1.Marketing Analytics in a Week Stephan Sorger, The Analytics Ambassadorwww.StephanSorger.com

2. ABOUT OUR SPEAKER The Analytics Ambassador Author - Marketing Analytics: Strategic Models and Metrics (2013)Professional Expertise - VP Strategic Marketing, On Demand Advisors Academic Expertise - Instructor at UC Berkeley, San Francisco Extension Applying marketing analytics to grow revenueTeaching Marketing Analytics since 2008Board Member - Served on UC Berkeley Ext. Marketing Metrics BoardWebsite: http://www.stephansorger.com LinkedIn: http://www.linkedin.com/in/stephansorger 3. ABOUT THE NEW BOOK Authoritative Guide to Marketing Analytics Over 10 years of professional experience Over 5 years of academic researchComprehensive Nearly 500 pages of text Nearly 400 figures, tables, and graphsPractical Structured around marketing and products, not math Packed with examplesAvailable on Amazon.com: Search on Marketing Analytics: www.amazon.com/Marketing-Analytics-Strategic-ModelsMetrics/dp/1481900307www.StephanSorger.com 4. ON DEMAND ADVISORS: PROCESS2. Market Definition3. Lead Generation4. Lead Management5. Sales Enablement1. Revenue Engineering4www.StephanSorger.com 5. ON DEMAND ADVISORS: CLIENTS5www.StephanSorger.com 6. ON DEMAND ADVISORS: UPCOMING EVENTS Revenue Engineering Workshops held every month: See OnDemandAdvisors.com for complete schedule6www.StephanSorger.com 7. MARKETING ANALYTICS IN A WEEK AGENDA Why a Week?Monday: Defining the problem and building a business caseTuesday: Selecting the people for the projectWednesday: Preparing the technology and dataThursday: Executing the analysis and computing the answerFriday: Gaining insight and presenting the results7IntroductionPractices & Pitfalls www.StephanSorger.com 8. TRENDS DRIVING ANALYTICS ADOPTION Online Data AvailabilityAccountability Improve productivity Reduce costs What gets measured gets doneData-Driven Presentations Data to back up proposals Predict success of plans8Marketing Analytics Adoption Cloud-based data storage Online = speed Online = convenienceReduced Resources Massive Data Initiatives to capture customer information What to do with all that data? Do more with less Scrutinized budgets Marketers must show outcomeswww.StephanSorger.com 9. MARKETING ANALYTICS ADVANTAGES Persuade ExecutivesDrive Revenue Marketing as cost center Marketing as profit center Correlation between spending & resultsSave Money9 Old way: execute campaign & guess outcome No longer tolerate this approach New way: predict outcomeMarketing Analytics Advantages Encourage Experimentation Test multiple scenarios before proceeding Run Simulations Predict which will work best Focus on revenue impact from marketing Correlation between spending & resultsSide-Step Politics Some CEOs do not appreciate marketing Show impact of efforts with metricswww.StephanSorger.com 10. WHAT IS MARKETING ANALYTICS? Its a Wall! It must be Big Data!Its a Fan! It must be Social Media!Its a Rope! It must be Predictive Analytics!Its a Snake! It must be Marketing Automation!10Its a Tree! It must be Google Analytics!www.StephanSorger.com 11. THE MARKETING ANALYTICS FRAMEWORKMarket AnalysisCompetitive AnalysisStrategy and OperationsMarketing Mix The 4 PsSales and SupportChapters 1-3Chapter 4Chapters 5-6Chapters 7-10Chapter 11Segmentation Targeting PositioningCompetitive AnalysisForecasting Big Data Predictive Anyl.Conjoint Google Analytics Social MediaMarketing Auto.Strategic11Analytics in ActionChapter 12Tacticalwww.StephanSorger.com 12. WHY A WEEK? Project Scope vs. Appetite for Quick Results: Day(s): Not credible for all but the most trivial projects Week(s): OK for small initiatives; Easy to digest Month(s): OK for medium initiatives; Perception of major project Year(s): OK for large initiatives; Significant risk management required MondayWednesdayThursdayFridayDefining the problem and building the business case12Tuesday Selecting the people for the projectPreparing the technology and dataExecuting the analysis and computing the solutionGaining insight and presenting the resultswww.StephanSorger.com 13. RUNNING EXAMPLE TopicDescriptionExampleStraightforward marketing analytics project Performed at a Fortune 