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Go Beyond Pretty Graphs – Gaining Actionable Customer Insights from Your Bank’s Big Data NGDATA Webinar – October 22 nd 2014 Steven Noels CTO, NGDATA

Go Beyond Pretty Graphs

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Discover the importance of moving from data visualization to more actionable insights that can help you engage your customers in new ways and offer more compelling products and services in order to strengthen your relationship with your customers.

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Page 1: Go Beyond Pretty Graphs

Go Beyond Pretty Graphs –Gaining Actionable Customer Insights from Your Bank’s Big DataNGDATA Webinar – October 22nd 2014

Steven NoelsCTO, NGDATA

Page 2: Go Beyond Pretty Graphs

2Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission

Key Takeaways

▪Steps to successfully gain actionable insights from your Big Data 

▪How to apply Customer DNA to better engage your customers and increase their value

▪Case studies of top banks that are increasing their customer satisfaction by using actionable, real-time insights

Page 3: Go Beyond Pretty Graphs

3Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission

With so much data available, analysis is often time-consuming—making it hard to be agile, let alone proactive.

Page 4: Go Beyond Pretty Graphs

4Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission

Customer Experience Customer spamming is doing more damage than good

Company& Customer

Activity

CustomerCRM

Systems

CustomerWeb & Mobile

Customer Channel Campaigns

CustomerService Desk

Social Data

Website &online apps

Mobile App Server

Mail

SMS

Print

Broadcast

Offers

direct mail

ATM

web

Agent, IVR

email

mobile

chat

Relevance?Awareness?

Value?Timing?Clarity?

Page 5: Go Beyond Pretty Graphs

5Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission

Main Challenges to Customer Centricity

MultipleCustomerDefinitions

No central view of the customer

Lack of relevant messaging to customers which can lead to low engagement

MarketingPressure

Large organizations are marketing to the same database in different ways and times

Inconsistent cadence and messaging damages trust and credibility

Over-marketing to customers can lead to decreased engagement and increased churn

Too manydashboards – little insights

Batched analysis can lead to missed opportunities to present offers and messaging in a timely manner.

Missed opportunity to impact loyalty and lowers ROI.

Page 6: Go Beyond Pretty Graphs

6Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission

Not Just Big Data Graphs…

Enterprises are NOT looking for new presentations of their data anymore, but for RESULTS and for solutions and people to achieve them

Page 7: Go Beyond Pretty Graphs

7Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission

Which additional offers can I recommend to a customer based on their recent behavior and spending or savings habits?

Answering the Tough Questions…

Which of my most valuable customers is most likely to churn away? And provide me with enough advance notice to go & fix this!

What is the best channel to connect with my customer, and when?

What products can I cross- or up-sell to gain a more solid, long lasting customer relationship, for greater engagement and value?

Page 8: Go Beyond Pretty Graphs

8Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission

Google NowThe Leading Example

real-time

context-aware

hyper-personal

connect the dots

Page 9: Go Beyond Pretty Graphs

9Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission

Get to Know Your Customers

Preferences

Affinities

Context

Behavior

CUSTOMER DNA

Page 10: Go Beyond Pretty Graphs

10Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission

What is Customer DNA?

▪ an organized collection of 1000s of predefined descriptive metrics

▪ calculated in real time

▪ by a configuration-based calculation engine

▪ organized per identified customer

▪ based on a variety of data sources, both interaction- and fact-based

▪ using a variety of predefined calculation, prediction or retrieval methods

▪ providing actionable data for marketing & customer-centric applications

Page 11: Go Beyond Pretty Graphs

11Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission

Customer DNA is Based on Interaction Dataand factual data (customer facts, contract info …)

Page 12: Go Beyond Pretty Graphs

12Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission

Customer DNA

www

STB

Mobile

Network

App Phone

Call Centre

CDR

Shop

POS

Personalization

Acquisition

Journey

ARPU / CLTV

Marketing

Advertising

Churn

Fraud

www

STB

Mobile

Network

App Phone

Call Centre

Shop

POS

CDR

Personalization

Acquisition

Journey

ARPU / CLTV

Marketing

Advertising

Churn

Fraud

Towards a New Architecture

Page 13: Go Beyond Pretty Graphs

13Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission

Customer DNA Enables You To…

Overcome “Analysis Paralysis”

