Increase Customer Engagement with PersonalizationNGDATA Demo Webinar – July 16th 2014

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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?

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Connecting with the Customer

Preferences

Affinities

Context

Behavior

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I have a customer - what are the top 3 products he is likely to buy?

Answering the Tough Questions…

Which top hundred customers are likely to buy my product X today?

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

How can I turn around my most valuable potential churners?

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Challenges in Becoming Customer-centric

Overcome “Analysis Paralysis”

Proactively Engage with Customers

Cope with plethora of

data

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Becoming Customer-centric with Customer DNA

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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

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Customer DNA is based on Interaction dataand factual data (customer facts, contract info …)

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Lily Enterprise

See everything together – comparisons with a Set defined by you, and evolving trend scores for each customer

From Data to DNA – 1000s of metrics determine individual DNA

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Lily Enterprise

Dynamically created Sets defined by your own rules

More effective Alerts based on real-time customer metricsModels available, or

easily and dynamically add new models from all available metrics

Manage Big Data - Breaking down data silos to gain insights on all customer interactions in one place

With Lily’s Customer DNA and Machine Learning Engine, individual product Preferences are available each moment

Demo

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Lily Enterprise 3.0

Time to Value

▪ Understanding a complete picture of your customers in 6 months− What they are about | How to engage them

Impact and Results

▪ Creating a data-aware organization− “Transactionable” | Bringing analytics to the end-user | Delivering results

Functions

▪ Building Metrics, Affinities, Preferences in real-time, with continuous Machine Learning

▪ Integrates with enterprise architecture (CRM, CMS, BI,...), also allowing triggers and alerts

▪ Adding data sources, dynamically, as available

Bringing a New, Greater Value to Customer Experience Management

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InteractionManager

Big Data Repository

Catalog Manager

Listen

Execute

Learn

TargetingEngine

Open APIConnectors

Calculation Engine

Machine Learning

ListenConnects

CustomerPreferences

Customer DNA

Lily Enterprise

Real-Time Processing

Architecture

Lily’s key components &

related modules

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Learn

Execute

ListenInteractionManager

Big Data Repository

Catalog Manager

Listen

Execute

Learn

TargetingEngine

Open APIConnectors

Calculation Engine

Machine Learning

ListenConnects

CustomerPreferences

Customer DNA

Technology Foundations

Hadoop eco-system components

Metastore

ZooKeeper

Flume

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Lily

Operational Systems

Lily Enterprise 3.0Bringing a New, Greater Value to Customer Experience Management

External Data

Contract Data

Product Data

Reference Data

Reporting / Analytics

Enterprise BI and reporting

CRM and Call Center

IVR and Calls

Enterprise Analytics Applications

Marketing Data

Interaction Data

Campaign Data

CRM

Social Data

Customer Web and Mobile

Mobile Web and Apps

Customer Website & Apps

User and Brand Follow Up

CRM Data

Data Warehouse Data Outbound Marketing

Campaign Management

Real Time Integration

Data integration

BatchIntegration

ETL or

Lily APIbased

Lily Connector Based

Feedback

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

• Personalization• Offer recommendations based on individual preferences• Customer Service assistance• Manage risk, fraud prevention, Reduce customer churn

• Personalization, Customer Services• Better targeting, micro campaigns, social leaders• Reduce customer churn, price sensitivity• Media and IPTV, audience measurement

• Personalization, Cross sell/upsell• Recommendations – ads, content, etc.• Audience measurement• Customer Services

Banks

Telecoms

Media and Publishers

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Website Real Time Offer Personalization

?

?

?

Determine offer eligibility from:• Joe’s product preferences• Joe’s DNA (Interests, lifecycle, activity,...)

Calls to Lilly with content:• Customer info.• Context info.• Session data

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?

?

?

Website Real Time Offer Personalization

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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

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