500 enterprise software firmProblemAssess customer satisfaction of major accountsConstraintLittle budget availability for customer sat surveyApproachCorrelate customer sat with existing dataTimeASAPRegional Office13HeadquartersRegional OfficeCustomerswww.StephanSorger.com 14. MONDAY MondayTuesdayWednesdayThursdayFridayDefining the problem and building the business caseSelecting the people for the projectPreparing the technology and dataExecuting the analysis and computing the solutionGaining insight and presenting the results14www.StephanSorger.com 15. MONDAY TopicDescriptionDefine ProblemState Problem to be Solved Completed to Estimate Project ScopeBuild Business CaseEstimate Cost Savings or Other Benefit Completed to Obtain Budget for ProjectMondayDefine problem15Build business case www.StephanSorger.com 16. BEST PRACTICES: PROBLEM DEFINITION TopicDescriptionProblem DefinitionDescribe clearly the problem to be solved X: Gauge customer satisfaction: Too vague OK: Determine predictive indicators for defection.Success CriteriaDefine success criteria X: Done once data is collected: No outcome OK: Show correlation at 95% confidenceBusiness CaseEstimate savings expected vs. cost X: Will improve customer sat.: Too vague OK: Estimate hard and soft costs16www.StephanSorger.com 17. POLL: PROBLEM DEFINITION QuestionScoreHow many of you have encountered the following: Project proposals without clear problem definitions?_____Project proposals without success criteria?_____Project proposals without dollar-based business cases?_____VOTE 17www.StephanSorger.com 18. RUNNING EXAMPLE: PROBLEM & BUSINESS CASE TopicDescriptionProblem DefinitionDetermine existing indicators of imminent defectionBusiness CaseSee belowCategoryComputationHard Savings: Regional data collection20 reg. mgrs. * 3hr/ea * $100/hrSoft Savings: Customer sat1 lost customer$100,000/hrHard Cost: Marketing analyst40 hr * $100/hr($4,000)Net SavingsSubtotal $6,000$2,000www.StephanSorger.com 19. TUESDAY MondayTuesdayWednesdayThursdayFridayDefining the problem and building the business caseSelecting the people for the projectPreparing the technology and dataExecuting the analysis and computing the solutionGaining insight and presenting the results19www.StephanSorger.com 20. TUESDAY TopicDescriptionCore TeamStatistical modeler: M.S./Ph.D. math or econ;SAS/SPSSData Analyst: B.S.; SAS/R/Pig/SQL; Large data sets Analytics SW Developer: OO; Scrum/Agile; SQLExtended TeamProject Leader Business analyst(s) Evaluator(s)/ Tester(s)Core Team Statistical ModelerExtended Team AnalystProject LeaderEvaluator(s)Developer20Business Analyst(s)Source: Roldan, Alberto: Implementing Business Analytics. Atomai blog. May 5, 2010. Link: http://atomai.blogspot.com/2010/05/implementing-business-analytics.htmlwww.StephanSorger.com 21. SATISTICAL MODELER: SAMPLE Senior Statistical Modeler: SunTrust; Atlanta, GA Responsibilities: Develops or analyzes quantitative models. Researches best practices and new technologies. Performs complex analysis and draws conclusions. Responsible for the analysis and/or development of quantitative models both financial and non-financial in support of the companys risk management effort. Consults with practitioners, the academic community, and other financial institutions in researching the development of risk management models.Qualifications: Masters/PHD degree in a in a quantitative field such as Mathematics, Statistics, Econometrics, Actuarial Science or Engineering. Programming skills (SAS, Matlab, Visual basic). Demonstrated mastery of quantitative modeling requirements for non-parametric type of models. 4+ experience in building Basel compliant models and involved in the entire life-cycle of building models. Basic understanding of financial statements. 