Module 2 Orchestration and Interaction Final

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  • And there is a natural growth path…
  • Create dialogue with client to understand:Where they think they are on the maturity graphWhat they think their organization is ready forWhere are the biggest opportunities
  • More channels Greater need for consistency across channels Even greater need with mergers and acqScale of the problem requires specialized optimization approaches in order to truly optimize
  • SAS has many customer references for MO whereas Unica has very few (e.g. Discover Financial Services)SAS has a number of examples where we have implemented MO where Unica Campaign is in place (and they even had Unica Optimize licensed.)                                                                     
  • Module 2 Orchestration and Interaction Final

    1. 1. Real-Time Analytics & Attribution
    2. 2. • Noah Powers – Principal Solutions Architect, Customer Intelligence, SAS• Patty Hager – Analytics Manager, Content/Communication/Entertainment, SAS• Suneel Grover – Solutions Architect, Integrated Marketing Analytics & Visualization, SAS – Adjunct Professor, Business Analytics & Data Visualization, New York University (NYU)
    3. 3. Client Case Study: Stapleshttp://www.youtube.com/watch?v=84wXOr9ddVI&feature=plcp
    4. 4. Module 2Orchestration & Interaction
    5. 5. Orchestration & Interaction Marketing Decisions Multi-Channel Campaign Management Real-Time Decisions Marketing Optimization Case Studies Information Management & AnalyticsERP CRM EDW Online Social Other Data Sources
    6. 6. Orchestration & Interaction “Interacting with your customers in an appropriate manner drives retention, migration, loyalty and growth. Being able to deliver an appropriate offer – at the righttime, via the right channel and with the right collateral –makes all the difference in satisfying your customer.
    7. 7. Precision Marketing“The Know ME or NO ME savvy consumer voteswith their dollars and defect from brands that arenot relevant.”- Lee Gallagher“Precision marketing is about using data to drivecustomer insights so that you send the right messageto the right person at the right time in the rightchannel.”- Sandra Zoratti
    8. 8. The Street & Precision Marketing http://www.thestreet.com/video/index.html?bcpid=62 7941001001&bckey=AQ~~,AAAAAEBQhPI~,35stD8- Ka9Fwet1OxGtEM5iOnD2FtfSl&bctid=1721392328001
    9. 9. Multi-Channel Campaign Management “Marketers are aggressively shifting budget to digital media and seeing interactive as more effective than traditional efforts. They look now to campaign management applications that enable them to act on and react to empowered customers rather than just integrate more channels.”
    10. 10. January 2012 “The Forrester Wave™: Cross-Channel Campaign Management, Q1 2012”Forrester Wave™: Cross-Channel Campaign Management, Q1 2012 © 2012, Forrester Research, Inc. Reproduction Prohibited
    11. 11. The TV used to be THE tribal camp fire… 11 Copyright © 2011, SAS Institute Inc. All rights reserved.
    12. 12. …but now it’s just another light source. 12 Copyright © 2011, SAS Institute Inc. All rights reserved.
    13. 13. Menu: 1960 TV ChannelsRadio StationsMagazine Titles 13 Media choices used to be limited… Copyright © 2011, SAS Institute Inc. All rights reserved.
    14. 14. 14…but media today is an exotic buffetCopyright © 2011, SAS Institute Inc. All rights reserved.
    15. 15. Example Path to ConversionMany ways to engage along the way! Create Monitor & Increase Engage Conversion Interest Value Interaction Value Time Analyze data to better understand and anticipate customer 15 behavior...and design targeted, relevant interactions. Copyright © 2011, SAS Institute Inc. All rights reserved.
    16. 16. Interactive Marketing Maturity Model Incorporate analytics, integrate online/offline data, multi- Optimized channel campaigns, use analytics to drive new programs and Interactions profitable customer relationships Targeted communications based on behavioral Behavioral segments and clusters, incorporate other Segmentation customer profile dataCompetitive Advantage Timing emails, SMS, etc., with an Event-Triggered “event”, such as a reservation, ticket purchase or birthday Personalized Basic Tailoring content based on preferences and database Segmentation attributes, incorporating previous email campaign “responses” (click-throughs) Batch and Blast Scheduled weekly communications and offers 16 Degree of Engagement Copyright © 2011, SAS Institute Inc. All rights reserved.
