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Abacus Market Analytics
(division of IMRB International – Kantar Group)




                                                  1
Agenda

 •   Introduction
 •   Marketing Research and Analytics Services
 •   Advanced CRM Analytics Services
 •   Technology and Research Software Services
 •   Client Engagement/Methodology
 •   Quality Metrics
 •   Appendix
      Case Studies
      Testimonials
      Infrastructure and Security
      What makes us Different




                                                 2
Corporate Identity


                                WPP PLC
               138,000 employees in over 107 countries
                          £ 38 billion in billings


                           The Kantar Group
          Revenues of £ 2.3 billion, 26,500 staff in 80 countries


                           IMRB International


 PQR    CSMM       BIRD       QUANTI       SRI        MnP       MSG/BS   Abacus




                                                                                  3
Specialist Units by Research Method




                Quantitative custom research units in Mumbai, Delhi,
                          Kolkata , Bangalore and Chennai


        Probe Qualitative Research                                Partners in Managing
                                                                Stakeholder Relationships




       The Marketing Sciences Group                           MindTech Systems & Software




                                 Advertising testing and Brand tracking



        Analytics & Data Processing House                           International Field & Tab



                                                                                                4
…and Specialist Units by Industry Sector




                      Research-based consultancy     Social & Rural Research
                    for B2B and Technology Markets           Institute




                                                                               5
Abacus Market Analytics Overview
Abacus MA is a full service research                        Abacus MA Fast Facts
provider catering to the global data
collection, survey programming, data
processing, advance analytics and             Parent formed in 1971, Abacus in 2000
reporting needs of companies in North
America, Europe and Asia                              Part of The Kantar Group/WPP

                                                             300+ Full- time Analysts
We are part of one of the largest and
most respected research agencies in
India, with a team size of over 300 highly   Clients across Asia Pac, Africa, UK, USA
qualified analysts based at our operations
centers in India.                                        Member of ESOMAR & MRA

                                                        ISO 9001:2008 and ISO 27001

                                                          Research in 65 Languages




                                                                                        6
Abacus MA – a Snapshot

 Staff strength of 300, majority of whom are Masters in Statistics, Computer Applications,
                          Operations Research and Engineering



   Tools/Software expertise – SPSS Dimensions, Quantum, Statistica, SPSS, Delphi,



  Our clients are in UK, USA, South Africa, Japan, France, Australia and most of Asia


                                                                         ISO 27001
              ISO 9001
           Certification for      Moving to Six                        Certification for
         Processes & Quality                                        Information Security
                                  Sigma level of
                               delivery capability:
                                automating tasks
                                 and eliminating
                                non-value added
                                      work
                                                                                             7
Agenda

 •   Introduction
 •   Marketing Research and Analytics Services
 •   Advanced CRM Analytics Services
 •   Technology and Research Software Services
 •   Client Engagement/Methodology
 •   Quality Metrics
 •   Appendix
      Case Studies
      Testimonials
      Infrastructure and Security
      What makes us Different




                                                 8
Market Research Solutions


                    Awareness/familiarity of your brand across various market segments
    Brand           Brand perception vis-à-vis competitor brands in the market
  Management        Performance on what parameters drive your brand’s perceptions?
                    Current positioning of your brand in the target segment’s mind


                   Determine right price for various types of product types
Pricing Research   Determine overall price/value and specific price point sensitivities
                   Determine sensitivities to changes in product, pack size, price or distribution



                    Determine the perceived attractiveness of the product/service for the target segment
 New Product/       Determine the ideal price and optimal design for the product/service
Concept Testing     Identify possible matches/mismatches between unmet needs and new features
                    Predict off-take rates of alternative price-feature configurations


                    Are users aware of the full functionality of your product?
Usage & Attitude    What is the usage pattern of different features of your product?
 Measurement        Which product features are the most difficult to use?
                    Are customers using your product over multiple locations?




                                                                                                            9
Market Research Solutions- Cont…


                       Evaluate overall effectiveness of your ad campaigns
    Advertising        Measure positive influences of the campaign on awareness, perception, intention to use
   Effectiveness       Evaluate effectiveness of your ad campaign in communicating intended message
                       Identify the best medium for advertising


                       Prioritize areas of product/service improvement
    Customer           Segment customers on the basis of their satisfaction and loyalty
   Satisfaction        Incorporate customer satisfaction results into your marketing/communications strategy
                       Influence customer behavior in-line with your strategic objectives


                       Measure satisfaction and derive action-points to improve employee retention
    Employee           Identify factors that employees consider when evaluating their experience with your firm
   Satisfaction        Determine satisfaction on each of these factors
                       Segment your employees to deliver focused training and implement retention programs


