Impact of Social Media & Big Data on Distribution. Prepared for the General Insurance Agents Convention 2016

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Transcription:

Impact of Social Media & Big Data on Distribution Prepared for the General Insurance Agents Convention 2016 August 2016

The world is changing The IBM Model 350 disk file with storage space of 5MB from 1956 and a contemporary Micro SD Card with 128GB of space. 2

A connected world Source: Cisco IBSG 3

Malaysia today Malaysia population ~28,250,000 No. of mobile phones ~30,379,000 > 100% penetration 143.8 connections/100 citizens Source: Wikipedia List of countries by number of mobile phones in use 4

Contents Section 1: Social Media Section 2: Big Data Section 3: Distribution 5

Contents Section 1: Social Media Section 2: Big Data Section 3: Distribution 6

Highly connected Millennials 7

The personal data shield Source: Extracts from the Ogilvy SAS presentation 2013 8

The personal data shield 85% of internet users use search to find products. ~50% used search to find recommendations from other people The top trusted sources for recommendations in Hong Kong are family and friends (~50%) and online product reviews (~50%) (~75%) Brands that use Social Media well, can deliver value across their business and pass through the Personal Message Shield Source: Extracts from the Ogilvy SAS presentation 2013 9

Social Media drives value in four key ways Building Brand Reputation; Demonstrating openness and responsiveness, Delivering more relevant content, Driving third-party advocacy Creating customer value; Activating loyalists, Improving marketing effectiveness, Getting customers to buy more Social Media Increasing operating excellence; Shortening time to market, Reducing cost in development, Testing ideas earlier Strengthening workforce and culture; Enabling employees to advocate, Training the workforce, Improving employee performance Source: Extracts from the Ogilvy SAS presentation 2013 10

Unlocking value is hard 56% Inc 500 companies say Social Media very important to business And while Social Media 69% of executives report measurable business benefits from 20% 80% Just of businesses received of the benefits from Social Media. Source: Extracts from the Ogilvy SAS presentation 2013 11

It requires change Increasing collaboration between marketing, communications, legal, HR and customer service Putting a value on customer and stakeholder advocacy, not just, sales Preparing employees as ambassadors, not just, as a workforce Integrating Social Media across the business. Source: Extracts from the Ogilvy SAS presentation 2013 12

So how can your business do it? Social Media marketing & communications Social customer care Social CRM Source: Extracts from the Ogilvy SAS presentation 2013 13

So how can your business do it? Social Media marketing & communications Social customer care Social CRM Source: Extracts from the Ogilvy SAS presentation 2013 14

Case study: AIA 15

Building advocacy for AIA 16

Building advocacy for AIA What s this insurance about? Hi Sharifah Puteri Chrishty Herklots, AIA Vitality is a unique insurance and health programme that actively supports and rewards you for making healthy choices every day so you can live a heathier, longer and better life.

So how can your business do it? Social Media marketing & communications Social customer care Social CRM Source: Extracts from the Ogilvy SAS presentation 2013 18

People use Social Media to amplify their dissatisfaction 19

Close to 50% of all social media users have used social care Social Care use by age % of social media users 60% 45% 30% 59% 56% 54% 47% 36% 30% 47% 15% 0% 18-24 25-34 35-44 45-54 55-64 65+ Hi Derun Shi, thank you for your comment! We are glad that our financial services consultant has helped you and Consumer your family. Age Groups Best wishes from us to your son for a speedy recovery. Have a great week ahead! Source: Extracts from the Ogilvy SAS presentation 2013 based on the NM Incite Social Care Survey 2012

Customers with positive experience 3x more likely to recommend Likelihood to recommend to others % likely to recommend company/brand based on social care experience ~3.5X Source: Extracts from the Ogilvy SAS presentation 2013 based on the NM Incite Social Care Survey 2012

Lessons in customer care 1. Be prompt 2. Respond to the question 3. Always maintain a respectful attitude 4. Sometimes take it offline

So how can your business do it? Social Media marketing & communications Social customer care Social CRM Source: Extracts from the Ogilvy SAS presentation 2013 23

Traditionally CRM looked at the transaction value of customers Amy: Caroline: $6,000 monthly $2,000 monthly Meet Amy Meet Caroline 35 years, Working, married, no children Savings, Credit Card, insurance 40 years, housewife, 2 kids Savings, Credit Card, insurance, home loan Source: Extracts from the Ogilvy SAS presentation 2013

Social Media provides another dimension of value Amy: Caroline: Brand switcher Low social media influence, but active Unwillling to collaborate Less inclined to brand switch Influencer, has 1,500 active followers + friends, has relevant conversations Willing to cocreate with brands Source: Extracts from the Ogilvy SAS presentation 2013

Traditionally CRM looked at the transaction value of customers Amy: $6,000 with another $1,000 spend potential based on social data Caroline: $2,000 with another $8,000 advocacy potential based on social engagement Opportunity: Use social data to increase individual spend Opportunity: Use social advocacy to increase network spend Source: Extracts from the Ogilvy SAS presentation 2013

The Total Customer Contribution Transaction value: $s for a specific purchase Lifetime value: Transaction x Frequency x Tenure Advocacy value (influence of purchase of others): # of people influenced x probability of changing their purchase behavior x value of purchase Collaboration: Custom designed by category customers who act as innovation advisors or helpers. Source: Extracts from the Ogilvy SAS presentation 2013

