Data-Driven Marketing Roadshow Attivio - March 27, 2014

Delivering Big Content

Insight for Marketing

Peter Philipp

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Avoid data theft and downtime by extending the

security perimeter outside the data-center and

protect from increasing frequency, scale and

sophistication of web attacks.

What is Big Data, really?


The Data Universe Big Bang

The Data Universe

Structured

Unstructured

Unstructured Data

Unstructured

Content

Business Intelligence

Enterprise Search


The (more) Complete Data Universe

The Data Universe

Structured

Unstructured

Unstructured Data

Unstructured

Content


Can you really use Big Data tools for Big Content?

Big Data Big Content

Many small records needing

reduction into something

meaningful

Many large documents often

needing individual

decomposition into multiple data

points

Often very high rates of change at

machine speeds, usually net-new

records

Rates of change at human speeds,

often in the form of updates

Many different varieties of sources

(social, web logs, sensors, etc.)

Dozens of languages, hundreds of

file types. Ultimately very “jagged”

data results

Vo

lum

eV

elo

cit

yV

ari

ety


Understanding your customer‟s sentiment

Will the word „sick‟ be good or bad?






Let‟s look at Big Content a bit closer

To: X Airline Service <[email protected]>

From: Joe Customer [email protected]

Subject: My recent experience with your phone agent

Date: 3-1-2013 01:35:00

I travelled on your airline from San Francisco to Boston and had a terrible experience with

your phone agent. I had recently been granted frequent flyer status on your airline matching

my status on airline Y and when I checked in for my flight was able to select a window

upgraded seat. However, when I arrived at the airport, I was in a middle seat. I called the

customer help desk and was told that “no seats are guaranteed” and there was nothing that

could be done for me. The agent spoke in a very rude tone, not the way I would expect you

to treat your frequent flyers.






What does this single email tell us?

To: X Airline Service <[email protected]>

From: Joe Customer [email protected]

Subject: My recent experience with your phone agent

Date: 3-1-2013 01:35:00

I travelled on your airline from San Francisco to Boston and had a terrible experience with

your phone agent. I had recently been granted frequent flyer status on your airline matching

my status on airline Y and when I checked in for my flight was able to select a window

upgraded seat. However, when I arrived at the airport, I was in a middle seat. I called the

customer help desk and was told that “no seats are guaranteed” and there was nothing that

could be done for me. The agent spoke in a very rude tone, not the way I would expect you

to treat your frequent flyers.

Sentiment

Competitor

Key terms for my

industry

Relevant Airport

Locations and

Route

Customer emailCustomer name

mailto:[email protected]


What could the value of a lot of emails be?

• Now we can

answer new

questions like:

• “Which routes are

driving negative

customer

experiences and

why are they

unhappy with

those routes?”


Building Bridges from Big Content to Big Data

• Leverage Text Analytics routines for interpreting content

• Entity Extraction: detection of people, places, things

• Key Phrase Detection: identifying topics and concepts

• Classification: sentiment analysis, categorization

• Lean on metadata layers

• Corporate taxonomies (e.g. product hierarchies, sales territories, etc.)

• Controlled vocabularies (e.g. Medical Subject Headings)

• It‟s all about tying the Content back to a Business Entity

• For example: identifying that the email is a complaint about Product XYZ


Big Content is everywhere!

Verticals Information Sources for Analysis

Financial Services / Insurance News, research reports, email, company filings, claims

Pharma / Life Sciences Patents and applications, clinical trials annotations,

electronic lab notebook, technical publications

Healthcare Patient records, care management systems, surveys

Government Analyst reports, news, communications, intelligence

Manufacturing / High Tech Parts catalogs, manuals, purchase orders, maintenance

comments, shift logs, field reports, safety reports

Media / eCommerce Social media, news, blogs, reviews


Case StudyMajor UK Retailer

• Leverage data from all sources to drive actionable insights in

real time

• Understand the impact of posts, sentiment on product

revenues and promotions

• Optimize to supply to demand

• Provide search and text analysis for

Facebook, Twitter, Databases and internal chat Yammer

integrated into BI tool

• Key phrase and entity extraction, document classification

according to customer product hierarchy, sentiment analysis

• Delivery in 4 weeks

• Maximize revenue from promotions – tap into trends, events, etc as

they happen

• Execute 1-1 marketing & merchandising strategies in real-time

• Quickly understand the „why‟ behind the „what‟ – tap into positive

revenue trends


Social Media AnalysisFull search

integration, let’s try bread

Select areas where sentiment is mostly negative in social media

Focus on negative comments

“Bread Dated” is a keyphrase, lets

see why… Customers are complaining that stale bread is

continually sold in stores!

Drill deeper by campaigns or promotions

Data-Driven Marketing Roadshow Attivio - March 27, 2014

Marketing

Transcript of Data-Driven Marketing Roadshow Attivio - March 27, 2014