Big data refers to the large and complex data sets that are difficult to analyze and process using traditional data processing applications. Retailers can leverage big data analytics to gain insights from customer data on social media and other sources to make better business decisions and stay competitive. Walmart analyzes over 2 million daily consumer insights and comments to better understand customers and manage inventory and logistics in a cost-effective way, helping ensure the best prices and customer service.

1. Emerging
Marketing
Analytics
BIG DATA
Akash| Bryan|
Nishi| Prashant|
Subhadeep|
Vaibhav

2. Types Of Data
Data
Semi
Structured Unstructured
Structured
Enterprise Resource Call centre logs with
Traditional Data in a Facebook, linkedin
Planning, back up toll –free responses,
Structured but
traditional Database logs, web chats,
Inconsistent
storage for large unstructured “blobs”
web logs that track
structure YouTube
volumes of data website activity

3. What is Big Data?
Advanced analytics operate on Big Data.
Leverage data to make better business decisions.
Data is increasing at a
Rate at which data Velocity rate of 15-20%
is consumed or Extremely large amounts
-Batch
generated of data (Terabytes)
-Real time
-Near Time
Big data
Variety Volume
-Structured -Terabytes
Range and type of -Unstructured - Transactions
data sources -Semi structured - Tables etc.

4. Big Data: Why?
Uses of Big Data:
• Marketing decisions and analytics
• Innovating new products and services
• Risk management
• Applicable to all domains – BFSI, Telecom, Media, entertainment etc.
Potential of Big Data
Increase value Increase value
Decrease Increase US
of US of Europe’s PSA
manufacturing retails net
healthcare by by EUR250
cost by 50% margin by 60%
$300 billion billion
Source: McKinsey Report

5. RETAIL
- Walmart

6. Need
Retail industry is customer driven
Fierce competition
- Very less switching cost
-Stock out
- Non Availability of any item
Companies should be well informed
-Continuous monitoring of customers data (real
time monitoring
For retailers to be
1. Competitive
2. Customer retention
Track and analyse social media and all other forms of customer data available

7. Market Causality
Intervening
Component
Antecedent
Extraneous

8. Data Organization
Type of Errors Manual Data Automated Data
Organization Organization
Incoherent
Incorrect
Irrelevant
Incomplete
Inconsistent

9. Metadata
Y = Sales
X = 10 P’s of marketing
Y = f(X)
Type of Metadata:
• Customer Life time Value
• Consumer buying behavior
• Transaction pattern
• Churn score

10. Social Media Analytics- the new wave
50% are unsure of
50% businesses
53% are unaware how to measure
are unsure of
of their ROI from impact of
direct value of
Twitter business metrics
LinkedIn
from blogs

11. Social Media Analytics- the new wave
Configure your
Revise your
• Quantitative- specific KPIs
• Social n/w New likes, Analytics
strategy • PAID tools- Radian 6, format
• Change content and
total likes, metrics that
• Choose Page views, •SYSOMOS, Lithium, Raven
Frequency change
referrals
translate into business •• Create a filter or segment
Test test test to get better • FREE tools- Social market
• Study target page
context
• Qualitative data- Users, for social traffic
results Mention, Whostalking,
• Your response rate and
language, locations, •• Add term benefits
Long event tracking Thinkup
relevance
comments •• Measure events responses
Identify worst performing
• Activity data- post views, and interactions
metrics
interactions, interaction
Define measurable •• Ad campaign tracking
Ad campaign tracking Use super social
times, response rates.
and Actionable KPIs What to do?
tools
Understanding
each social metrics

12. How Walmart connects!
More than 2 Daily consumer
Over 22 million
million insights and
likes
comments data mapping

13. RESULTS
Inventory
• Cost and Mission- • Best Price to Customers
success alignment • Right portfolio of goods
• Better inventory and • Understand Customer
Logistics management better
by using Predictive
analytics
Improved
Cost Effective
Customer Service

14. THANKS