big data and customer analytics examples

© 2012 IBM Corporation

Big Data & Big Data AnalyticsExperiences in building a 360°Integrated Customer View

Pietro LeoExecutive ArchitectMember of IBM Academy of Technology Leadership Team

@pieroleo www.linkedin.com/in/pieroleo

http://www.linkedin.com/in/pieroleo

© 2012 IBM Corporation@pieroleo www.linkedin.com/in/pieroleo

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IBM Institute for Business Value

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Financial constraints

Decreasing brand loyalty

Growth market opportunities

ROI accountability

Customer collaboration and influence

Privacy considerations

Global outsourcing

Regulatory considerations

Corporate transparency

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Data explosion1

Social media2

Growth of channel and device choices3

Shifting consumer demographics4

Mean

Marketing Priority Matrix

Factors impacting marketingPercent of CMOs selecting as “Top five factors”

UnderpreparednessPercent of CMOs reporting underpreparedness

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1011

Mean

What are the main Factors impacting marketing & CMO?

IBM

Big Data related dimensions!



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A new paradigm targeting a 360°Integrated Customer View in order to leverage the Customer Empowerment


The new profession paints a predictive picture of each customer by harnessing data on a massive scale

• Instruments all key touch points to gather the right data about each customer.

• Connects social media data, transaction data and other information to paint a more vivid picture of each customer.

• Runs the right analytics at the right time on the right customer to generate new ideas about whom to serve and how best to serve that person.

• Generates insights that are predictive, not just historical.

• Builds capabilities to do this on a massive scale.



Branch office

Web

IVRCall Center

Enterpriseproducts

and services

Unstructured Call logs, Transcripts

Emails, Surveys

Self Service

Agent

StructuredCustomer/Product Transaction Data

StructuredAgent Data

Customer Intelligence Process Understanding

Dissatisfaction Drivers Sales Drivers

Agent Performance Social Drivers

Enterprise Contact Points Customer

Data & Content

Big Data BusinessAnalytics

Insights Distribution & Utilization

Integrate and Analyze Structured and Unstructured Data

How Big Data Analytics can help? Create an integrated view of Customers Data & Content from ALL enterprise contact points including internal and external sources... social business!

Social



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A new paradigm targeting a 360°Integrated Customer View in order to leverage the Customer Empowerment


Ex1. Collect customers longitudinal point of viewsAnd correlete them with

internal data

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6 Nov 14, 2012

Business challenge

Social media is considered a new and relevant source to understand the consumer and improve service levels; measure its own as well as the competition’s brands and products; and compare results with traditional TV research data for better market awareness. Particularly, the company needed a social media analytics solution that could: accurately measure the echo on Social Media about the efficacy of its products and campaigns; provide insight into competitors;

Solution

IBM helped the client to analyze unstructured data across a number of social media channels and assess the company’s corporate brands, with respect to its competitors, as well as to discover and statistical measure signals and alerts about viewer preferences and experiences about TV contents. Specifically, among others, included:

detect hot words and design attitudinal indicators about company products and services

discover new trends and hot words on Social Media in order to compare them and weight them with respect to internal information streams

analyze findings and evaluate their significance with respect to business priorities

correlate customer attitudinal attributes results of unstructured data analysis with internal data

Benefits

• Measure as well as discover a number of signals referred to TV viewers that were expressed in web 2.0 comments and referred to several kind of TV contents and TV ads campaigns.

• A number of interesting correlations were discovered and evaluated among those signals and with respect to internal customer loyalty parameters that will contribute refine the company marketing strategy.

“Big Data is a great opportunity for TV innovation in the next years. TV viewing is transforming into a multiplatform and participative experience: the better we know and understand our viewers, the better we can serve them." – Valerio Motti, Head of Marketing Innovation, Mediaset S.p.A.

Example 1: Big Data Analytics to collect Customer longitudinal point of views from Web 2.0 and correlate them with internal data


© 2012 IBM Corporation7@pieroleo www.linkedin.com/in/pieroleo

RSS

Social Intelligence Workplace

Example 1: Big Data Analytics to collect Customer longitudinal point of views from Web 2.0 and correlate them with internal data

Working Environment OUTPUT

STRONG SIGNALS

WEAK SIGNALS

Content Provider / Aggregators

SorgentiFeedRSS

Regular Reporting & Monitoring

Specialized Analysis & Studies

Information Sources

Model taxonomyHotwords Taxonomy

REPORTING

ADVANCED SEARCH:

TAXONOMIES RELTATIONS

SENTIMENT

CONCEPT DISCOVERY

DISCOVERY and ANLYSYS OF INFLUENCERS

ALERTS



360-degree Consumer Profiles from Social Media

Personal Attributes• Identifiers: name, address, age, gender, occupation…• Interests: sports, pets, cuisine…• Life Cycle Status: marital, parental

Personal Attributes• Identifiers: name, address, age, gender, occupation…• Interests: sports, pets, cuisine…• Life Cycle Status: marital, parental

Products Interests • Personal preferences of products• Product Purchase history• Suggestions on products & services

Products Interests • Personal preferences of products• Product Purchase history• Suggestions on products & services

Life Events• Life-changing events: relocation, having a baby, getting married, getting divorced, buying a house…

Life Events• Life-changing events: relocation, having a baby, getting married, getting divorced, buying a house…

Monetizable intent to buy products Life Events

Location announcementsIntent to buy a house

I'm thinking about buying a home in Buckingham Estates per a recommendation. Anyone have advice on that area? #atx #austinrealestate #austin

I'm thinking about buying a home in Buckingham Estates per a recommendation. Anyone have advice on that area? #atx #austinrealestate #austin

Looks like we'll be moving to New Orleans sooner than I thought.Looks like we'll be moving to New Orleans sooner than I thought.

