Big Data and Analytics. Stephen Gordon, SAS Institute

Transcription

1 Big Data and Analytics Stephen Gordon, SAS Institute

2 Agenda Demystifying Big Data and Analytics Category Management and the Role of Analytics The Changing Face of Loyalty Marketing

3 THE CONTINUED RETAIL TRANSFORMATION ONE SIZE FITS ALL TO PERSONALIZED Yesterday Today "Any customer can have a car painted any color so long as it is black. Henry Ford

4 CUSTOMER CENTRICITY AND PERSONALZIATION ARE NOT NEW Establish Relationships Provide Recognition Offer Relevant Value Develop Understanding

5 SAME BUSINESS JUST MODERNIZED Establish Relationships Provide Recognition Offer Relevant Value Develop Understanding

6 SAME BUSINESS JUST MODERNIZED Establish Relationships Provide Recognition Offer Relevant Value Develop Understanding

7 SAME BUSINESS JUST MODERNIZED Establish Relationships Provide Recognition Offer Relevant Value Develop Understanding

8 SAME BUSINESS JUST MODERNIZED Establish Relationships Provide Recognition Offer Relevant Value Develop Understanding

9 SAME BUSINESS JUST MODERNIZED Establish Relationships Provide Recognition Offer Relevant Value Develop Understanding

10 SAME BUSINESS JUST MODERNIZED Establish Relationships Provide Recognition Offer Relevant Value Develop Understanding

11 Agenda Demystifying Big Data and Analytics Category Management and the Role of Analytics The Changing Face of Loyalty Marketing

12 BIG DATA AND ANALYTICS DEFINED BIG DATA: When Volume, Velocity and Variety of data exceeds an organization s storage or compute capacity for accurate and timely decision-making. ANALYTICS: The application of statistics to understand and interpret data to solve a problem. Three types of Analytics: Descriptive, Predictive, Prescriptive

13 - Distributed Storage - Distributed Processing BIG DATA BASICS HADOOP

14 BIG DATA BASICS HADOOP

15 BIG DATA BASICS BLADES Single Blade Distributed Blades Chassis of Blades Commodity, low cost hardware Extremely powerful and highly scalable Performance is gained by breaking work into tasks that can be done in parallel (MPP Massive Parallel Processing)

16 BIG DATA BASICS GRIDS Client Grid Control Server Commodity Blades Client

17 ANALYTICS BASICS 3 TYPES Descriptive Analytics What happened / why it happened Hindsight reporting and post mortem analysis Predictive Analytics What will happen From data mining and forecasting to probabilities and propensities Prescriptive Analytics What s the best that can happen Optimization simultaneous evaluations of outcomes based on maximizing a particular objective within defined constraints/rules

18 ANALYTIC MATURITY CURVE Proactive Reactive Source: Competing on Analytics Thomas Davenport and Jeanne Harris

19 Agenda Demystifying Big Data and Analytics Category Management and the Role of Analytics The Changing Face of Loyalty Marketing

20 STILL 3 PRIMARY OBJECTIVES KNOW, KEEP & GROW YOUR BEST CUSTOMERS INCREASE NUMBER OF TRIPS PER CUSTOMER INCREASE SPEND / MARGIN PER TRIP

21 BIG DATA, ANALYTICS AND THE 4 P S Promotion Pricing Placement Product 21

22 CATEGORY MANAGEMENT MODERNIZED Personalization Promotion Pricing Placement Product People

23 A DIFFERENT LENS, A DIFFERENT DECISION

24 A DIFFERENT LENS, A DIFFERENT DECISION Decision without Basket Insight Decision with Basket Insight Incremental from Promotion Units Sales $ GM $ Incremental from Other products Baskets Sales $ GM $ Promotion A ($12.00) 1,000 12,000 3, ,397 4,199 Promotion B ($12.00) 800 9,600 2,880 Difference (2,400) (720) ,994 5, ,597 1,799

25 Agenda Demystifying Big Data and Analytics Category Management and the Role of Analytics The Changing Face of Loyalty Marketing

26 THE CHANGING FACE OF LOYALTY The Right Offer The Right Time The Right Place

27 MULTI-LEVEL CUSTOMER ENGAGEMENT Macro Micro Pico General Locale / Venue 500ft - 300ft Diameter Neighborhood / Cross Roads 100ft - 10ft Diameter In the Aisle 10ft 1ft Diameter

28 THE JOURNEY TO PERSONALIZATION GROCERS AFTER THE FACT COUPONS LOYALTY REWARDS GENERIC OFFERS GROCERY ANALYTICS PROPENSITY SCORING OPT OPTIMIZED CUSTOMER- CENTRIC OFFERS Mobile Website OMNI- CHANNEL CUSTOMER- SPECIFIC, PERSONALIZED OFFERS RELEVANT, REAL- TIME, RIGHT-TIME INTERACTIONS CIRCULAR Social Network

29 CUSTOMER ENGAGEMENT WHY DO IT? Sales / Year $ 15,600,000 Sales / Week $ 300,000 Customers / Week 10,000 Sales / Yr Customer Groupings % Customers % Sales % Visits Visits / Wk Sales / Visit Sales / Wk Sales / Yr All Customers Best Customers 20% 60% 40% 2 $45 $90 $4,680 $9,360,000 Potential Best Customers 80% 40% 60% 0.75 $20 $15 $780 $6,240,000 $15,600,000 1% conversion 100 $468,000 $78,000 $390,000

30 Questions