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Today, we are witnessing a data explosion of unimaginable magnitude. Much of this Big Data is being generated through the emergence of new technologies, devices, networks, mobility and interoperability. Big Data is seldom useful in itself - given its size and variety, it lends itself to meaningful scrutiny only when viewed through the prism of the business problem or process of interest. Smart decisions increasingly lie at this intersection of Big Data, Smart Technology and Domain Knowledge. This presentation, through several illustrative case studies, talks about how Big Data generated through social media is emerging as a strong source of insights for demand signaling.
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Finding the “Sweet Spot”: Big Data, Smart
Technology, and Domain Knowledge
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www.empowerresearch.com
Debjani Deb Managing Partner
a company
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We are drowning in
a sea of data
Vo
lum
e o
f G
lob
al
Da
ta
in
Ex
ab
yte
s
130
2720
7910
2005
2012
2015
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But it’s not just the volume of data we are dealing with
Velocity of
data
Volume of
data
Variety of
data Value
from data
The 4Vs of “Big Data”
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While historically focus has been on processing big “volumes” of
data, the real value lies somewhere else
Low High
Low
High
Most companies are here
Va
lue
C o s t s / I n v e s t m e n t
T h e “ B i g ”
O p p o r t u n i t y To d a y
1 Ve l o c i t y
Real time insights on
customer preferences and
issues faced
C o s t o f d a t a p r o c e s s i n g h a s
o f t e n e x c e e d e d t h e v a l u e
2 Va r i e t y
Bringing together disparate
data-forms for holistic and
actionable insights
(high data processing and technology costs)
This is where you need to be (integrated view on volumes,
velocity and variety)
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The advent of social media: volumes, velocity and variety leading
to greater value for businesses
1 4 %
Of those online now use
social media
14% either publish a blog/ web
page or upload videos
21% post ratings or
comments in forums
31% post updates on
social sites
3 1 % 2 1 % 66%
Sources: www.sanfranciscosentinel.com, wwwblogs.forrester.com, Knowledge Networks
HOW MANY INTERNET USERS TURN TO SOCIAL MEDIA WHEN MAKING PURCHASES
REGULARLY TURN TO SOCIAL MEDIA
SOMETIMES TURN TO SOCIAL MEDIA
Travel
Services
4% & 24%
Financial
Services
4% & 10%
$$
Eating
Out
3% & 21%
Clothes or
Fashion
4% & 23%
Mobile
Phones
2% & 21%
Groceries or
Food
2% & 15%
Personal
Care
3% & 15%
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The market is waking up to the velocity , variety and value of
insights possible from this data stream: example 1
Sentiment of companies
on Twitter closely
follows market
movements. Also shows
positive correlation
between trading volume
and message volume
on Twitter
According to a study
conducted by scientists
from Indiana University
and the University of
Manchester, social
media has an 86.7%
accuracy rate at
predicting the stock
market
Sprenger and Welpe (2010)
Trends Lead
Indicator
$$
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The market is waking up to the velocity , variety and value of
insights possible from this data stream: example 2
A leading data products company (B2B) uses social media for Identifying opportunities of sales, engagement and service improvements
Impact
30 alerts every month leading to annual sales pipeline of over $12 million
Sales alerts Service
alerts
EN
AB
LE
AC
TIO
N
Engagement alerts
Determine
Pain areas related to customer services
The most important product attributes for
exceeding end user expectations
Develop
Strategies that address enduring customer
service needs and expectations
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The market is waking up to the velocity , variety and value of
insights possible from this data stream: example 3
A global leader in confectionary products wanted to identify the impact of negativity / sentiments on overall brand loyalty
Impact
Predictive models to measure impact of negativity on loyalists
Loyalist First timers
Switchers
Week 1 Week 2 Week 3 Week 4
Increase in Awareness Sentiment
Negative
Sentiment
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The key to insights depends on how one can integrate disparate
forms of data in a near real time framework
Internal Data External Data
E-mails Surveys Call Records Social Media
Data Standardization Data cleansing Data Diagnostics
(One time)
Detailed understanding of
various data forms in which
data is captured
(Ongoing)
Detecting and correcting (or
removing) corrupt or
inaccurate records
(Ongoing)
Ensuring that field entries
from one source match field
entries from another
Bytes + Brains
Processing
Insights
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Case study 1
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O u r C l i e n t
A global leader in credit cards
B u s i n e s s
P r o b l e m The client wanted to understand a holistic net promoter score across
