Finding the “Sweet Spot”: Big Data, Smart Technology, and Domain Knowledge

a company

www.empowerresearch.com

Finding the “Sweet Spot”: Big Data, Smart
Technology, and Domain Knowledge

Debjani Deb
Managing Partner
ddeb@empowerresearch.com

1
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All Rights Reserved.

2005 130

We are drowning in

Vo l um e o f G l o b a l D a t a i n E xa b y t e s
a sea of data
2720 2012

2015
7910
2
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But it’s not just the volume of data we are dealing with

The 4Vs of “Big Data”

1 2 3 4

Volume of Velocity of Variety of Value
data data data from data

3
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While historically focus has been on processing big “volumes” of
data, the real value lies somewhere else

Cost of data processing has
often exceeded the value
High The “Big”
O p p o r t u n i t y To d a y
This is where you need to be
(integrated view on volumes,
velocity and variety) 1 Ve l o c i t y
Real time insights on
Va l u e

customer preferences and
issues faced
Most companies are here
(high data processing and technology costs) 2 Va r i e t y
Bringing together disparate
data-forms for holistic and
Low actionable insights

Low Costs / Investment High

4

The advent of social media: volumes, velocity and variety leading
to greater value for businesses

66% 14% 21% 31%

Of those online now use 14% either publish a blog/ web 21% post ratings or 31% post updates on
social media page or upload videos comments in forums social sites

HOW MANY INTERNET USERS TURN TO SOCIAL REGULARLY TURN TO SOCIAL MEDIA
MEDIA WHEN MAKING PURCHASES SOMETIMES TURN TO SOCIAL MEDIA

Travel Financial Eating Clothes or Mobile Groceries or Personal
Services Services Out Fashion Phones Food Care
4% & 24% 4% & 10% 3% & 21% 4% & 23% 2% & 21% 2% & 15% 3% & 15%

$$
Sources: www.sanfranciscosentinel.com, wwwblogs.forrester.com, Knowledge Networks
5

The market is waking up to the velocity , variety and value of
insights possible from this data stream: example 1

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

Sentiment of companies
$$
on Twitter closely
follows market Twitter Lead
movements. Also shows Trends Indicator
positive correlation
between trading volume
and message volume
on Twitter
Sprenger and Welpe (2010)

6


A leading data Sales alerts Service
products company alerts
(B2B) uses social
media for
Identifying
opportunities of sales,
engagement and
service improvements
Engagement alerts

Impact
30 alerts every
month leading to Determine
annual sales  Pain areas related to customer services

ENABLE ACTION
pipeline of over  The most important product attributes for
$12 million exceeding end user expectations
Develop
 Strategies that address enduring customer
service needs and expectations

7


A global leader in Increase in Awareness Sentiment
confectionary
products wanted to
identify the impact of
negativity / Negative
Sentiment
sentiments on overall
brand loyalty
Week 1 Week 2 Week 3 Week 4

Impact
Predictive models to First timers
Loyalist
measure impact of
negativity on
loyalists
Switchers

8

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 Diagnostics Data cleansing Data Standardization
(One time) (Ongoing) (Ongoing)
Detailed understanding of Detecting and correcting (or Ensuring that field entries
various data forms in which removing) corrupt or from one source match field
data is captured inaccurate records entries from another

Bytes + Brains
Processing

Insights
9

Case study 1

10

About the client and
their business
problem
Our Client
A global leader in credit cards

Business The client wanted to understand a holistic net promoter score across
Problem countries which included disparate new and existing data sources

11

Our approach to integrate disparate data forms

Data source Systems Output measures Outcome

Social Media
NPS
Unstructured

System 1 Indicative drivers
Responsiveness

System 2 Performance Empathy
Emails
measures (Top
Reliability
box excellence)
System 3 Respect
Call Records Satisfaction Security
System 4
measures (CSI)
Structured

Surveys
EmPower Media Competitor Competitor
Interactive Dashboard Insights
Feedback

Co-relate sentiment, advocacy, loyalty and influence in real-time to
directional NPS

12

Business Outcomes
Product attributes that
Client Competitor impact customer
experience were brought
into focus, reorienting
33% Unhappy about resources from non-
Service verification
59% charges performing ones

Competitive benchmark of
26% Safe transactions 1
product attributes
Security won customer
58% confidence Identification of customer
2
satisfaction drivers in real-time
premium cards
30%
Respect provided were
48% admired

Sentiments (%)
13

Case study 2

14

their business
problem
Our Client
A leading venture capital firm

Business While comprehensive CRM solutions existed on profiling target
Problem portfolios and prospect companies, the existing solutions lacked ability
to integrate real-time data on sentiments, trends, perceptions etc.

15

Our approach to integrate real-time insights into CRM

Data Pull from the Sites into Salesforce done real-time; optimized
to filter noise; and produce customized profiles for client

Salesforce Connector
Content Mining
Filtering

Semantic Analysis Company
NLP Profiling
Machine Learning
Client
Salesforce
Influential sources

1 SMMART 2 Crawling 3 Seamless
Building Learning Engine Integration
blocks of white-list sources, comprehensive A 2 way seamless
our solution keyword hierarchy crawling from a wide integration
and service bureau variety of sources interface
SMMART: Social Media Multi-Attribute Rating Tool
16

Business Outcomes
A system that enables
investment professionals
Sectoral Viral news Executive hire / with comprehensive social
trends fire updates media insights on their
Performance target companies
updates Perception of
between results management Near-term value
Velocity of actionable insights
being integrated in their CRM in
Customer near- real time mode
Sentiment
trending satisfaction
Long-term value
Scalability across different media
Stakeholder New product or types, languages, user groups,
perception on innovation target companies
performance

17

Case study 3

18

their business
problem
Our Client
World leader in pharmaceutical products

Business Existing databases captured point of sales and promotional data but
Problem there was not qualitative input which explained sales fluctuations or
business impact of competitor initiatives

19

Our approach

S t a r t i ng Hyp o t h e s i s Marketing efforts, product features and competitor actions drive sales

IMS Data Social Media
IMS Data
(Lag) Data (Lead)

Sentiment
Medical Data

Awareness

Sales

Share of
Voice
Promo Data Perception Sentiment

20

Business Outcomes
Negative discussions seen on
Competitor_X side effects  Social media integrated
influenced sales in a poitive way with IMS data to explore
Patients felt better and SALES
correlations between drug
well after using KPIs and drug’s sales
Competitor_Y
performance

SALES Ability to predict and positively
1
influence sales pipelines

Real time insights on strategy
2
Mon 1 Mon 2 Mon 3 Mon 4 Mon 5 Mon 6 Mon 7 and tactics
Competitor_X Negative Competitor_Y Conversations

o Competitor_X’s negative tonality increased sales
o Competitor_Y’s conversations affected sales performance in a
negative way

21

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….

22

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Disclaimer: The data presented in this presentation is collected
from publically available resources. EmPower Research doesn’t
EmPower Research Knowledge Services Pvt. Ltd. take any responsibility on the authenticity of the data disclosed
Ozone Manay Tech Park in this presentation and outcomes of decisions taken based on
3rd floor, Block B such data by the recipient of this presentation.
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