Van BigData naar BigInsights. Pepijn Born, Team Lead Solu4on Architects

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1 Van BigData naar BigInsights Pepijn Born, Team Lead Solu4on Architects

2 Crystalloids

3 Objective Crystalloids assists optimizing marketing processes & business decisions by integrating predictive analytics into sales and marketing operations improving loyalty, bottom-line results and sustainability.

4 BI & Predictive Analytics Among BI disciplines, predic4on provides the most business value..

5 Sources of BigData E- mail DM SMS Call Center Website Customer Interac&on Processes Advanced Analy&cs Repor&ng 360 Customer View Infrastructure

6 Loyalty programs CRM Personalized Communicatons Privileges Personalized Offers

7 Loyalty programs Loyalty Targe4ng

8 Loyalty Benefits Better customer insights Better lead qualification* Higher visit frequency Longer customer relationships Higher spent Loyalty Targe4ng

9 Loyalty Engage Retain Deepen Grow Loyalty Targe4ng

10 Loyalty Engage Behavioral Loyalty Regain / Retain Loyalty Retain Deepen AFtudinal Loyalty Grow Emo&onal Loyalty Loyalty Targe4ng

11 Loyalty Points Privileges Economic Priority Treatment Special Services Discounts Coupons Presents Rebate Loyalty Targe4ng

12 Targeting Engage Iden&fy Prevent Retain Deepen Describe Predict Grow Loyalty Targe4ng

13 Identify What makes this customer unique? Personal Details Behavior Preferences Interests Customer Satisfaction Your website could be improved, but the customer service is great I like soccer, Red wine, HBO shows and cooking Loyalty I m Jim, 32 years old I shop online but pick up the package in the store I don t like to be called, but you can text me Targe4ng

14 Profile Loyalty Targe4ng

15 Profile Low Frequency High Value High Frequency High Value Low Frequency Low Value High Frequency Low Value Loyalty Targe4ng

16 Profile Spend per visit last year # Visits Last Year 0 Low Value Medium Value High Value Occasional 3 Low Value Shoppers Valuable Occasional Shoppers Infrequent XL Shoppers IntermiKent 29% 32% 10% 6 Frequent 11 Very Frequent Frequent Modest Shoppers 14% Top Shoppers 15%

17 Predict & Prevent Loyalty Targe4ng

18 So far, not BigData specific

19 Creating BigInsights Types of data used in Predictive Analytics Personal Details gender age income Preferences Behavior Interests Customer Satisfaction

20 Creating BigInsights Behavioural Data / Transactional Data Recency Frequency Monetary Value I checked on shoes yesterday The average amount per order is 53,29. I buy 1,3 pair of shoes a year

21 Data Types in Models Rule Probability Avg rental amount per year as booker >= and _H_Number of bookings made non holiday windows >= 6 and _H_Number of visits made in last 4 years >= 2 15,38% Number of visits made in last 2 years >= 2 and Number of visits made in last 3 years >= 5 and _H_Number of bookings made non holiday windows >= 2 8,75% Avg invoice amount per year as booker >= and Number of visits made in last 2 years between {1, 6} and Number of visits made last year between {1, 3} 5,05% Number of visits made in last 3 years between {1, 8} and requested brochures >= 2 3,44% Avg invoice amount per year as booker >= and Number of visits made between {6, 20} and _H_Number of visits made in last 4 years between {2, 4} 3,03% Days between date of last arrival and selection date > 260 0,96% Avg leadtime of non holiday windows between {2, 125} and Number of bookings made between {1, 5} and _H_Number of strategic since 2004 and last arrival between {1, 25} 2,78% Age oldest child <= 10 and Age youngest child <= 3 and Oldest age on an address between {26, 35} 2,50% Adults (30-54) Y/N = "Yes" and Number of visits made in last 3 years between {2, 7} and Relative bookings made >= ,11% Number of visits made in last 2 years between {1, 5} and Oldest age on an address between {44, 68} 1,23%

22 Typical technical roadmap E- mail DM SMS Call Center Website Marke&ng Resource Management Outbound Customer Interac&on (Campaign Management) Contact Op&miza&on Advanced Analy&cs Inbound Customer Interac&on (Real- &me Marke&ng) 360 Customer View Infrastructure Repor&ng

23 Bedankt

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