                       Measure impact of event association on the customers’ image of your brand
Event Effectiveness    Assess impact of your association on industry analysts and competitors
                       Evaluate the success of the event in communicating your intended message
                       Measure impact on likelihood of purchase or recommendation




                                                                                                                   10
Market Research Services

                             Research & Analytics Value Chain

      Survey Design and Primary
                                             Data Processing and Analytics                      Reporting
              Research

• Online & CATI survey scripting                                                   • PowerPoint templates
                                           • Uniform processes and standard
• Programming & non-English                 software platforms                     • Charting & Graphs
 language overlays
                                           • Data entry, data cleansing & coding   • Commenting and Data insights
• Quota management, project                                                        • Topline, Preliminary and Final
                                           • Advanced statistical analysis          Reports with executive summary,
 management and study completion
 support                                   • Modeling                               advanced analysis, conclusions and
                                                                                    recommendations
                                           • Data mining
•   Global online & CATI data collection                                           • Dashboards
                                           • Predictive analytics
• Best in class F2F, CLT’s, mall
                                           • Decision trees
 intercept & qualitative interviews in
 India                                     • Simulation techniques
                                           • Clustering
• Language capabilities in more than                                               Tools: E-Tabs Enterprise, VB.net
 65 languages across continents                                                     based online apps
                                           Tools: FoxPro, Quantum, Pascal,
Tools: Dimensions, In- house                Quanvert, SPSS, Espri, SPSS,
 applications, 4 CATI centers with          Statistica, Dataminer
 150 interviewers



                                                                                                                         11
Programming for a Healthcare Research Agency
A leading global market research agency, specializing in healthcare and headquartered in Europe

          Project Description                           Abacus MA Deliverables

       12 Countries, 8 Languages            Customization of the questionnaire for online research

  TG: Surgeons and General Physicians                Designing the layout of the interface

 2 Screener Sections, 4 General Sections          Programming the online survey in English

    Programming in SPSS Dimensions            Translating the online survey into eight languages

                                               Hosting the survey and monitoring the fieldwork

                                            Real time reporting on data collected during fieldwork

                                                  Data validation and delivery of clean data




                                                                                                   12
Primary Research for a Leading Commercial Bank
           Online Data Collection for a leading commercial bank based in China and Japan

              Project Description                                    Abacus MA Deliverables

      Formulate go to market strategies                   Finalize the recruitment and survey questionnaire

         TG: Retail banking customers                  1,500 surveys to be completed across China and Japan

           N=1500, Japan and China                                3D Quota with multiple skip patterns

      Programming in SPSS Dimensions                     Voice based recruitment and phone/Web completion

                                                               Questionnaire translation and localization

                                                       Programming, hosting and management of Web survey

                                                        Survey Coding/Design of data reporting files in SPSS

                                                        Real time reporting on data collected during fieldwork

                                                                 Final presentation with study findings



Efficient and effective management of the entire program involving secondary research, questionnaire design, sample
allocation, recruitment, surveys and reporting/presentation with recommendations/findings
Met the stringent timeline of 14 weeks of the client
Multi channel-recruitment by phone, and survey completion on


                                                                                                                      13
Advanced Survey Analytics

• Z-Test                                                          • Multiple Regression Analysis
• T-Test                                                                  • Discriminant Analysis
• ANOVA                                                                     • Logistic Regression
• Chi-Square Test                                                              • Conjoint Analysis
                                                                • Canonical Correlation Analysis
                                                                                  • Path Analysis
                                Hypotheses     Dependence
                                  Testing      Techniques




                                Data Mining   Interdependence
                                Techniques       Techniques




                                                                               • Cluster analysis
• Decision Trees/Segmentation                                         • Multidimensional Scaling
• MARSpline                                                          • Correspondence Analysis
• Market Basket Analysis                                                        • Factor Analysis


                                                                                                14
Churn Prediction for a Telecom Client
     Gather customer         Run Various
  requirements including      Descriptive                                                                   Using Data Mining                                                                                                  Evaluate results
      churn definition,      Analyses and                                                                   Techniques, Build                                                                                                   and select the
    variable information      transform                                                                          Models                                                                                                          best models
             etc               variables

 Data Mining Techniques          Outputs- Best Result Lift Values and Graphical Pane

    Descriptive Analysis                                                         Lift Chart - Lift value
                                                                               Cumulative; Category: 1
                                                                        Analysis sample;Number of trees: 1377
                                                                                                                                                                                            Lift Chart - Lift value
                                                                                                                                                                                         Cumulative; Category: 1
                                                                                                                                                                                  Test set sample;Number of trees: 1377
                                                    4.0                                                                                                       3.0
                                                    3.8                                                                                                       2.9
                                                                                                                                                              2.8
                                                    3.6

