Improving customer service with data 19 may 2015 Maarten Jonker Leiden

(1)

Improving customer service with data

(2)

Increasing our understanding of data and using knowledge

We are increasing our understanding of data

(including big data) and using the knowledge

gained to improve customer service

Opportunity

 In the digital world, customers have enormous freedom of choice

 Customers expect relevant, personalised communications wherever and whenever convenient, and on any device

 Technology makes this possible

Achmea

 Digital-first principles form the guidelines for customer service and the use of technology

 We use our data (including NPS) to improve customer service

 This is why we are expanding our understanding of data in general and big data in particular

Achmea’s digital-first principles

Customer journeys

(4)

The way we work:

Five Digital First Principles

Our customers:

 see the real-time consequences of their actions

 receive services entirely online, although offline services remain available

 are provided with relevant, personal, specific information

 are linked to other customers through online communities

 are always alerted to possibilities for digital interaction

(5)

Digitalisation at the heart of business innovation

Digitalisation is based on four driving factors.

Security is an important prerequisite.

 Omni –24/7, everywhere, all services and on all devices

 Data – 90% of data worldwide was created in the last two years. Structured and unstructured data provide new

possibilities for understanding our clients, creating new insights and creating innovations

 Networks – Traditional value chains are changing to open eco systems. Achmea is applying partitioning, and clients count on Achmea when it comes to the security and

reliability of data and processes

 Cloud – New, constantly evolving, easily scalable technologies. This driving factor is behind the high level of standardisation and the use of

globally accepted protocols

Driving factors

Digital customer Cloud Mobile Networks Data

(6)

Exponential growth of data used to improve service for customers

General findings

 All things are connected nowadays

 The constant growth in digital devices and people using them has led to the exponential growth of data (volume), more variety in data, such as text and images, and greater data velocity due to streaming data devices

 New developments include sensor data, social data and web behaviour

Achmea

 The growth of data gives Achmea the opportunity to understand the needs of customers better and offer them better products and services

 The customer decides what kind of data he or she wishes to share

(7)

Our motives. Big Data analysis support by actionable insights

Higher conversion rate /

lower churn rates

Improve customer satisfaction and loyalty

Enhance propositions and create new added value

Lower operational costs due to self-service

Cross-sell and have more relevant contact

with customers Improve services for customers Create community value by win-win Achieve cost savings to operate at competitive price levels

(9)

Our roadmap: marketing & distribution

Proposition Marketing & Distribution ICT and Back-office Claims

(10)

Our roadmap: marketing & distribution

Proposition Marketing & Distribution ICT and Back-office Claims Digital Acceleration Digital Innovation

 Use of digital footprints

of processes

 Omni-channel

 Use of social media

 Real-time marketing

 360° view of customer

 Low level segmentation,

personalised and more relevant

 Text mining and

(11)

Our roadmap: proposition

 Online real-time use of analytics  Dynamic content – increasing relevance of digital contact  Customer engagement,

value and pricing

 Use of data and IoT

 Usage based insurance

(12)

Our roadmap: claims

 Fraud detection

 Call and claim routing

 Connected world – car, home data used

for prevention and improved servicing

 Predictive modelling for advising and claim handling

(13)

Our roadmap: ICT and Back-office

 Reduction of data redundancy, improvement of data quality

 Agile analytics capabilities

 Lower IT costs due to standardisation and continuously

declining cost of storage and CPU power

 Digital 3rd party integration

 Digital/cyber security and privacy

 Dynamic plug & play sourcing

(14)

Big data programme starting to make an impact at Achmea

Impact is preceded by insight and innovation

 Insights must by actionable and make an impact

 Innovation will make an impact in future, one year ahead and further on

People, process, data and technology

 People: community data analysts and cooperation with universities

 Process: agile, reusable approach resulting in actionable analytics; strict data governance processes for

accessing and using data

 Data: creation of uniform data platform for structured and unstructured data

 Technology: standardisation of IT tooling and challenging new technical innovations

Insights Impact Innovation

People Proces Data Technology

Marketing

Intel. Cockpit CEV in action

Academy, big data pilot projects

(15)

Unlocking data from different disciplines is key in making an impact;

limits exist, however

Privacy and data governance

 All data is secure and access is controlled

 Coordination of definitions and usage of common or corporate data

 Compliance with legislation; reputational risks

 No commercial use of data outside Achmea

 For research purposes, data is always made anonymous

Shared interest

 Recruitment and training programmes

 Governance, policies, IT infrastructure

 Exchange of knowledge, best practices

Generic Object Layer

Health Non-life Life & pensions

Co mm er cial Fi n an cial He alt h Non -lif e Lif e IT s ys tems HR O p er ational …

(16)

