatting Guide: Colors & Fonts
    SAAS & CLOUD M&A AND VALUATION UPDATE Q1 2016 BOSTON CHICAGO LONDON LOS ANGELES NEW YORK ORANGE COUNTY PHILADELPHIA SAN DIEGO SILICON VALLEY TAMPA CONTENTS Section Page Introduction . Research Coverage: SaaS & Cloud 3 . Key Takeaways 4-5 M&A Activity & Multiples . M&A Dollar Volume 7 . M&A Transaction Volume 8-10 . LTM Revenue Multiples 11-12 . Revenue Multiples by Segment 13 . Highest Revenue Multiple Transaction for LTM 14 . Notable M&A Transactions 15 . Most Active Buyers 16-17 Public Company Valuation & Operating Metrics . SaaS & Cloud 125 Public Company Universe 19-20 . Recent IPOs 21 . Stock Price Performance 22 . LTM Revenue, EBITDA & P/E Multiples 23-25 . Revenue, EBITDA & EPS Growth 26-28 . Margin Analysis 29-30 . Best / Worst Performers 31-32 Notable Transaction Profiles 34-43 Public Company Trading & Operating Metrics 45-50 Technology & Telecom Team 52 1 INTRODUCTION RESEARCH COVERAGE: SAAS & CLOUD Capstone’s Technology & Telecom Group focuses its research efforts on the follow market segments: ENTERPRISE SAAS & MOBILE & WIRELESS CONSUMER INTERNET CLOUD • Analytics / Business Intelligence • Cloud & IT Infrastructure • Cloud Computing / Storage • Communication & Collaboration • Content Creation & Management • CRM & Customer Services • ERP, Supply Chain & Commerce CONSUMER IT & E-COMMERCE • Finance & Administration TELECOM HARDWARE • Human Resources • Marketing & Advertising • Software Conglomerates • Vertical Markets 3 KEY TAKEAWAYS – M&A ACTIVITY & MULTIPLES LTM M&A dollar volume continued to increase in Q1’16, representing
    [Show full text]