countries which included disparate new and existing data sources
About the client and
their business
problem
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Our approach to integrate disparate data forms
Co-relate sentiment, advocacy, loyalty and influence in real-time to directional NPS
Responsiveness
Empathy
Reliability
Respect
Security
Indicative drivers
Emails
Social Media
Call Records
Surveys
Feedback
Str
uctu
red
Unstr
uctu
red
Data source Systems Output measures Outcome
NPS
Performance
measures (Top
box excellence)
Satisfaction
measures (CSI)
System 1
System 2
System 3
System 4
EmPower Media
Interactive
Competitor
Dashboard
Competitor
Insights
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30%
48%
26%
58%
33%
59%
Service
Security
Respect
Safe transactions
won customer
confidence
Unhappy about
verification
charges
premium cards
provided were
admired
Sentiments (%)
Client Competitor
Business Outcomes
1 Competitive benchmark of
product attributes
2 Identification of customer
satisfaction drivers in real-time
Product attributes that
impact customer
experience were brought
into focus, reorienting
resources from non-
performing ones
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Case study 2
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O u r C l i e n t
B u s i n e s s
P r o b l e m
About the client and
their business
problem
A leading venture capital firm
While comprehensive CRM solutions existed on profiling target
portfolios and prospect companies, the existing solutions lacked ability
to integrate real-time data on sentiments, trends, perceptions etc.
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Our approach to integrate real-time insights into CRM
Content Mining
Machine Learning
Semantic Analysis
NLP
Data Pull from the Sites into Salesforce done real-time; optimized
to filter noise; and produce customized profiles for client
Filte
ring
Company Profiling
Salesforce C
on
necto
r
Client
Salesforce
Building
blocks of
our solution
Influential sources
1 SMMART
Learning
white-list sources,
keyword hierarchy
and service bureau
2 Crawling
Engine
comprehensive
crawling from a wide
variety of sources
3 Seamless
Integration
A 2 way seamless
integration
interface
SMMART: Social Media Multi-Attribute Rating Tool
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Business Outcomes
Executive hire /
fire updates
Performance
updates between results
Sectoral
trends
Sentiment
trending
Viral news
Customer
satisfaction
New product or
innovation
Stakeholder
perception on performance
Perception of
management
A system that enables
investment professionals
with comprehensive social
media insights on their
target companies
Near-term value Velocity of actionable insights
being integrated in their CRM in
near- real time mode
Long-term value Scalability across different media
types, languages, user groups,
target companies
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Case study 3
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O u r C l i e n t
B u s i n e s s
P r o b l e m
About the client and
their business
problem
World leader in pharmaceutical products
Existing databases captured point of sales and promotional data but
there was not qualitative input which explained sales fluctuations or
business impact of competitor initiatives
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Our approach
Sales
Se
ntim
en
t
Sh
are
o
f
Vo
ice
Social Media
Data (Lead) IMS Data
IMS Data
(Lag)
Medical Data
Promo Data
Awareness
Perception Sentiment
S t a r t i n g H y p o t h e s i s Marketing efforts, product features and competitor actions drive sales
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Business Outcomes
o Competitor_X’s negative tonality increased sales
o Competitor_Y’s conversations affected sales performance in a
negative way
Mon 1 Mon 2 Mon 3 Mon 4 Mon 5 Mon 6 Mon 7
Patients felt better and
well after using
Competitor_Y
Negative discussions seen on
Competitor_X side effects
influenced sales in a poitive way
Competitor_X Negative Competitor_Y Conversations
SALES
SALES
Social media integrated
with IMS data to explore
correlations between drug
KPIs and drug’s sales
performance
1 Ability to predict and positively
influence sales pipelines
2 Real time insights on strategy
and tactics
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In Conclusion
The rate of change in data creation is only increasing multi-fold each day !
Companies are challenged with existing data repositories that does not complement new sources and repositories
The challenge has to be dealt with, with the right combination of bytes and brains, to be cost effective!
The value of harnessing the data should be thought through in light of actions that it can enable….
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Disclaimer: The data presented in this presentation is collected
from publically available resources. EmPower Research doesn’t
take any responsibility on the authenticity of the data disclosed
in this presentation and outcomes of decisions taken based on
such data by the recipient of this presentation.
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