Analytical Revolution

The Analytical Revolution: Are You Ready?

Heena Jethwa Sr. Product Marketing Manager

© 2010 IBM Corporation

Business Analytics

Heena Jethwa Sr. Product Marketing Manager

Business Analytics

Commonly Asked Questions

�Can I get copies of these slides after the event?

� Is this event being recorded for later viewing?

Reap the Rewards: Create a Positive Customer Experience

© 2010 IBM Corporation© 2009 SPSS Inc.© 2009 SPSS Inc. 2

� Is this event being recorded for later viewing?

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Key Trends

• Research is becoming commoditized with clients less willing to pay for quality

• Clients are demanding shorter timelines for projects and faster delivery of findings


• Businesses are seeking added value from research –more strategic thinking and high-end analysis

• Fresh information, accurate measurement and true insight

willing to pay for quality

• Non-researcher management are conducting their own

surveys on the internet

Business Analytics

A time for change: Research Press

“What’s driving consumers and markets will breathe life into a new-look research business one that’s more tightly focused on delivering clear returns, actionable information, fresh ideas and a higher level of service” than before the crisis struck” ESOMAR Research 2009


ESOMAR Research 2009

“Painting the bigger picture and answering strategic questions is precisely what market researchers ought to be doing” Norio Taori, president of Japanese research firm INTA GE

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A Time for Change: Customer View

�“Today, more than ever, insight as well as foresight are essential to the success of our business.” Joan Lewis, SVP and head of consumer knowledge P&G

�“Customers are evolving – and so should


�“Customers are evolving – and so should marketing and research techniques.” Elisabetta Osta (CMO) Barclaycard

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The opportunity

“I hope we’ll see collaboration efforts between various sectors to tackle the tough work required to build an infrastructure that enables integration of data from all sources … that’s a huge opportunity”


opportunity”

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The Challenge

�Harnessing the wealth of data

�Tuning out noise from valuable insight

�Competition for insight

�Data access/silos


�Data access/silos

�Changing relationships and expectations

�Decisions and data at the right time

�Ensuring ROI and profitability

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Role of the MRI : Data Provider or Insight Partner?


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Traits of an Insight Partner

�Understand and report on what people, think and do

�Data and insight expertise

�Objectivity


�Objectivity

�Methodology

�Strong client relationship

�Deliver Insight and Foresight

�Aid strategic and holistic actions

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More data than we can imagine…

�1 billion transistors for every human

�10 billion devices connected to the internet

�100 Billion smart devices

�15 petabytes of new information everyday


�15 petabytes of new information everyday

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What is a Petabyte ?

�20 Million 4 drawer filling cabinets filled with text

�13.3 years of HDTV video


�13.3 years of HDTV video

�10 billion photos on facebook

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Attitudinal data- Opinions- Preferences- Needs & Desires

Interaction data- E-Mail - Call center notes - Web Click-streams- Blogs/ social networks

Leveraging all data


Behavioral data- Orders- Transactions- Payment history- Usage history

Descriptive data- Attributes- Characteristics- Self-declared info- (Geo)demographics

�Predictive Analytics .. For data (structured and unstructured)

How can you harness ALL this data and delivering Insight and Foresight


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unstructured)

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The Power of Predictive Analytics- Data Mining

There’s analytics…and analytics

�Typical analysis (reporting)

–Measure. Compare. Report. Study.

–“Rear-view mirror”

–Data cuts and crosstabs

�Predictive analytics


�Predictive analytics

–Algorithms automatically “learn” significant patterns

–Include all data types attitudinal, transactional, demographic and Interactive

–Models make predictions for current/new cases

–Insight delivered to drive better business decisions

Business Analytics

Data Mining – Fact or Fiction?

“Predictive Analytics doesn’t have a whole lot to do with Market Research”

“Predictive Analytics is really no different than BI… they’re both based on a look in the rear


BI… they’re both based on a look in the rear view mirror”

“Data mining would add little perceived value to MR customers… so why add another tool to the

toolbox”

Business Analytics

Data Mining –Dispelling Myths

� Predictive Analytics and Market Research– Add value at multiple stages of research – from respondent management, through

data processing, to innovative reporting that delivers deeper, more actionable insight

– Deliver Foresight and insight

� Predictive Analytics vs. Typical Reporting– Report on data up to the time it’s pulled


– Report on data up to the time it’s pulled

– Predictive Analytics uses an extensive pool of algorithms to predict what will happen next

– Let´s the data do the talking and exploring

� Creating Value & Differentiating with Predictive analytics– Customers increasingly want innovative approaches that help them understand

their business better and make more informed decisions

– Meeting this customer need makes the Market Researcher a more strategic business partner

Business Analytics

The Predictive Analytics Process

Predictive Analytics

Analyze data to

provide insight and

predict the future

Predict

THIS IS WHERE THE INSIGHT PARTNER REALLY IS NEEDED


Decision Optimization

People Data& Enterprise Data Sources

Store new data

on customers,

events, etc. for

continuous

improvement

Predictive Analytics

Capture Act

�Improve customer retention

�Grow share of wallet

�Minimize risk

�Increase customer satisfaction

� Enhance market share

Prospects

Customers Constituents

Employees

Students Patients

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� “More and more people are living part of their lives online and sites like Facebook provide a way for brands and researchers to move beyond traditional onewayobservation and dialogs.”

