4th African Insurance Distribution & Bancassurance Conference Aug 2014 Presenter: Julian Ardagh.

Transcription

1 4th African Insurance Distribution & Bancassurance Conference Aug 2014 Presenter: Julian Ardagh

2 2 Agenda 1. What is Big Data? 2. Why do we need Big data? Which The key Data benefits sources? 4. What analytics can we use? How Data does sources Predictive Analytics help? 6. How do we support or improve our channels 4. How can different Channels use it?

3 3 Agenda 1. What is Big Data? 2. Why do we need Big data? Which The key Data benefits sources? 4. What analytics can we use? How Data does sources Predictive Analytics help? 6. How do we support or improve our channels 4. How can different Channels use it?

4 4 Big Data What is it?

5 5 Big Data What is it?

6 6 Big Data What is it?

7 7 Big Data What is it?

8 8 What is Big Data really?

9 9 The General View

10 10 The IT View

11 11 The IT View

12 12 The IT View

13 13 Big Data for Business BIG

14 14 The Business View Big Data is about INSIGHTS & UNDERSTANDING your customers

15 15 1 st Benefit - Analytics Aggregated Data of many people s interactions gives Insights into Patterns of Behaviour

16 16 2 nd Benefit - Opportunities Lots of information about 1 Person enables us to Understand what they might Need

17 17 The Bottom Line We can combine this information to Price Risk better & craft more Relevant & Timeous offers

18 18 The Bottom Line The formula is simple: Bigger, Richer Data + Real Time Analytics + Personalized Customer Journeys = Higher ROI

19 19 Agenda 1. What is Big Data? 2. Why do we need Big data? Which The key Data benefits sources? 4. What analytics can we use? How Data does sources Predictive Analytics help? 6. How do we support or improve our channels 4. How can different Channels use it?

20 20 We know the TRIGGERS We all know the key Triggers for identifying good opportunities for selling the different products but HOW do we get more of this information?

21 21 Data Sources

22 22 We leave Digital Footprints

23 23 These lead to Digital Trends

24 24 Data Gathering Facts Marketing is going to be turned upside down innovatively and creatively. We are going to start ASKING customers for information and offering VALUE for this information BEFORE using it to offer products via the CHOSEN CHANNELS.

25 25 Data Gathering Facts The key is to start building continuous sources of Real-time data and Operationalising the gathering and usage of this data.

26 26 Data Gathering Example New cell phone purchase tweeted? Automatic Offer: Cell phone insurance? R40 for 1 st Phone, R15 for each additional phone in family subject to information/permission/app Advantages: Better persistency (Multiple products) Family can be monitored for real-time events Airtime can be offered as incentives which increases loyalty and ability to communicate

27 27 Data Gathering Facts One of the challenge s will be to maintain sales volumes whilst we move from High volume batch campaigns to always-on Customer Engagement Journeys

28 28 Data Gathering Facts Another challenge will be to start building the information whilst we don t have enough to maximise the economics of the investment in new technology

29 29 Agenda 1. What is Big Data? 2. Why do we need Big data? Which The key Data benefits sources? 4. What analytics can we use? How Data does sources Predictive Analytics help? 6. How do we support or improve our channels 4. How can different Channels use it?

30 30 Predictive Analytics

31 31 What do we NEED to know? To sell Insurance EFFECTIVELY we need to know: WHAT a customer needs WHY they need it? WHEN they need it?

32 32 It would be NICE to know? Is this product IMPORTANT to them? Was it an INFORMED PURCHASE DECISION or just a spur of the moment decision? What are their PREFERRED communications channels? How should we ENGAGE in REAL-TIME with them?

33 33 Real-Time Characteristics Real-Time Analysis Real-Time Analytics Real-Time Delivery Right Time Real-Time Action

34 RIGHT TIME Offer versus Timing Generic Offer made at the Right Time Response Up +400% 5% Relevant Offer made at the Right Time Response Up +2,900% 30% Ad-hoc Batch Generic offer made at the Wrong Time Base Response rate 1% Relevant Offer made at the Wrong Time Response Up +100 % 2% By Segment RIGHT OFFER Personalised and optimised 34

35 35 Predictive Modelling

36 36 Operationalising Big Data Social Media Orchestration Hub Car Telematics Mobile Customer Database Adaptors Behavioural Predictive Model Rules Engine No Purchase Next Best Offer Predictive Model Rules Engine Purchase

37 37 Timing gives improved ROI Digital Customer Journey Timing Broker Information Timing

38 38 Agenda 1. What is Big Data? 2. Why do we need Big data? Which The key Data benefits sources? 4. What analytics can we use? How Data does sources Predictive Analytics help? 6. How do we support or improve our channels 4. How can different Channels use it?

39 39 Channels Big Data is about combining channels Mobile powerful interactive platforms Brokers better information & timing triggered long copy TV meshing with interactive offers Call Centres better information > sales Stores build foot traffic using location and special offers

40 40 The New World We are moving ever faster towards an always-on society that expects increasingly speedier and more relevant Service

41 41 The New World Big Data is a Big part of the answer But we must look at the Big Picture.. so what should we do?...

42 42 Critical TO DO s Start building your strategy to Collect and Associate BIG DATA

43 43 Critical TO DO s Start understanding the Intelligent Glue of Orchestration Hubs. They are essential to achieving real-time journeys and they protect your current investments in Software and Hardware

44 44 Critical TO DO s Clearly identify the difference between Batch Campaigns and enabling Real-time Customer Journeys

45 45 Critical TO DO s Start building the value of Big Data into your strategy TODAY

46 46 Big Data ROI faith needed

47 47 Getting to new markets

48 48 New Markets are Mobile The new markets in Africa are mainly reachable by mobile. You have to embrace Real-time automated interactive communications to optimise your investments. You will need Big Data thinking to get there.

49 The Final Message Big Data adds Information and Intelligence and Timing which helps out-perform Competitors and drives PROFITS 49

50 50 Remember If you don t get to the always on customer soon your competitors will. Some are already far down the strategic journey.

51 51 Finally if its too much

52 52 Thank You!