College: Off to Stanford for my MBA! Bbye chicago!College: Off to Stanford for my MBA! Bbye chicago!

I'm at Starbucks Parque Tezontle http://4sq.com/fYReSjI'm at Starbucks Parque Tezontle http://4sq.com/fYReSj

I need a new digital camera for my food pictures, any recommendations around 300?

I need a new digital camera for my food pictures, any recommendations around 300?

What should I buy?? A mini laptop with Windows 7 OR a Apple MacBook!??!

What should I buy?? A mini laptop with Windows 7 OR a Apple MacBook!??!

Timely Insights• Intent to buy various products • Current Location• Sentiment on products, services, campaigns• Incidents damaging reputation• Customer satisfaction/attrition

Timely Insights• Intent to buy various products • Current Location• Sentiment on products, services, campaigns• Incidents damaging reputation• Customer satisfaction/attrition

Relationships• Personal relationships: family, friends and roommates…• Business relationships: co-workers and work/interest network…

Relationships• Personal relationships: family, friends and roommates…• Business relationships: co-workers and work/interest network…



Example 2: Big Data Analytics to expand knowledge about customer profiles and measuring marketing campaign

• Analysis of social media messages for large Media and Entertainment company to determine reaction to movie commercials aired during the SuperBowl

• Insights based on 30M+ social media consumer profiles created by analyzing over a Billion messages• Real-time evolution of insights correlated with the airing of the commercial

• Analysis of social media messages for large Media and Entertainment company to determine reaction to movie commercials aired during the SuperBowl

• Insights based on 30M+ social media consumer profiles created by analyzing over a Billion messages• Real-time evolution of insights correlated with the airing of the commercial

Key Business Questions:

How many people are talking about the film ?• Intention to see the movie, Impact of SuperBowl commercial

Who are they ?• Demographics, Influencers, avid movie goers

What is the reaction ?• Categorized sentiment (plot, characters, …)• Comparison with competitive movies

Key Business Questions:

How many people are talking about the film ?• Intention to see the movie, Impact of SuperBowl commercial

Who are they ?• Demographics, Influencers, avid movie goers

What is the reaction ?• Categorized sentiment (plot, characters, …)• Comparison with competitive movies

Buzz Amongst Avid Movie-Goers Jan - Feb

The Lorax

Project X

John Carter

The Dictator

The Dark Knight Rises

Battleship

Spider-man

G.I. JoeGhost Rider

The Avengers

Act of Valor

Think Like a Man

21 Jump Street

Buzz Amongst Avid Movie-Goers During Super Bowl

Project X

John Carter

Battleship

Ghost Rider

21 Jump Street

The Dark Knight Rises

G.I. Joe

Spider-manThe Avengers

Act of Valor

The Lorax The Dictator

10% 20% 30% 40% 50% 60% 70% 80% 90%

Battleship

The Dictator

Gender

Top 10 Markets

Gender

Top 10 Markets

Female Male

Female Male

Gender

Top 10 Markets

Female Male

Act of Valor

Competitive IntelligenceCompetitive Intelligence

Consumer demographics by movieConsumer demographics by movie

Comparing feedback by important microsegment (avid movie-goers)

Comparing feedback by important microsegment (avid movie-goers)



Social MediaConsumer Profiles

Social MediaConsumer Profiles

CustomerModels

CustomerModels

InfoSphere Streams

InfoSphere BigInsights

Entity Integration

Entity Integration

Predictive Analytics

Predictive Analytics

Data Ingest & prep.

Data Ingest & prep.

Text Analytics: Timely InsightsText Analytics: Timely Insights

Entity Integration:

Profile Resolution

Entity Integration:

Profile Resolution

Predictive Analytics:

Action Determination

Predictive Analytics:

Action Determination

Social Media Data

Social Media Data

IBM SDA: Social-media Based Micro-segmentation and Real-time Correlation

Online Flow: Data-in-motion analysis

Text Analytics

Text Analytics

Offline Flow: Data-at-rest analysis

Timely

Decisions

Large-scale data-at-rest analysis using InfoSphere BigInsights Large-scale data-in-motion analysis using InfoSphere Streams Advanced text analysis, entity integration, and predictive modeling using common analytics

infrastructure across Streams and BigInsights

Large-scale data-at-rest analysis using InfoSphere BigInsights Large-scale data-in-motion analysis using InfoSphere Streams Advanced text analysis, entity integration, and predictive modeling using common analytics

infrastructure across Streams and BigInsights

Social Media Data

CustomerDatabase

CustomerDatabase

ConsumerLists

ConsumerLists

Customer & Prospect

profiles

Customer & Prospect

profiles

EntityIntegration

EntityIntegration


© 2012 IBM Corporation12 @pieroleo www.linkedin.com/in/pieroleo

Business Models based on connecting Virtual and Real Words: the AMEX model

American ExpressSmart Offer

A portal that collects special offers and discounts from

retailers and detail about the customer segment that is target

Marketing segmentation engine that evaluate customer profiles and select the best coupon to

propose

Moble app and connection with Twitter, Facebook e

Foursquare to communicate with the customers and enable

viral effects

Just virtual Coupons are managed! Customers activate the coupon and receive on montly basis on the credit card account the equivalent of the coupon discounts after that transactions were registred



Grazie!

Pietro LeoExecutive Architect

Member of IBM Academy of Technology

@pieroleo www.linkedin.com/in/pieroleo@pieroleo www.linkedin.com/in/pieroleo

@pieroleo www.linkedin.com/in/pieroleo



