Emerging
Marketing
Analytics



BIG DATA

 Akash| Bryan|
Nishi| Prashant|
  Subhadeep|
    Vaibhav
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
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.
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
RETAIL
- Walmart
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
Market Causality




                   Intervening

                   Component

                   Antecedent

                   Extraneous
Data Organization
Type of Errors    Manual Data    Automated Data
                  Organization   Organization

Incoherent


Incorrect



Irrelevant


Incomplete



Inconsistent
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
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
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
How Walmart connects!




                  More than 2   Daily consumer
Over 22 million
                    million       insights and
     likes
                  comments       data mapping
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
THANKS

Big Data Marketing Analytics

  • 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 BigData? 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.
  • 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 ofErrors 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.

Editor's Notes

  • #3 Unstructured Data: Most of the content on web is unstructured
  • #5 The speed with which Big data is growing, companies which are proactive and have the capability to provide big data analytics will have a competitive edge over the competitors as compared to the companies which do not have such provisions.