Customer DNA Defined

Customer DNA DefinedBuilding Greater Customer Experiences

March 18th 2015

Steven Noels

CTO, NGDATA

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

Customer Experience Above All Else

42.2%Customer Service

24.3%Bank Location

22.0%Efficient Online

Services

11.5%Financial Rates/Loans

Which quality is most important to consumers when selecting a bank?

Customer Service is Valued Even More Than Financial Rates/Loans


Do You Understand Your Customers?

Only 20%

are very confident their bank understands them


Give Your Customers What They Want…

▪ Exceptional customer experiences

▪ Relevant offers and consistent messaging

▪ High quality customer service

▪ Personalized omni-channel experience

▪ Needs anticipated and exceeded

− Google, Facebook etc…


Make an Impact

▪ Operational efficiency

▪ Establishing effective data

governance

▪ Accurate information on customers

to align internal messaging

▪ Marketing team is less dependent

on data scientists

▪ Decrease errors and increase

marketing effectiveness

▪ Effective inbound and outbound campaigns

How?


How can I leverage all customer data and easily market to my customers at the individual level?

By Answering the Tough Questions…

How can I quickly address the right customers with the right product offers?

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

What is the best, tailored omni-channel experience for my customers?


Challenges with the Classic Approach

Data silos > no complete view of the customer

Inefficient allocation of resources

Inaccuracy of traditional segmentation

Lack of data actionability


Take Your Data to the Next Level

DATAGOVERNANCE

DATAAVAILABILITY

DATAACTIONABILITY


Data Governance

DATAGOVERNANCE Improve traceability and accountability

Centralize efforts for all departments

Create multi-department agreement over keycustomer metrics


Data Availability

Clear, prescriptive metrics supporting

modeling of customer profiling actions

Fresh, actual data, always up-to-date

Valuable data becomes an asset

DATAAVAILABILITY

Reuse data consolidation efforts


Data Actionability

DATAACTIONABILITY Customer behavior events triggering actions

Real-time is important for context awareness

Trend more important than value


What is Customer DNA?

▪ A standard centrally-managed customer-centric approach providing 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


What is Customer DNA?

▪ Uniquely identifies customers by dynamically matching different source IDs

(twitter handles, different email addresses, etc.) from different touch points to

a single customer

▪ Provides in-depth DNA insights by breaking DNA on dimensions such as

brand, product category, channel, device, location, etc

▪ Shows how the customer’s DNA evolves by providing a timeline view, a

changelog view and a DNA trend and acceleration.

▪ Dynamically organizes customers in Sets and calculates Set DNA


Customer DNAExtensibility model

Lily CommonCustomer DNA

data sources

Custom metricse.g. analytical view

Lily Data Model

OtherCustomer Non-DNA entities Interaction

customers, products, subscriptions, contracts, transactions, interactions, market & social data

Industry DNAExtensions

variable calculation engine

map / load / transform: interactions with context & customer source records

ModelBasedDNA


Common DNA CategoriesWith a Marketing mindset

Socio-demo

Life Time Events

Connections

Value

Status

Product

Usage

Relationship

Impressions

CommunicationPreferences & History

Affinities

Affluence

Competition

Loyalty

Usage

• product usage frequency

• number of shared contact devices• tablet used• smartphone used• number of social devices used• mobile app downloaded/used• …

location, time of day, day of week, device


Different Types of Customer DNA Metrics

CONTRIBUTED OBSERVED

CALCULATED PREDICTED

Fields Aggregates

Formulas Scores

Facts

CRM

DWH

CustomMetrics

Behavior

Transactions

Clickstream

Models


Customer DNA in MediaLarge International Media Group – De Persgroep

Single Customer View –

Centralized, real time updated, and very detailed single customer view, driving personalized marketing and customer analytics.

Result

• A platform for actionable, omni-channel customer intelligence from Big Data

Objectives

• Collect CRM/DWH and clickstream data• Build Customer DNA with 1000s of metrics• Support operational & analytical reporting• Integrate with Campaign Management for offer

proposal and capture feedback• Learn affinities for automatic profiling

Solution

“ NGDATA is critical in the way we capture, analyze and generate actionable intelligence from Big Data. NGDATA makes it easier for us to connect with our customers across all of our channels, learn from their behavior and create personalized, unique offers to foster loyalty.”

—Luc Verbist, CIO, De Persgroep


Working with DNA for Marketing Execution

InboundOutbound

more relevant & precise target lists

MassMarketing

Individual

individual-level data-driven approach, alerts, using channel preferences, past purchase history

personalizationOnline

ServiceDesk

anticipation, guided conversation


Key Takeaways

▪ Customer and Company Challenges

▪ Customer DNA Definition

▪ Case Studies

− De Persgroep

− Inbound & Outbound Solutions

▪ Next steps


Are you ready to use Customer DNA to gain and keep your customers?Learn more about how Lily Enterprise can help your company. Schedule an appointment with an NGDATA representative to get a personalized walkthrough.

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Benefits of DNA Over a Customer Data Warehouse

▪ Built-in versioning: Factual data is now stored over time

− Where did the customer live at the time of the purchase?

▪ Process high-velocity unstructured information that cannot be stored in a

relational data warehouse.

▪ Temporal customer behavior summaries are much more flexible

− Average purchase amount per day automatically gives access to the same metric per week and

month

▪ Easily managed breaks allowing to drill down a customer’s DNA

− Average purchase amount per product category.

▪ Real-time and recursive calculation

− Formulas are calculated on the fly and recursively as their building blocks are versioned.