HPMC12: Aviva - Existing Customer Management: Poor data,no analytics,no chance?

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HPMC12: Aviva - Existing Customer Management: Poor data,no analytics,no chance?

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Presented during the High Performance Marketing Conference 2012, organized by Accenture on February 9th 2012. This presentation given by Aviva discusses the challenges organizations are facing due......

Presented during the High Performance Marketing Conference 2012, organized by Accenture on February 9th 2012. This presentation given by Aviva discusses the challenges organizations are facing due to the continued macro economic uncertainty and changing consumer behavior.

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  • 1. High Performance MarketingConference 2012Aviva UK Life & Pensions? Copyright © 2010 Accenture All Rights Reserved. Accenture, its logo, and High Performance Delivered are trademarks of Accenture.
  • 2. Aviva UK Life & Pensions Existing Customer Management: Poor data, no analytics, no chance?Copyright © 2010 Accenture All Rights Reserved. Accenture, its logo, and High Performance Delivered are trademarks of Accenture.
  • 3. Contents • Background & Context • Existing Customer Management • From Tactical to Strategic • Benefits & Reflections 3
  • 4. Background & context 4
  • 5. About Aviva A significant global business: - 6th largest insurer globally - 44m customers - 12 focus markets - 36,000 employees - 300bn+ funds under mgt A clear strategy: - Geographic focus - Exploit composite advantage - Build on core capabilities© 2011 Accenture. All rights reserved. 5
  • 6. Aviva UK – a 300 year pedigree • Life, pensions, savings and retirement UK Life • 12% market share • 6.5m customers mostly through IFA and Bancassurance • House, car, pet, business insurance UK GI • Direct and broker distribution • 6m customers • Private medical insurance and group UK Health risk • Direct and intermediated business • #3 in market© 2011 Accenture. All rights reserved. 6
  • 7. Aviva UK Life – the problem and the opportunity Problem  More customers leaving than arriving Existing Customer  £XXXm commission bill Management:  Creaking legacy infrastructure “We’ll invest in analytics-led customer  Overwhelmingly intermediated marketing to drive more value from our existing base” Opportunity  6.5m customers  Regulatory dynamics  Compelling customer brand© 2011 Accenture. All rights reserved. 7
  • 8. Existing Customer Management 8
  • 9. Starting from a low baseOld approach constrained by: New brand position focused Existing Customer Management on understanding the team created individual customer and being relevant • Poor view of customer • Increase up/ cross sell, data retention, rollover • No analytics tools campaigns with analytics • No analytical skills • Identify additional • Campaign selections opportunities by intuition / experience • Build Aviva internal sustainability • Little visibility of new opportunities • Define the roadmap and investment case • DM campaigns with long lead times • Pilot value from customer analytics • Belief DQ = bad
  • 10. Key project phases and evolution of capability Proof of value / pilot Value exploitation Analytics managed service Feb’10 Aug.’10 Feb’ 11 Jul’ 11 March 2012 •Data Check •Exploratory Analytics •Test Campaigns •Process Changes •Build Awareness •Increase Campaign Volumes •Test Multiple Channels / Mechanics •Broaden Use UK •Inform Customer Retention Strategy •Inform IFA Analytics Proposition Italy •Campaign Prioritisation India •Pure Off-shore Model •Transition To In-House (plan)© 2011 Accenture. All rights reserved. 10
  • 11. Did we have poor data? We developed a new “single-view-of-the- customer” Life Insurance Data Model Structure Policy Value Segment Complaints Demographics Claims Payments DWH DWH CampaignsAccenture’s Life InsuranceCustomer Analytic Record (CAR):• Facilitates rapid descriptive and propensity model development• Identified overall data quality and identify key data gaps. 11© 2011 Accenture. All rights reserved.
  • 12. If you really want to know what it looked like…
