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How to leverage loyalty data to generate deep customer segmentation?

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How to make us of data gathered from loyalty programs in order to target specific marketing actions towards specific audiences?

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How to leverage loyalty data to generate deep customer segmentation?

  1. 1. FROM DATA TO INSIGHTS HOW TO LEVERAGE LOYALTY DATA TO GENERATE DEEP CUSTOMER SEGMENTATION Comarch Loyalty Breakfast 2017 Maximize profitability thanks to customer insights from Loyalty & Gamification programs
  2. 2. Anna.bazela@comarch.com Anna Bazela Comarch BI Consultant
  3. 3. TODAY’S QUESTION IS… -More and more data -Cheaper space to keep it -Lack of data structure & understanding OBJECTIVE - How do we get from raw data to actionable insight? - How do we use this huge amount of information to understand our customers better and take our business to the next level? - Understand what’s behind the data - Make it meaningful - More and more data - Lack of data structure & understanding CHALLENGEDATA MARKET TRENDS
  4. 4. AGENDA FOR TODAY 1. HOW DO WE USE LOYALTY DATA TO FIND MEANINGFUL PATTERNS ABOUT OUR CUSTOMERS 2. SAMPLE CUSTOMERS REPORTS & DASHBOARDS - LIVE DEMO 3. DATA BASED DECISION MAKING SUPPORT TO OPTIMIZE CUSTOMERS EXPERIENCE
  5. 5. AGENDA FOR TODAY 1. HOW DO WE USE LOYALTY DATA TO FIND MEANINGFUL PATTERNS ABOUT OUR CUSTOMERS 2. SAMPLE CUSTOMERS REPORTS & DASHBOARDS - LIVE DEMO 3. DATA BASED DECISION MAKING SUPPORT TO OPTIMIZE CUSTOMERS EXPERIENCE
  6. 6. CUSTOMERS DO NOT BECOME EASIER CUSTOMER TODAY:  Less loyal & less trusting  Having more and more power (choice, comparison, social media)  Diverse customers types (lifestyle, purchasing power, expectations)
  7. 7. HOW DO WE GET TO UNDERSTAND OUR CUSTOMERS BETTER?
  8. 8. … IT’S EASIER THAN YOU THINK!
  9. 9. INFORMATION TECHNOLOGY, DATA GATHERING AND ANALYTICS MAKE IT POSSIBLE SELF SERVICE BI – USER EXPERIENCE ADVANCED ANALYTICS MOBILE SOCIAL INTELLIGENCEBIG DATAVISUAL ANALYTICS ANALYTICAL SOLUTIONS INTEGRATION WITH OTHER SYSTEMS IN-MEMORY ANALYTICS (HIGHER PERFORMANCE) IOT DATA
  10. 10. ROLE OF BUSINESS INTELLIGENCE IN LOYALTY PROGRAMS BETTER CONTROL OVER THE PROGRAM  Costs  Benefits  ROI UNDERSTANDING CUSTOMER NEEDS INCREASING CUSTOMER EXPERIENCE ABILITY TO PERSONALIZE CUSTOMER EXPERIENCE IN CONTEXT OF:  Communication Channel  Offer Monitoring, control, decision support Better Customer understan- ding Create proper recommendations
  11. 11. AGENDA FOR TODAY 1. HOW DO WE USE LOYALTY DATA TO FIND MEANINGFUL PATTERNS ABOUT OUR CUSTOMERS 2. SAMPLE CUSTOMERS REPORTS & DASHBOARDS - LIVE DEMO 3. DATA BASED DECISION MAKING SUPPORT TO OPTIMIZE CUSTOMERS EXPERIENCE
  12. 12. LIVE DEMO
  13. 13. AGENDA FOR TODAY 1. HOW DO WE USE LOYALTY DATA TO FIND MEANINGFUL PATTERNS ABOUT OUR CUSTOMERS 2. SAMPLE CUSTOMERS REPORTS & DASHBOARDS - LIVE DEMO 3. DATA BASED DECISION MAKING SUPPORT TO OPTIMIZE CUSTOMERS EXPERIENCE
  14. 14. BEHIND THE CURTAINS…
  15. 15. COMARCH BI POINT Dashboards & Reports COMARCH DATA WAREHOUSE MANAGER ETL & Admin of Data Warehouse OUT OF THE BOX ANALYTICAL MODEL Predefined Reports and Dashboards ADVANCED ANAYTICS SERVICES Analytical Extensions … BI PLATFORM TO OPTIMZE CUSTOMER EXPERIENCE
  16. 16. POWER OF DATA IN YOUR LOYALTY STRATEGY Client Lifetime Value Customer Retention / Churn Analysis Points issuance/ redemptions Shop / Site performance Next Best Offer Points/marketing budget expenditures Call center - contact center analysis Sales Staff Analysis
  17. 17. WITH ADVANCED ANALYTICS YOU CAN FIND OUT  Which products are being sold together?  Which products are being sold more often in location A than in location B and why?  Who is my typical client? How can I encourage more of them?  Which products is my bestseller now and why?  To whom shall I direct my next campaign?
  18. 18. x y z f2 f1 SEGMENTATION LOCATION RECOMMENDATION Standard Data ERP CRM CLM SOCIAL MEDIA Other New Data What products he was interested in How much time did he spent What was his route What bought the customer in the first place What action did he make GOING BEYOND TRADITIONAL DATA SOURCES
  19. 19. LOCATION – INTEGRATION WITH COMARCH BEACON  The most visited places analyses,  Heat maps,  Effective exposure and merchandising,  Data mining techniques.
  20. 20.  Geography segmentation: e.g. continent, country, city, district, distance  Socio-demographic segments: e.g. gender, age, family, job, income, car  Behavioral segments: e.g. RFM, segment migrations, churners  Activity segments: within the loyalty program, participation in promotion, cherry pickers, points issuance/redemption/expiration, responsiveness to campaigns, rewards ordering, call-center contacts, mobile application activity, social media activity, surveys answers  Product segmentation: e.g. garden, food, animals  Lifestyle segmentation: home birds, romantic, grab&go DEEP CUSTOMER SEGMENTATION
  21. 21. RECOMMENDATION ENGINE  The most visited places analyses,  Heat maps,  Effective exposure and merchandising,  Data mining techniques. Base Parameters InputData
  22. 22. DATA BASED DECISION MAKING SUPPORT TO OPTIMIZE CUSTOMERS EXPERIENCE (example) SALES & TRANSACTIONAL DATA CUSTOMER DATA ADVANCED ANALYTICS  build segmentation where one of the segments will contain all customers liking product X Plan new promotions CLM BI ANALYSIS  Find which customers bought the most of product X RECOMMENDATION ENGINE  send those customers personalized offer MONITORING  Follow up on results of promotion ; get new insights
  23. 23. IMPROVE CUSTOMER EXPERIENCE (CX) SINGLE CUSTOMER VIEW consumption logs & devices content metadata, ratings, comments transactions and subscriptions social media activity marketing campaign response demographic data customer contacts and service cases personalized content targeted offers and sales next best offer customer acquisition, retention multi-channel marketing programmatic advertising content acquisition product & price strategy data-driven products  micro-segments  scoring  preferences  behavior  interests  history
  24. 24. THANK YOU Any questions?
  • VietNam25

    Feb. 9, 2020
  • jtcliu

    Aug. 21, 2017

How to make us of data gathered from loyalty programs in order to target specific marketing actions towards specific audiences?

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