Proactively Engage with Customers

Cope with plethora of data

Page 14: Go Beyond Pretty Graphs

14Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission

Customer DNA Enables You To…

Analysis

Action ability3 V’s

Page 15: Go Beyond Pretty Graphs

15Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission

Apply Data-Driven Applications

Data-driven applications act on any volume of real-time data to actively guide and optimize business processes based on continuously growing insights on customer behavior, intent and preferences.

Page 16: Go Beyond Pretty Graphs

16Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission

Applied to Subscription-based BusinessesCustomer Lifetime Value (Inbound, Outbound, Risk)

Banking

• Value-add Services such as Merchant-funded Coupons

• Customer Experience− Personalized service & products− Financial Advise

• Risk Assessment

• Marketing Targeting Efficiency

Page 17: Go Beyond Pretty Graphs

Use Cases for Finance

Page 18: Go Beyond Pretty Graphs

18Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission

Listen: 1-2-1 Marketing and Micro Campaigns

Individual Product and Content Preferences –

Marketing campaigns with higher Frequency (> x10), higher Response rate (x4) and reduced Budget (< ½)

Result

• Improve ROI (conversion ratio) of Marketing Campaigns by targeting individual customers, or Sets of customers based on preferences

Objectives

• Real-time ingest of multiple data feeds• DNA with focus on current accounts, activities,

context based interactions and product preferences• Learned preferences to feed event-based marketing

actions & connect customers to preferred products• Moving from product centric to customer centric

marketing

Solution

Retrofit Cus

tomer

Product Teams

Branch

Product-Centric Customer-Centric

journeys

contactcenter

mobile

web

self-Service

socialmedia

branchweb

social

ATM

telesales Product & Channel Wrapper

Page 19: Go Beyond Pretty Graphs

19Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission

Learn: Improve Customer Service for Increased CLTVLarge US Wealth Management Bank

Real Time Actionable Customer DNA –

Allows agents to provide better and more efficient advice. Building increased customer loyalty

Result

• Improve financial advice suggesting the right investment at the right time to the right customer

Objectives

• Real time ingest of the investment history, behavioral metrics, etc., of the customer

• Monitor all interactions (payments, CC, calls, IVR, mobile and online…) to develop a Customer DNA

• Continuously learn and enhance the Customer DNA, with a focus on offering potential new investments in line with the individual profile

Solution

Page 20: Go Beyond Pretty Graphs

20Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission

Execute: Merchant-funded Mobile OffersFortune 50 US Retail Bank

Mobile Information Mobile Wallet Mobile Redemption

• Leverage multiple sources of data to improve coupon redemption rate through real-time, location-based personalized offers

Objectives

• Real-time ingest of payment transactions• Behavior-based MCC preference learning• Location- and preferences-based coupon selection &

delivery in mobile wallet• Evaluate performance between collaborative

filtering & KB-based preference learning

Solution

Individual Coupon delivery –

Average targeting precision increased by 5-7x, results in increased redemptions and loyalty

Result

Page 21: Go Beyond Pretty Graphs

21Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission

Experience the Difference with Lily

Listen Bigger.

VO

LU

ME

Learn Faster.

SP

EED

Execute Smarter.

AN

SW

ER

S

Volumes of Data

Availability

Questions Answered

Start working with Lily to discover results from Day 1

Zettabytes

Exabytes

Petabytes

Terabytes

Gigabytes

Seconds

Minutes

Hours

Days

Weeks

Unknown Unknowns

Known Unknowns

Known Knowns

DW/BIDW/BIDW/BI

Page 22: Go Beyond Pretty Graphs

22Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission

Page 23: Go Beyond Pretty Graphs

Thank [email protected]