  • 13. Descriptive Modelling: shining a light to identify value Multiple Layers Of Analysis …. 2ND POLICY 1ST POLICY Annuities Group Pension • X.X million Life policyProtection records in our CIC database Investments Individual Pension Equity Release holder Unknow Grand Total Life 31% are joint 59% Annuities 0% 31% 2% 3% 4% 0% 88,528 GPP policies Investments 8% 5% 49% 1% • X.X million are currently active 3% 66% 21% 9% 0% 0% 19% 18% 0% 0% 48,815 442,480 IPP 18% 7% 11% 40% 0% 24% 0% 331,664 Equity Release Protection 3% 2% 0% 3% • Average Life product holding is 1.06 products. 19% 8% 0% 9% 64% 1% 13% 77% 0% 0% 9,382 407,887 Uknown Life 8% 2% 50% 9% 1% 21% 10% 4,953XXm no longer active X.Xm active Life1 Grand Total 11% 5% • Average 17% policy holding is 1.2 policies. 29% Life 1% 36% 0% 1,333,709 Life1 Customers Customers Product PH with Single PH with Single PH with PH with Total Policy Holdings Policy (#) Policy (%) multiple multiple Holders (PH) policies within policies within (#) same product same product X.Xm customers X.Xmil X.Xm customers holding holding (%) with at least one customers with with at least one Protection Protection policy at least one IPP Investment policy, 0.5m for policy Investments GPP, 0.6m for IPP Annuities, 0.1m for Equity GPP Release Annuities Equity Release X.Xm Active Life1 X.Xm Active Joint Policies Life1 Policies X.X.m Policyholders are between 35 and 49 and represent future growth opportunity 90 Campaign Ideas Generated© 2011 Accenture. All rights reserved. 13
  • 14. Campaign targeting through analytics Propensity Model Top 2 Deciles of Customers – 203K Active policy holders – 144K Age Profiling Cut (30 -60 yrs)– 108K Has Phone– 74 KIncreased targeting by Afterapplying filters based on Supp. 28Kinsights from profiling ofresponders 14
  • 15. Campaign results - significant uplift over BAU selection CAMPAIGNS LIFT OVER RANDOM ANNUITY CROSS_SELL 2.59 PROTECT CROSS_SELL 1.57 EQUITY RELEASE CROSS_SELL 1.36 MOTOR TO LIFE 1.5 HOME TO LIFE 3.8 IPP RESTART 0.9 (negative performance) Annuity Pensions base 7.1 Annuity Non Pensions base 3.6 15
  • 16. From tactical to strategic 16
  • 17. Strategic Analysis: IFA (Financial advisor Base) 1 PROJECT APPROACH PARTNER WITH IFA TO CROSS- SELL HIGH Track IFA VALUE PRODUCTS Performance PARTNER WITH IFA TO CROSS- SELL STRATEGIC PRODUCT LINES IFA IS NOT OPERATING IN 4 2 Data driven RE-TIERING Execute insights agreed 3 delivered to BRING IN-HOUSE DM OPERATION / actions IFA’s RESPONSIBILITY FOR NON-STRATEGIC IFA’s Plan and prioritise actions on IFA Base© 2011 Accenture. All rights reserved. 17
  • 18. Strategic Analysis - churn segmentation • Cluster analysis of inactive accounts to identify the types of customer attitudes and behaviour toward Joint holders : 10% churn. Active products and joint policy • Overlaid sample of bond surrender customer feedback holder group to validate Loyal customers : 17% Middle age group, matured policies, high tenure group, pension and annuity base, mostly IFA customers Protection seekers : 19% Young customers, protection focused group Golden geese: 19% Older customer, high value and high ticket policy holder with bond surrender Movers & Changers: 35% Older customer, voluntary inactive group, low value, joint policyholders, pension customers© 2011 Accenture. All rights reserved. 18
  • 19. Benefits & Reflections 19
  • 20. Benefits delivered 1. Incremental sales • Uplift of 2.84 in sales conversion achieved against conversion & revenues BAU customer selections. • £XXmillion incremental value delivered through ECM campaigns 2011 •200k customers added to multiple Life policy holders in 18 months: 23% vs 20.5% (adding in GI policies 34% vs 26%) • 25+ insight driven campaign waves executed 2. Campaign Management & Process • First cross BU campaign by customer management team • Campaign timelines reduced by 50% • 100% increase in marketable base by challenging existing suppressions and data management routines 3. Analytics & Strategy • Proved tactical and strategic value of analytics • Insight generation and dissemination has led to snowball of new insight requests© 2011 Accenture. All rights reserved. • 20
  • 21. Reflections from Aviva• We developed analytics too early – the marketing infrastructure wasn’t ready• The business wasn’t bought in enough – limiting the effectiveness of some campaigns• We can use analytics as a tradeable currency – why aren’t we doing more?• Is there more we can use CIC for... Predictive underwriting...?• We still haven’t developed processes to deploy the analytics in anger – but we are near• The value added from Accenture was outstanding – far more that their remit…….. 21
  • 22. Aviva’s Accenture Legacy• We have proven the case for analytics in UK Life• We have reduced campaign speed to market substantially• We have a usable single customer view… after 6 years of trying• We have sold the benefits of analytics to the wider UK regionBut essentially……• We have a platform for significant value growth over three years 22
  • 23. Questions? 23