       Boosting Trees                               3.4
                                                    3.2
                                                                                                                                                              2.7
                                                                                                                                                              2.6
                                                                                                                                                              2.5
                                                                                                                                                              2.4
                                                    3.0
                                                                                                                                                              2.3
                                                    2.8                                                                                                       2.2

      Random Forests                                2.6
                                                    2.4
                                                                                                                                                              2.1
                                                                                                                                                              2.0
                                                                                                                                                              1.9
                                                    2.2
                                                                                                                                                              1.8




                                       Lift value




                                                                                                                                                 Lift value
                                                    2.0                                                                                                       1.7
                                                    1.8                                                                                                       1.6

  Support Vector Machine                            1.6
                                                    1.4
                                                                                                                                                              1.5
                                                                                                                                                              1.4
                                                                                                                                                              1.3
                                                    1.2                                                                                                       1.2
                                                    1.0                                                                                                       1.1
                                                                                                                                                              1.0
                                                    0.8                                                                                                       0.9
                                                                                                                                      Baseline
                                                          0   10   20     30     40     50     60     70        80   90   100   110                                                                                                             Baseline

      Detailed Steps                                                                                                                  Model                         0   10   20     30     40     50     60     70        80   90   100   110
                                                                                                                                                                                                                                                Model
                                                                                        Percentile
                                                                                                                                                                                                  Percentile




       Data selection

    Data transformation

   Binning and Sampling

 Use of modeling technique

 Results using Lift Charts


                                                                                                                                                                                                                                                           15
Segmentation for a Telecom Client
                                        Objectives of the Study                                                      Methodology

                          Identify rules for needs based segmentation at macro level                                 Create Segments

                    Test the goodness of fit of this sample for the entire user base of Client                      Identify Key Drivers

                                 Replicate segments across the user database                                 Identify Most Important Variables

                           Gain customer insights for better campaign management                                  Run Cluster Algorithms

                                                                                                           Run Cluster Algorithms multiple times


                                                                                                              Statistical Techniques
                                                                                                                  K-Means Clustering

                                  Graph of means for c ontinuous variables
                                                                                                                     EM Clustering
                                            Num ber of c lus ters : 4
                   0.5

                                                                                                                    Random Forests
                   0.4


                                                                                                                    Boosting Trees
Normalized means




                   0.3




                   0.2




                   0.1


                                                                                            Clus ter   1
                                                                                            Clus ter   2
                   0.0                                                                      Clus ter   3
                               S MS               Inc oming Calls                 S TD      Clus ter   4
                                      Outgoing Calls                    Roaming



                                                                                                                                             16
Path Analysis
   A Model relating customer satisfaction to real business out-comes

   Network Quality                .41

                                                          .51
                                .16      Overall Quality of
Customer Care Experience
                                             service
                                .11                             .58
Recharge experience

                                                          Value for Money         .69



                                                                                                        .87

                                                                      .69                Intention to
                                                                                         Continue


         Tariff plan                    .69                                 .91
                                                                                        .10

                                        .45                      Cost

Accuracy of balance reduction

                                                                                                        17
Agenda

 •   Introduction
 •   Marketing Research and Analytics Services
 •   Advanced CRM Analytics Services
 •   Technology and Research Software Services
 •   Client Engagement/Methodology
 •   Quality Metrics
 •   Appendix
      Case Studies
      Testimonials
      Infrastructure and Security
      What makes us Different




                                                 18
Advanced Analytics Solutions
   Core Objectives                            Analytics Solutions
                                                                 Behavioral Segmentation
                            Customer behavior analysis         Demographic Segmentation
                                                               Psychographic Segmentation
     Acquire New
      Customers
                               Customer Acquisition
                                                                   Response Modeling
                          Improve Efficiency of Acquisition
                                                                      Offer Testing
                                   Campaigns


  Increase Wallet-Share          Grow Customers
                                                                        Modeling
  in existing customers   Improve Efficiency of Cross-Sell /
                                                                 Cross-sell/up-sell model
                                Up-sell Campaigns

                             Marketing Effectiveness
                           Understand Effect of Different          Market Mix Modeling
    Retain Existing             Marketing Drivers
     Customers
                               Customer Retention                    Churn modeling
                             Reduce Customer Attrition               Survival Analysis



                                    Special tools used by the team :
                                     Random Forests
                                     Support vector machine
                                     Multivariate Adaptive Regression Splines (MARS)
                                     Boosted Trees
                                     Memory based reasoning

                                                                                            19
Data Analytics Methodology & Processes (CRISP)
                    Abacus follows the industry accepted CRISP methodology



     Business               Data             Data            Analysis &                          Reporting &
     objectives                                                                Evaluation
                           study          preparation        modeling                            deployment