22. DATA ANALYST: SAMPLE Data Scientist: Cisco; San Bruno, CA Responsibilities: The Data Scientist will apply disciplined analysis to explore and develop new techniques for identifying and mitigating internet security threats (spam, malware, etc.). Deliverables include research proposals, research documents describing a technique and quantitative measures of expected efficacy improvement, prototypes, functional specifications and ad-hoc measurement tools As a leading team within Cisco STG, the Analysis Team is responsible for developing new techniques to identify and mitigate network security threats, as well as for assessing the efficacy of those techniques in defending against security threats.Qualifications: 5+ years of big-data experience including applied techniques in data mining, machine learning, or graph mining. Experience with Hadoop, Hive, MapReduce, or column stores, as well as working with large, unfiltered data sets. Able to persuade stakeholders and champion effective techniques through product development. Understanding of network security, including email and/or web threats highly desirable. Proficiency with Unix and databases, as well as working knowledge of PERL or Python. Advanced degree in a relevant field is desirable. 23. ANALYTICS SOFTWARE DEVELOPER: SAMPLE Software Engineer, Analytics Big Data Quality: Salesforce.com; SF, CA Responsibilities: Understand and perform analysis on the unique requirements in on-demand multi-tenancy model for Analytics tools assuring that changes to existing functionality are truly required and correctly deployed. Participate in the scrum team under our agile development process utilizing principles such as test-driven-development Perform both functional manual/automated testing of application features using automation tools such as Selenium and JUnit and extensive white-box testing through an application program interface (API).Qualifications: Experienced. Experienced using automation frameworks such as Selenium and JUnit, coming up with comprehensive test plans and tests cases, as well as hands on experience with Java programming and testing. Having BI tool testing experience is definitely a big plus. Highly technical. Strong background in Object-Oriented programming concepts and constructs. Solid knowledge of SQL and understanding of relational database schema design. Testing expert. Industry experience in testing on various types of browsers (Google Chrome, Firefox, IE) and web technologies, such as HTTP, XML, Javascript, HTML5, and CSS3. In depth knowledge of SQA methodologies, tools and approaches (black box, white box and automated testing experience) in testing multi-tier scalable applications. 24. ANALYTICS PROJECT LEADER: SAMPLE Analytics Project Manager: NYC Dept. of IT and Telecomm; Brooklyn, NY Responsibilities: Manage Citywide Performance Reporting (CPR)/Analytics platform support releases and new application development projects Lead the Analytics Production Support team on initiatives necessary to maintain and support the platform for City agencies Manage vendor relationships performing ongoing Analytics support and development work, Security, PMQA, independent contractors and similar engagements, including the creation of RFPs, review/selection of vendors, etc. Ensure that applications are stable and maintainable; Provide information to the public upon request and approval of executive managementQualifications: 3+ years experience managing large projects (end-to-end) Knowledge of SDLC and/or Agile; 2+ years experience in Vendor management, WBS creation, Project and resource planning Proficiency in Microsoft Project and other project management software Business analysis experience creating requirements, use cases, functional specifications preferred Experience with Oracle Business Intelligence Enterprise Edition (OBIEE); PMP certification; experience working with City of New York agencies www.StephanSorger.com 25. BUSINESS ANALYST: SAMPLE Business Analyst: Magenic; San Francisco, CA Responsibilities: Developing use case based requirements specifications to capture project business requirements Managing functional and non-functional requirements artifacts through all development and QA iterations Facilitation of requirements analysis sessions with project stakeholders Collaboration with project stakeholders to establish requirements baseline. Stakeholders include client business team, Magenic development team, third party development teams, QA teamQualifications: Hands on experience as a business analyst in a software production environment Must have experience