    17. 17. Where In The Marketing Process Are We? Information Advanced Analytics Management Business Intelligence MKT DBWeb Data Holistic ViewWarehouse Campaign Management Real-time Decisioning Marketing Optimization Responses Tracked Integrated Workflow 17 Copyright © 2011, SAS Institute Inc. All rights reserved.
    18. 18. Campaign Workflow Manage tasks and details of marketing campaigns 18 Copyright © 2011, SAS Institute Inc. All rights reserved.
    19. 19. Campaign Design Define simple or multi-stage and multi-channel campaigns Manage entire campaign process – from start to finish 19 Copyright © 2011, SAS Institute Inc. All rights reserved.
    20. 20. Define Selections Define a single or multiple range combination Graphically select or enter values directly Update counts instantly Manage waterfall selections 20Copyright © 2011, SAS Institute Inc. All rights reserved.
    21. 21. Reusable Segments Define global inclusions and suppressions Reuse them across campaigns 21 Copyright © 2011, SAS Institute Inc. All rights reserved.
    22. 22. Integrated Analytics Up-to-date propensities based on the most current data Dynamic use of analytic models 22 Copyright © 2011, SAS Institute Inc. All rights reserved.
    23. 23. Manage Tests & Audience Splits Can be based on counts, percentages and customer attributes (e.g. channel, preference, value) Statistical cell sizing calculator to determine minimum cell sizes 23 Copyright © 2011, SAS Institute Inc. All rights reserved.
    24. 24. Multi-Channel Define multi-channel campaigns Link to any fulfilment channel 24 Copyright © 2011, SAS Institute Inc. All rights reserved.
    25. 25. Manage Communication Details Manage offers and channels Fulfilment lists Seeds Tracking for reporting 25 Copyright © 2011, SAS Institute Inc. All rights reserved.
    26. 26. Manage Communication Details Manage offers and channels Fulfilment lists Seeds Tracking for reporting 26 Copyright © 2011, SAS Institute Inc. All rights reserved.
    27. 27. Treatments Create and manage the universe of treatments Assign treatments to a campaign Define custom treatment details 27 Copyright © 2011, SAS Institute Inc. All rights reserved.
    28. 28. Schedule Schedule campaigns and communications Define them as recurring if necessary (e.g. birthdays) 28 Copyright © 2011, SAS Institute Inc. All rights reserved.
    29. 29. Schedule Schedule campaigns and communications Define them as recurring if necessary (e.g. birthdays) 29 Copyright © 2011, SAS Institute Inc. All rights reserved.
    30. 30. Campaign Workflow  Manage approvals  Support different roles on marketing team 30Copyright © 2011, SAS Institute Inc. All rights reserved.
    31. 31. Let’s Imagine A BusinessUse Case…. 31 Copyright © 2011, SAS Institute Inc. All rights reserved.
    32. 32. Cross-sell / Upsell Marketing ApplicationPrint Subscriber Visits Explores Media & Explores Subscription Website & Logs In Marketing Content Bundle Offer 32 Copyright © 2011, SAS Institute Inc. All rights reserved.
    33. 33. Cross-sell / Upsell: Outbound MarketingExplores Subscription CRM Data Bundle Offer On Line Behavior Enrichment Data Trigger Outbound Marketing Advanced Analytics & Campaign (Batch) Scoring 33 Copyright © 2011, SAS Institute Inc. All rights reserved.
    34. 34. #DreamBigger 34 Copyright © 2011, SAS Institute Inc. All rights reserved.
    35. 35. Real-Time Decisioninghttp://www.youtube.com/watch?v=N4TiPtP08LE&hd=1&t=5m59s(Stop Time Stamp: 10:48) 35 Copyright © 2011, SAS Institute Inc. All rights reserved.
    36. 36. Real-Time The ability to present relevant and timely offers based on prior Offer assignment of scores helps prioritize offers based on Management customer eligibility. Real-Time Decision management helps identify interactions to influence or to Decision which to apply various business rules, such as "if [x], then [y]" Management rules, for optimizing campaigns.Real-Time Online Interaction optimization technology is infrastructure that applies Interaction predictive and statistical techniques to tailor online experiences to Optimization meet the needs of individual visitors or visitor segments. 36 Copyright © 2011, SAS Institute Inc. All rights reserved.