Our pathway to big insights and big impact

 Data governance in place

 General IT environment defined

and migrations started

 Technical pilot projects

 Digital capability, education,

collaboration

 Standardisation and rationalisation

of corporate data items

 Life-cycle management

infrastructure and software

 Migration of all BI environments

to strategic platforms

 Technical and business pilot projects

 Digital capability: recruitment

of data analysts, collaboration with universities

 Effective response to triggers in

customer journeys. Lower churn, higher conversion rates

 Campaign and pricing based on

customer engagement value

 Lowering of claims ratio due to

insight into variation handling, fraud analysis and prevention

 Fact-based and direct / daily

operational performance management (lean)

 Agility and higher productivity,

resulting in new insights and analytical models

 New service propositions

based on data

2013-2014 - Basic analytics

2015 - BIG Data

(17)

Achmea uses big data to enhance both commercial and underwriting performance

Pricing desk

Pricing based on data analysis using analytical tools is

now used in the consumer non-life business (CBA and FTBO)

Customer value model

Optimisation of commercial success based on customer behaviour and loyalty

Geodata

Application of insights based on analysis of geographical data in claims processing and in the sales process

Text mining and speech analysis

A proof-of-concept project conducted by a multidisciplinary team should soon produce useful results in the area of text mining and speech analysis

(19)

Geoanalysis enables creation of new propositions

Aerial and side elevation photos

 Detailed analyses. Every year tens of thousands of

inspections are performed from workstations and fraud is detected by means of built-in timeline analyses

Geographic analyses

 Visualisation based on postcode, socio-demographic level, etc. GIS applications

 “Geo view of the customer”

Geospatial analytics

 Calculations based on the geographical position or distance from high-risk objects (gas pipeline, high voltage network, etc.)

Distance from repair shop as input for analysis

Repair shops

Clients

(20)

Text data are an additional source of information

Various uses

 To be used for incoming mails (call centres) for subject recognition and for tagging messages

 To help spot trends and frequently asked questions

(21)

Visualisation and analysis of processes

Based on timeline

 Transactions are visualised in a timeline of activities

 Lean principles, such as getting it right first time, avoiding irrelevant steps and reducing waste, are more easily identified

 Data is collected directly from systems (e.g. by means of log files)

Usage

 All processes with multiple touch points, with the aim of improving the quality of service and lowering handling time and costs

(22)

Data analysis (data mining) provides new insights

Supported by the growth of available data, computing power and advanced techniques for modelling and visualisation

Usage

 Predictive models of workforce planning

 Pricing and customer segmentation models

 Probability model for possible cases of fraud

(23)

Big data is a prerequisit for many financial and qualitative objectives

Name Qualitative Estimated financial impact

Rationalisation of BI application landscape Improved data quality, compliance with rules and regulations, data governance and accelerating time to market

IT cost saving of more than 15% for BI

Concluding insurance – becoming a customer: models focused on earlier detection of triggers in customer journey and effectiveness of using affiliates

Focus on churn, NPS and conversion rate and costs of online marketing budget (affiliates)

Significant increase in customer engagement value, and pricing as percentage of premium

Being a customer: good view of the customer and analyses provide input for personalised service and customer dialogue – also focused on credit management process

NPS, reducing claim settlement costs and reducing receivables

Fall in operating cost and in level of outstanding receivables

Usage: for fraud prevention, non-life procurement and

management of repair services based on advanced data analyses

Reducing fraud also enhances reputation and compliance

Decrease in number of claims or amount per claim

There are millions of customer contact moments in the customer journey. In the migration to digital customer services, a great deal of analysis has focused on the customer journey and the volume and quality of customer contact moments online, through calls,

by e-mail and by post

Optimisation of NPS, guiding change to digital, removal of ‘unnecessary’ customer contact moments through calls and other channels

> 10% ‘waste’ calls identified and to be avoided

Lean-based performance improvements, supported and accelerated by digital footprint in systems and big data visualisations

Improved insight into process of drilling down to root causes; more things right first time, handling time, lapses

(24)

Conclusions.

 The constant growth in digital devices and their use has led to the exponential growth in data

 The growth in data gives Achmea the opportunity to understand the needs of customers better and offer them better products and services

 Achmea has defined the roadmap to be implemented. Governance, IT infrastructure and data provisioning are centralised for compliance reasons, supporting re-use across divisions and cost-effective investments

 Impact follows insights and innovations. Many examples of this are already in place at Achmea. Impact is the starting point for pricing and customer value, fraud analysis and lean-driven efficiency improvements. We use our data (including NPS) to improve customer service

 This is why we are expanding our understanding of data in general and big data in particular

Thank you for your attention

(25)

Improving customer service with data 19 may 2015 Maarten Jonker Leiden

Full text