12/10/2012. Real-Time Analytics & Attribution. Client Case Study: Staples. Noah Powers Principal Solutions Architect, Customer Intelligence, SAS

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1 Real-Time Analytics & Attribution 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) Client Case Study: Staples 1

2 Module 2 Orchestration & Interaction Orchestration & Interaction Marketing Decisions Multi-Channel Campaign Management Real-Time Decisions Marketing Optimization Case Studies Information Management & Analytics ERP CRM EDW Online Social Other Data Sources 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 right time, via the right channel and with the right collateral makes all the difference in satisfying your customer. 2

3 Precision Marketing The Know ME or NO ME savvy consumer votes with their dollars and defect from brands that are not relevant. - Lee Gallagher Precision marketing is about using data to drive customer insights so that you send the right message to the right person at the right time in the right channel. - Sandra Zoratti The Street & Precision Marketing &bckey=AQ~~,AAAAAEBQhPI~,35stD8 Ka9Fwet1OxGtEM5iOnD2FtfSl&bctid= 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. 3

4 January 2012 The Forrester Wave : Cross-Channel Campaign Management, Q Forrester Wave : Cross-Channel Campaign Management, Q , Forrester Research, Inc. Reproduction Prohibited The TV used to be THE tribal camp fire 11 but now it s just another light source. 12 4

5 Menu: 1960 TV Channels Radio Stations Magazine Titles Media choices used to be limited 13 but media today is an exotic buffet 14 Example Path to Conversion Many ways to engage along the way! Create Interest Engage Conversion Monitor & Increase Value Interaction Value Time Analyze data to better understand and anticipate customer behavior...and design targeted, relevant interactions. 15 5

6 Interactive Marketing Maturity Model Incorporate analytics, integrate online/offline data, multichannel campaigns, use analytics to drive new programs and profitable customer relationships Optimized Interactions Competitive Advantage Batch and Blast Targeted communications based on behavioral segments and clusters, incorporate other customer profile data Personalized Basic Segmentation Event-Triggered Tailoring content based on preferences and database attributes, incorporating previous campaign responses (click-throughs) Scheduled weekly communications and offers Behavioral Segmentation Timing s, SMS, etc., with an event, such as a reservation, ticket purchase or birthday Degree of Engagement 16 Where In The Marketing Process Are We? Information Management Advanced Analytics Business Intelligence MKT DB Web Data Holistic View Warehouse Campaign Management Real-time Decisioning Marketing Optimization Responses Tracked Integrated Workflow 17 Campaign Workflow Manage tasks and details of marketing campaigns 18 6

7 Campaign Design Define simple or multi-stage and multi-channel campaigns Manage entire campaign process from start to finish 19 Define Selections Define a single or multiple range combination Graphically select or enter values directly Update counts instantly Manage waterfall selections 20 Reusable Segments Define global inclusions and suppressions Reuse them across campaigns 21 7

8 Integrated Analytics Up-to-date propensities based on the most current data Dynamic use of analytic models 22 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 Multi-Channel Define multi-channel campaigns Link to any fulfilment channel 24 8

9 Manage Communication Details Manage offers and channels Fulfilment lists Seeds Tracking for reporting 25 Manage Communication Details Manage offers and channels Fulfilment lists Seeds Tracking for reporting 26 Treatments Create and manage the universe of treatments Assign treatments to a campaign Define custom treatment details 27 9

10 Schedule Schedule campaigns and communications Define them as recurring if necessary (e.g. birthdays) 28 Schedule Schedule campaigns and communications Define them as recurring if necessary (e.g. birthdays) 29 Campaign Workflow Manage approvals Support different roles on marketing team 30 10

11 Let s Imagine A Business Use Case. 31 Cross-sell / Upsell Marketing Application Print Subscriber Visits Website & Logs In Explores Media & Marketing Content Explores Subscription Bundle Offer 32 Cross-sell / Upsell: Outbound Marketing Explores Subscription Bundle Offer CRM Data On Line Behavior Enrichment Data Trigger Outbound Marketing Campaign (Batch) Advanced Analytics & Scoring 33 11

12 #DreamBigger 34 Real-Time Decisioning (Stop Time Stamp: 10:48) 35 Real-Time Offer Management Real-Time Decision Management Real-Time Online Interaction Optimization The ability to present relevant and timely offers based on prior assignment of scores helps prioritize offers based on customer eligibility. Decision management helps identify interactions to influence or to which to apply various business rules, such as "if [x], then [y]" rules, for optimizing campaigns. Interaction optimization technology is infrastructure that applies predictive and statistical techniques to tailor online experiences to meet the needs of individual visitors or visitor segments