    37. 37. Real-Time Decision Making Definition Inbound Communications Smarter Response Organization Customer Real-time decision making enables the real-time delivery of decisions and recommendations that optimize every customer interaction to improve revenue, growth and retention.  Analytical insights (predictive and descriptive)  Business rules  Contact strategy 37 Copyright © 2011, SAS Institute Inc. All rights reserved.
    38. 38. How Does It Work? 38 Copyright © 2011, SAS Institute Inc. All rights reserved.
    39. 39. Isn’t It Nice When Things Are Easy? Inbound Real-Time Campaign Management Outbound Batch Campaign Management 39 Copyright © 2011, SAS Institute Inc. All rights reserved.
    40. 40. Let’s Imagine Another BusinessUse Case…. 40 Copyright © 2011, SAS Institute Inc. All rights reserved.
    41. 41. Real-Time Marketing ApplicationPrint Subscriber Visits Explores Media & Explores Subscription Website & Logs In Marketing Content Bundle Offer 41 Copyright © 2011, SAS Institute Inc. All rights reserved.
    42. 42. Real-Time Decisioning: Inbound Marketing Explores Subscription CRM Data Bundle Offer On Line Behavior Enrichment DataTrigger Inbound Marketing Trigger Outbound Marketing Website Personalization Campaign (Batch) Campaign (Real-Time) 42 Copyright © 2011, SAS Institute Inc. All rights reserved.
    43. 43. Real-Time Decision Diagram: Inbound Targeting Subscriber Logs In Subscriber “Content” Click Content Type Dynamic Analytic Model & Scoring Media & Marketing Potential Upsell Offers Media & Marketing Other Print Digital Print + Digital Offer Decision Real Time Decision RT Decision 43 Copyright © 2011, SAS Institute Inc. All rights reserved.
    44. 44. #NotEvenSheldonCanDoThis 44 Copyright © 2011, SAS Institute Inc. All rights reserved.
    45. 45. Marketing Optimizationhttp://youtu.be/ktUWdngfg98?hd=1 45 Copyright © 2011, SAS Institute Inc. All rights reserved.
    46. 46. Marketing Optimization DefinedMarketing Optimization determines the bestoffer(s) to deliver to each customer through the right channel at the right time 46
    47. 47. Marketing Optimization What’s the best that can happen? Optimization What will happen next? Predictive Modeling What if these trends continue? Forecasting Why is this happening? Statistical Analysis Alerts Query What actions are needed? Drilldown Ad hoc Where exactly is the problem? Reports Std. How many, how often, where? Reports What happened? 47
    48. 48. Marketing Optimization Is An Assignment ProblemCustomers &ProspectsOffers,Services,and Pricing Web Email Mail Mobile Phone Branch ATM AdvisorChannels Checking Credit Cards Lines InvestmentsProducts Savings Loans Mortgages Insurance 48
    49. 49. The Relationship Marketing Context • Many customers, offers, channels • Managing the contact strategy • Looking ahead and behind • How do you allocate offers effectively to maximize return? • Many constraints impact decisions  Budgets, resources, policies • How to respect constraints? • How to reconcile competing goals? • How to plan effectively for change? 49
    50. 50. Optimization Decision Components Decisions  Which Offer(s) to present to each customer and channel Objective  Maximize: Sales, Profit, Response, etc.  Minimize: Cost, Returns Constraints  Aggregate business constraints (e.g. Budget)  Customer/HH level constraints  Customer/HH level contact policies  Contact policies 50
    51. 51. Examples Of Aggregate Constraints Budgets  Spend at most $200,000 on Campaign A Offer counts  Make at least 10,000 offers from Campaign B Channel capacities  Call center is available for only 4,000 hours during June ROI  Require an overall ROI of at least 15% Risk  Average credit score for customers who receive the credit card offer must be at least 700 51
    52. 52. Examples Of Contact Policy Constraints Max/Min contacts  At most 3 offers per household  At most 1 email per customer per week  At least 1 offer to each high-value customer Blocking  Call center blocks direct mail for at least 4 weeks  Mortgage campaign blocks credit card campaign for 2 months General customer-level constraints  Maximum budget of $12 per customer  Maximum call center usage of at most 60 minutes per household 52