Meg Sloan, market research Lead Facebook

Text Mining in Market Research?


� “The combination of social computing tools and an understanding of social networks is allowing us to build new types of research communities as well as observe organically created ones, in which respondents can interact not only with the researchers but with our clients and, most fertilely, with each other

� Mike Cooke GFK NOP

Business Analytics

Time is of the essence

ComplexResponses need

interpretation.

RestrictivePre-determined coding scheme for consistency.

Time-Consuming& Costly

The standard coding process...


Text is read quicklyand intelligently.

(Natural Language Processing)

A robust coding scheme is derived.

(Manual/Automatic)

Response coding is fast, accurate,and consistent.

Scalable.Projects are

easily re-usable with new data-sets.

With IBM SPSS Text Analytics...

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Including Social media channelsComments regarding customer experience:


Sentiment Analysis enables organizations to categorize a person’s own words based on both business issues and customer opinions

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From Unstructured to insight to foresight

From analyst workbenches…


…to executive reports

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Text mining in Market Research: Extracting the Value

�Speed– The power to run text automatically

�Focus– To find the key concepts and phrases

� Integration– Look across many different sources


– Look across many different sources

�Value – Deliver insight that is critical and impactful

“Text Mining can be one of the most powerful tools to discover new insights and hypotheses from existing data”

Dr. Markus Eberl TNS Infratest Forschung GmbH

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Business Analytics

Complete Workbench


I2

Slide 23

I2 New image with some blurbs...take it apart a bit and show value that may be easier to lead into the other stuff???IBM_USER, 4/26/2010

Business Analytics

Complete Workbench

�Access both structured and unstructured data from virtually anywhere

�Powerful data aggregation, transformation, cleansing and manipulation

�Full range of modeling algorithms


�Full range of modeling algorithms �Apply multiple techniques and

create ensemble models easily�Leverage intuitive visualizations

to evaluate models�Deploy predictive intelligence in

multiple ways

I1

Slide 24

I1 New image with some blurbs...take it apart a bit and show value that may be easier to lead into the other stuff???IBM_USER, 4/26/2010

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Predicting Outcomes and Measuring Effects

Let the data show you the path to an outcome


Is this factor consistently important?

What is important to the outcome? How does this

factor contribute to the outcome?

Where are the links between events?

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Finding Commonalities and Differences

Find clusters and interact with results visually


Find anomalies and identify their root cause

Not forgetting Data management and quality


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Data Sources & Preview


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Data Merge & Preview


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Data Visualization and Preparation

Visualization Use tables and reports

Use interactive graphs


Transformation and Preparation

Use interactive graphs

Summarize and Manipulate Records

Clean, Transform and Validate Fields

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Automatic Data Preparation


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Data Analysis & Modeling


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Internal DataInternal Data

Transactions, Utilisation, ...

Hard Facts

�� Where, what, when,

Transactions, Utilisation, ...

Hard Facts

�� Where, what, when,

External DataExternal Data

Needs, Motivations, Satisfaction

Soft Facts

�� Why, how, what for?

Needs, Motivations, Satisfaction

Soft Facts

�� Why, how, what for?

DataFusion enriches internal data with attitudes


�� Where, what, when, how much?

�� Where, what, when, how much?

BehaviourBehaviour

�� Why, how, what for?�� Why, how, what for?

AttitudesAttitudes

Attitude-basedDatabase Enrichment

Attitude-basedDatabase Enrichment

Business Analytics

Contact

data:

name,

address,

phone,

...

Master

data:

age,

gender,

...

Transaction

data

(behaviour):

product

usage,

...

Internal Data: customer database

Projecting the market research findings back into the customer

database

Data Fusion

DataFusion - Methodological Approach


Market research:

typology of consumers,

target segments, affinities, scores, …

Master

dataTransaction

data

Model estimation

Anonymous,representative sample

customer-ID <=>

interview-ID

Sampling

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IBM SPSS Technology

�Created to be:

–Innovative

–Powerful

–Flexible

–Integrated


–Integrated

–Scalable

–Easy to use

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The Future

‘The future is already here – it’s just unevenly distributed.’

William Gibson (1999)


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�Changing dynamics of the MRI

Summary


�Changing dynamics of the MRI

�Leverage comprehensive workbench for data and text

�Maximize efficiencies throughout the research process

�Capitalize on new market trends

�Deliver insight and foresight

�Become the Insight Partner

Questions?


Business Analytics

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