working with end users and/ or product owners Ideally, some level of experience developing software TFS ideally, and an understanding of how to use it to drive requirements Expression Blend experience a plus A sense of humor and perspective Experience with Agile, or Agile-based, development methodologies www.StephanSorger.com 26. EVALUATOR/TESTER: SAMPLE Analytics Software Tester: JMP (SAS); Cary, NC Responsibilities: As a JMP Analytics Software Tester, you will validate statistical features of JMP. Interact directly with developers to test the numerical accuracy of statistical algorithms during the development life cycle. Ensure quality and functionality of software code that is used to make critical decisions. Understand the needs of JMP's customer base and give usability feedback in order to make data-based analytical problem solving accessible to a wide audience. Research technical literature, maintain test scripts and participate in the documentation review processQualifications: Master's degree in statistics or a related quantitative field including extensive coursework in mathematics. 2 or more years of experience using JMP in a professional capacity. Ability to think analytically and to effectively communicate problems and suggest fixes.26www.StephanSorger.com 27. TUESDAY TopicDescriptionStatistical modeler Data analyst Analytics SW developer Project Leader Business Analyst Evaluator +Executive SponsorCore Team Statistical Modeler Developer27No dedicated modeler due to simple model Data analysis done by product manager No dedicated developer due to simple model Leadership done by product manager Worked with financial business analyst to get data Testing done by product manager VP ProductsExtended Team AnalystProject LeaderBusiness Analyst(s) Evaluator(s)www.StephanSorger.com 28. WEDNESDAY MondayTuesdayWednesdayThursdayFridayDefining the problem and building the business caseSelecting the people for the projectPreparing the technology and dataExecuting the analysis and computing the solutionGaining insight and presenting the results28www.StephanSorger.com 29. ANALYTICS TECHNOLOGY CATEGORIES Category Affiliate Marketing Attribution Analytics Big Data Analytics Customer Acquisition Analytics Data Visualization Direct/email Marketing Analytics Extract, Transform, Load (ETL) Marketing Automation Marketing Intelligence/BI Marketing Tools and Templates Predictive Analytics Social Media Analysis Statistical Software Web Analytics29Sample Companies Linkshare Adometry, Apsalar, VisualIQ Hadoop, Oracle RTD, Teradata Angoss, Nettpositive, Vertex Group Leftronic, QlikView, Tableau Software Icontact, Litmus Astera, Informatica, Snaplogic Eloqua (Oracle), Marketo, Pardot, Act-On IBM, PivotLink, Sybase (SAP) Demand Metric Angoss, Fair Isaac, KXEN Radian6, SproutSocial, Visible Technologies R, SAS, SPSS CoreMetrics, Google, Omniture, WebTrends 30. DATA ANALYSIS: PREPARATION Step Selection Pre-Processing TransformationDataSelect portion of data to target Data cleansing; Removing duplicate records Sorting; Pivoting; Aggregation; MergingData Mining InterpretationSelectionDescriptionFind patterns in data Form judgments based on the patternsPre-ProcessingTarget DataTransformationPreProcessed DataData MiningTransformed DataInterpretationPatternsActionable Informationwww.StephanSorger.com 31. POLL: DATA PREPARATION QuestionScoreHow many of you have encountered the following: Problems with selecting the right data to analyze? Problems with pre-processing the data? (de-duping, etc.) Problems with transforming the data? (merging, etc.)