13 Real-Time Decision Making Definition Inbound Communications Organization Smarter Response 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 How Does It Work? 38 Isn t It Nice When Things Are Easy? Inbound Real-Time Campaign Management Outbound Batch Campaign Management 39 13

14 Let s Imagine Another Business Use Case. 40 Real-Time Marketing Application Print Subscriber Visits Website & Logs In Explores Media & Marketing Content Explores Subscription Bundle Offer 41 Real-Time Decisioning: Inbound Marketing Explores Subscription Bundle Offer CRM Data On Line Behavior Enrichment Data Trigger Inbound Marketing Campaign (Real-Time) Website Personalization Trigger Outbound Marketing Campaign (Batch) 42 14

15 Real-Time Decision Diagram: Inbound Targeting Subscriber Logs In Content Type Subscriber Content Click Dynamic Analytic Model & Scoring Media & Marketing Media & Marketing Other Potential Upsell Offers Print Digital Print + Digital Offer Decision Real Time Decision RT Decision 43 #NotEvenSheldonCanDoThis 44 Marketing Optimization

16 Marketing Optimization Defined Marketing Optimization determines the best offer(s) to deliver to each customer through the right channel at the right time 46 Marketing Optimization What s the best that can happen? What if these trends continue? Why is this happening? What will happen next? Alerts Statistical Analysis Forecasting Predictive Modeling Query What actions are needed? Drilldown Ad hoc Where exactly is the problem? Reports Std. How many, how often, where? Reports What happened? Optimization 47 Marketing Optimization Is An Assignment Problem Customers & Prospects Offers, Services, and Pricing Channels Web Mail Mobile Phone Branch ATM Advisor Products Checking Credit Cards Lines Investments Savings Loans Mortgages Insurance 48 16

17 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 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 Budgets Examples Of Aggregate Constraints Spend at most $200,000 on Campaign A Offer counts Make at least 10,000 offers from Campaign B Channel capacities ROI Call center is available for only 4,000 hours during June Require an overall ROI of at least 15% Risk Average credit score for customers who receive the credit card offer must be at least

18 Examples Of Contact Policy Constraints Max/Min contacts At most 3 offers per household At most 1 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 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? 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 18

19 Illustration of Optimization Benefits Over Business Rule Based Approaches Expected Return = Propensity to respond x Expected Value Checking Mortgage Credit Card 55 Campaign Prioritization Based Approach Constraints: 1. Each customer must get an offer from at most one campaign 2. Each campaign must target at most three customers Expected Return = $ Customer Rules Based Approach Constraints: 1. Each customer must get an offer from at most one campaign 2. Each campaign must target at most three customers Expected Return = $

20 Optimization Yields The Best Results Constraints: 1. Each customer must get an offer from at most one campaign 2. Each campaign must target at most three customers Expected Return = $ Not All Decision Approaches Yield The Same Results % Prioritization First In, First Out Prioritized by Campaign Does not provide best possible combination 5-10 % Customer Rules First In, First Out Prioritized by Customer/Campaign Fails in the face of constraints Optimization Solves by taking a holistic approach Factors in all constraints Determines the best possible result 59 Marketing Optimization Process Flow Campaigns Offer definitions Offer costs Offer/customer eligible transactions Customer Data Model scores Demographic/behavior al information Contact History Data Offer/customer contact Time of contact Business Goal Profit, Revenue Score/Rank based Marketing Optimization Engine Define Examine Optimize Optimization Optimization Scenarios Reports What-If Analysis Optimized Output O 1 O 2 O 3 O 4 O 5.. O j C 1 x C 2 x C 3 x C 4 x C 5 x. x x x x x Campaign ID - Customer ID Offer ID Channel ID - Time Constraints & Business Rules Offer & Channel levels Offer conflict & sequencing Contact Policies Global Opt-outs Budget 60 20

21 Case Studies Client Name Commerzbank Vodafone (Australia) Scotiabank Major US Insurer U.S. Regional Telco Global Telco #1 Market Share European Retailer Benefits 55% increase in profitability of DM program Payback in 4 months 3-10x Response Rate increase Improve campaign ROI by 4x 30% reduction in campaign costs 50% Campaign ROI improvement 12% increase in revenue; 52% in earnings Savings of >$4 million per year $6 million incremental LTV in the 1 st month Reduced call center contacts by 25% without decreasing effectiveness Individualized targeting of monthly coupon mailers Increased offer response rates Decrease mailing costs 61 Marketing Optimization 62 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. 21

22 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 Questions? 22