    53. 53. Optimization Framework Enables Evaluation Of Trade-offs  What is the impact if I optimize against expected profits instead of expected revenues?  Could I increase profits if my campaign budget is increased? How much?  Is my contact policy optimal? Should I be contacting my customers less frequently?  Is the number of offers required for the campaign ideal? What would happen if this were changed? 5353
    54. 54. Marketing Optimization Applications Financial Services  Insurance policy offers  Credit line increase/decrease  APR to offer on balance transfer offers Telecom  Complex cell phone plan offers  Bundled services  Cross channel offers with different execution costs Hospitality (Hotels, Casinos) » Loyalty offers Retail • Personalized coupons (POS) • Offer prioritization and collisions • Contact stream optimization 54
    55. 55. Illustration of Optimization Benefits Over Business Rule Based Approaches Expected Return = Propensity to respond x Expected Value Customers Checking Mortgage CC Checking 1 100 125 90 2 50 70 75 3 60 80 65Mortgage 4 55 80 75 5 70 60 50 6 75 65 60 Credit Card 7 80 70 75 8 65 60 60 9 90 135 60 55
    56. 56. Campaign Prioritization Based ApproachConstraints: Customers Checking Mortgage CC 1 100 125 901. Each customer must 2 50 70 75 get an offer from at most one campaign 3 60 80 65 4 55 80 752. Each campaign must target at most three 5 70 60 50 customers 6 75 65 60 7 80 70 75 8 65 60 60 9 90 135 60 Expected Return = $670 56
    57. 57. Customer Rules Based ApproachConstraints: Customers Checking Mortgage CC 1 100 125 901. Each customer must 2 50 70 75 get an offer from at most one campaign 3 60 80 65 4 55 80 752. Each campaign must target at most three 5 70 60 50 customers 6 75 65 60 7 80 70 75 8 65 60 60 9 90 135 60 Expected Return = $705 57
    58. 58. Optimization Yields The Best Results Customers Checking Mortgage CCConstraints: 1 100 125 901. Each customer must 2 50 70 75 get an offer from at most one campaign 3 60 80 65 4 55 80 752. Each campaign must target at most three 5 70 60 50 customers 6 75 65 60 7 80 70 75 8 65 60 60 9 90 135 60 Expected Return = $775 58
    59. 59. Not All Decision Approaches Yield The Same Results 10–100+ % Optimization - Solves by taking a 5-10 % holistic approach - Factors in all constraints - Determines the best Customer Rules possible result - First In, First Out - Prioritized by Customer/Campaign - Fails in the face of Prioritization constraints - First In, First Out - Prioritized by Campaign - Does not provide best possible combination 59
    60. 60. Marketing Optimization Process FlowCampaigns Offer definitions Offer costs Offer/customer eligible transactionsCustomer Data Model scores Optimized Output Demographic/behavior O1 O2 O3 O4 O5 .. Oj al information C1 x Marketing Optimization Engine C2 x C3 xContact History Define Examine C4 x OptimizeData Optimization Optimization C5 x Offer/customer contact . x Scenarios Reports x Time of contact x xBusiness Goal x Profit, Revenue Campaign ID - Customer ID – Offer ID What-If Analysis – Channel ID - Time Score/Rank basedConstraints &Business Rules Offer & Channel levels Offer conflict & sequencing Contact Policies Global Opt-outs Budget 60
    61. 61. Case Studies Client Name BenefitsCommerzbank • 55% increase in profitability of DM program • Payback in 4 monthsVodafone (Australia) • 3-10x Response Rate increase • Improve campaign ROI by 4x • 30% reduction in campaign costsScotiabank • 50% Campaign ROI improvementMajor US Insurer • 12% increase in revenue; 52% in earnings • Savings of >$4 million per yearU.S. Regional Telco • $6 million incremental LTV in the 1st monthGlobal Telco • Reduced call center contacts by 25% without decreasing effectiveness#1 Market Share European • Individualized targeting of monthly couponRetailer mailers • Increased offer response rates • Decrease mailing costs 61
    62. 62. Marketing Optimizationhttp://youtu.be/wQYyUDpgDaU?hd=1 62
    63. 63. Sunday Morning Preview• Recognize the key elements of the customer experience and how to manage them.• Know how to integrate online and offline customer data for better, faster decision making.• Understand the critical role of full customer views in assessing customer value and opportunities.
    64. 64. Adaptive Customer Experience Marketing Decisions Customer Experience Analytics Customer Experience Targeting & Personalization Social Media Analytics Case Studies Information Management & Analytics ERP CRM EDW Online Social Other Data Sources
    65. 65. Questions?

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