_____ _____ _____VOTE 31www.StephanSorger.com 32. RUNNING EXAMPLE: DATA ANALYSIS PREP StepDescriptionSelection Pre-Processing TransformationLimit data to customers served by regional centers Remove duplicate records Merged two databasesSelectionData32Pre-ProcessingTarget DataTransformationPreProcessed DataData MiningTransformed DataInterpretationPatternsActionable Informationwww.StephanSorger.com 33. THURSDAY MondayTuesdayWednesdayThursdayFridayDefining the problem and building the business caseSelecting the people for the projectPreparing the technology and dataExecuting the analysis and computing the solutionGaining insight and presenting the results33www.StephanSorger.com 34. DATA ANALYSIS: EXECUTION Step Selection Pre-Processing TransformationDataSelect portion of data to target Data cleansing; Removing duplicate records Sorting; Pivoting; Aggregation; MergingData Mining InterpretationSelectionDescriptionFind patterns in data Form judgments based on the patternsPre-ProcessingTarget DataTransformationPreProcessed DataData MiningTransformed DataInterpretationPatternsActionable Informationwww.StephanSorger.com 35. POLL: DATA MINING QuestionScoreHow do you analyze data for patterns: Eyeball it: Look over columns of numbers and identify patterns Sort it: Sort the data and examine trends Analyze it: Conduct regression or other types of analysis_____ _____ _____VOTE 35www.StephanSorger.com 36. RUNNING EXAMPLE: DATA ANALYSIS - EXECUTION StepDescriptionData Mining Pre-Processing TransformationLimit data to customers served by regional centers Remove duplicate records Merged two databasesSelectionData36Pre-ProcessingTarget DataTransformationPreProcessed DataData MiningTransformed DataInterpretationPatternsActionable Informationwww.StephanSorger.com 37. FRIDAY MondayTuesdayWednesdayThursdayFridayDefining the problem and building the business caseSelecting the people for the projectPreparing the technology and dataExecuting the analysis and computing the solutionGaining insight and presenting the results37www.StephanSorger.com 38. COMMUNICATIONS WITH ANALYTICS: BEFORE Engineering Department Status Engineering resources are very low; definitely need more engineersSome engineers working many hours per weekEngineers risk getting burned out from working so many hoursNew projects coming up will require more resources than we haveEngineering resource types Engineering resource type A: have 10 engineers; need at least 12Engineering resource type B: have 3 engineers; need at least 4Engineering resource type C: have 5 engineers; need at least 6Engineering resource type D: have 15 engineers; need at least 20Possible slips to schedule can occur unless we hire more engineersRecommend hiring at least 2 additional engineers in next monthMany engineers complaining to their management about workloadwww.StephanSorger.com 39. COMMUNICATIONS WITH ANALYTICS: AFTERDepartment Revenue and ResourcesProfessional Services Organization Department Status Will Stop Producing Incremental Revenue Here Current Resource LevelProjected RevenueRevenue to DateJanFebMarAprMayJunJulAugSepOctNovDec 40. RUNNING EXAMPLE: DATA PRESENTATION StepDescriptionConclusion Secondary OutcomeMoney Savings Increased AccuracyPrimary Outcome40Problem solved; Correlated variable identifiedBig deal in enterprise software world Ghost-wrote article; Authored by EVP Company positioned as expert in analyticswww.StephanSorger.com 41. KEY TAKE-AWAYS Monday: State clear definitions, success criteria, and business casesTuesday: Identify the right people for the jobWednesday: Adopt skill sets in preparing and merging dataThursday: Be on the lookout for patterns in data; Be open to new onesFriday: Develop presentations that scream Action and Insight41www.StephanSorger.com 42. QUESTIONS?Q&A42www.StephanSorger.com 43. SPONSORAct-On is a leading provider of integrated marketing automation software.Using Act-On, more than 1700 companies tie inbound, outbound and nurturing programs together -across email, web, mobile, and social -- and achieve a superior Return on Marketing Investment. www.act-on.com43www.StephanSorger.com 44. HOSTDemand Metric is a marketing advisory firm serving a membership community of over 30,000 marketing professionals and consultants in 75 countries with consulting methodologies, advisory services, and a library of 500+ premium marketing tools and templates. These tools allow Demand Metric members to plan more efficiently and effectively, and answer the difficult questions about their work with authority and conviction. Demand Metric tools enable members to complete marketing projects more quickly and with greater confidence, boosting the respect of the marketing team and making it easier to justify resources the team needs to succeed. www.demandmetric.com44www.StephanSorger.com