Contents Section 1: Social Media Section 2: Big Data Section 3: Distribution 28

The value of data (according to The Economist) 77% Customer support Operations 71% 73% Competitive intelligence Strategic decisions of a company 71% 71% Sales processes Cost management 69% 52% Product development Brand awareness Statistics from The Economist Intelligence Unit s Levelling the playing field: How companies use data for competitive advantage paper. 29

NMG s analytics survey A short survey relating to the use of analytics within the business was conducted across a number of insurance and reinsurance companies (conventional and takaful operators) in the region. Participants were asked various questions relating to the following areas: Availability of data Quality of data Accessibility to data Management information tools Culture of analytics Value of analytics 30

How analytics-driven are companies? 53% of the respondents believe their company has the necessary data available for useful insights. While data is regularly updated from trusted sources, only is consistent over time, while sources. 69% 31% believe their data have issues in integrating data from various 47% have easy access to data and 56% have difficulties in using the data for their analysis. 84% 42% Of the currently using some form of analytical tool, have doubts about its usefulness in addressing their business needs. NMG survey of insurance and reinsurance companies, conventional and takaful, in Singapore, Malaysia, Sri Lanka, Philippines, Vietnam, Thailand and Indonesia. 31

How analytics-driven are companies? 68% of the respondents say that the senior management team actively engage analytics in their strategic decisions. NMG survey of insurance and reinsurance companies, conventional and takaful, in Singapore, Malaysia, Sri Lanka, Philippines, Vietnam, Thailand and Indonesia. 32

So how to we go about developing an analytics-driven company? 33

The four-stage journey The best practices to adopt advanced analytics are typically conducted in four phases*. Building insights Capturing value Achieving scale Becoming an analytics-driven organisation Analytics is operated in silos, fragmented across the organisation. Development of prescriptive and predictive analytics tools to provide insights into the business performance. Analytics remains subscale and yet to cover all functions across the organisation. C-executives commitment, alignment of incentives and adoption of the analytical tools are embedded within the organisation and drive day-to-day business. Analytics services most business units and initiates profitable growth. Analytics shift from being an enabler to being the core way of doing business. Centre of Excellence is developed with dedicated resources, investment and commitment. Analytics becomes the backbone for conducting business and is centralised as a shared service. 360-analytics: Integrated dashboards and real-time management information are available to provide the key decision makers with a full view of the business. Analytics-led strategies and data-driven decision making are the norm. *The four phases approach is retrieved from Chester, A., Clarke R., Libarikian, A. (February 2016). Transforming into an analytics-driven insurance carrier. http://www.mckinsey.com/industries/financial-services/our-insights/transforming-into-an-analytics-driven-insurance-carrier 34

Becoming an analytics-driven company Instead of static reports, all decisions are analytics enabled with visualised key trends, predicting insightful outcomes and prescribing relevant actions 360-degree analytics provide integrated dashboards, inclusive of distribution funnel, portfolio performance, pricing decisions, and drivers of losses and claims. The COE is embedded within the business. Analytics-driven insurance company The financial impact of analytics is blended with price metrics, new-business growth or in-force lapse. The business metrics themselves are the markers of success The human resource adopts analytics in its talent strategy via performance review, expectation management, leadership recruitment and retention *The four phases approach is retrieved from Chester, A., Clarke R., Libarikian, A. (February 2016). Transforming into an analytics-driven insurance carrier. http://www.mckinsey.com/industries/financial-services/our-insights/transforming-into-an-analytics-driven-insurance-carrier 35

A single source of truth 47% of the respondents say that there is a centralised function in the company to provide analytics support. 86% Yet, almost and/or well-integrated data. of these companies face issues with consistent NMG survey of insurance and reinsurance companies, conventional and takaful, in Singapore, Malaysia, Sri Lanka, Philippines, Vietnam, Thailand and Indonesia. 36

A practical example in a detariffication strategy framework NMG Detariffication framework PRODUCT STRATEGY CUSTOMER STRATEGY TECHNICAL PRICING DISTRIBUTION CHANNEL STRATEGY CORE STRATEGY MACROECONOMIC OUTLOOK MARKET PRICING 37

The insurance industry is embracing analytics A success story of a leading UK-based general insurer, who specialises in commercial and niche sectors in personal motor insurance. Challenges Capacity, Storage and Traffic Restrictions Data Management & Analysis done in silos Increased policy count by 50% 5m detection. 120% in 18 months. reduction in customer cancellation rates. savings in claims through real-time fraud Limited visibility in analysis Source: Cloudera s case study on Markerstudy 38 Savings in annual operational costs in rate updates 20% by.

The wish-list Improved data quality People with the right mind-set and skills More sophisticated analytical tools Single source of truth NMG survey of insurance and reinsurance companies, conventional and takaful, in Singapore, Malaysia, Sri Lanka, Philippines, Vietnam, Thailand and Indonesia. 39

Don t be afraid to start now What we want to do VS What we practically can do 40

Contents Section 1: Social Media Section 2: Big Data Section 3: Distribution 41

Buzzwords NMG survey of insurance and reinsurance companies, conventional and takaful, in Singapore, Malaysia, Sri Lanka, Philippines, Vietnam, Thailand and Indonesia. 42

The insurance industry is lagging Source: McKinsry 43

The increasingly complex buying journey for insurance Source: Swiss Re Economic Research and Consulting 44

Case study: ServisHero 45