• Evaluate        • Identify data   • Standard          • Select          • Compare         • Deployment
  business          needs             operating           modeling          with desired      planning
  objectives                          procedures          technique         outcomes
                  • Map data          on data                                               • Resource
• Decide on         needs to                            • Build model     • Evaluate          allocation
  the planning      sources         • Data                                  results
  horizon                             cleaning          • Generate                          • Periodic
                  • Identify data                         test design     • Review &          screening &
• Determine         gaps &          • Data qc for                           revisit model     scrutiny of
  data mining       mismatch          missing           • Test run on                         model
  goals                               fields,             sample data     • Client
                  • Evaluate          values,                               feedback and    • Reporting as
                    data sources      mismatch          • Assess            domain            based on
                                                          model             application       client
                  • Suggest data    • Transition to                                           requirements
                    sources           standard
                                      templates
                  • Explore data
                    type and        • Data
                    quantity          formatting



                                                                                                               20
Consumer Panel Analytics




                            Market                                 Market Mix
                           Structure                               Modeling
• Identify the most
                                          • Likely to buy        • Impact of
     profitable
                       • Identify the       which brand          Advertising
      segment
                      interaction with                            Promotion,
                      other categories                        Distribution Price
       Usage
                                              Predicting
    Segmentation




                      Market Basket      Cox Regression        Pooled Fixed or
Cluster Analysis
                        Analysis                            random effects model




                                                                                   21
Agenda

 •   Introduction
 •   Marketing Research and Analytics Services
 •   Advanced CRM Analytics Services
 •   Technology and Research Software Services
 •   Client Engagement/Methodology
 •   Quality Metrics
 •   Appendix
      Case Studies
      Testimonials
      Infrastructure and Security
      What makes us Different




                                                 22
Technology and Research Software Solutions


 •   Customized Graphics tool                                   • Template Designing
 •   Better Insights                                                 • Query Filtering
 •   Excel Based                                                 • Migrating daily data
 •   Flash Based                                                   • User friendly GUI
 •   Windows Based                                             • Web Based interface
 •   Web Based
                                Dashboards          OLAPs




                                       Automated
                                     Marketing Tools



                                 •Choice based conjoint tool
                                 •Media measurement tools
                                   •Pricing Research tools

                                                                                          23
Dashboard- Example (Web Based)




                                 24
Normative Database
     Merged Data for Different CRA Studies conducted for Multiple industries

      Data Uploading Module                          Data Analyzing Module

         Master File Creation                         Data of Multiple Studies

    Unique Code for each Variable                 User can select specific data type

   Restructuring for Data Merging                  Scores are averages of studies
  Specific Format using Visual Basic                  Multiple data at one place




                                                                                       25
Using Data Fusion to measure ROI



  Two way fusion of housewife TV viewership from TAM and her
   purchases of FMCG from the Household purchase panel

  Helps in identifying the Return on Investment of advertising

  User friendly software - IMRB MagicBox to analyze advertising
   impact on purchases




                                                                   26
Agenda

 •   Introduction
 •   Marketing Research and Analytics Services
 •   Advanced CRM Analytics Services
 •   Technology and Research Software Services
 •   Client Engagement/Methodology
 •   Quality Metrics
 •   Appendix
      Case Studies
      Testimonials
      Infrastructure and Security
      What makes us Different




                                                 27
Client Engagement


                                  Ad-hoc and On Demand




       Client Engagement                                Blended Model




                                 Dedicated Research Center



                          Features and Benefits
         •   One off projects to handle client peak loads
         •   Quick project initiation and turn around time
         •   Dedicated project managers and single point of contact
         •   Scale up depending on client requirements

                                                                        28
Agenda

 •   Introduction
 •   Marketing Research and Analytics Services
 •   Advanced CRM Analytics Services
 •   Technology and Research Software Services
 •   Client Engagement/Methodology
 •   Quality Metrics
 •   Appendix
      Case Studies
      Testimonials
      Infrastructure and Security
      What makes us Different




                                                 29
Quality Metrics


   Customized Quality Metrics for each client
   Separate ‘Quality Certification & Audit’ cell
         Member of ESOMAR and MRA                                         ISO 9001
                                                                       Certification for
     ISO 9001:2008 and ISO 27001 certified                           Processes & Quality
                                                   Quality Norms


  Exhaustive Training Program for each Analyst
       Regular updated training modules


                                                         Training

   Live Monitoring by Quality Team members
       One to One feedback with Analysts
    Individual exhaustive development plans

                                                          Feedback




                                                                                     30
Agenda

 •   Introduction
 •   Marketing Research and Analytics Services
 •   Advanced CRM Analytics Services
 •   Technology and Research Software Services
 •   Client Engagement/Methodology
 •   Quality Metrics
 •   Appendix
      Testimonials
      Infrastructure and Security
      What makes us Different




                                                 31
Client Testimonials

“The research team does not act on the research brief as is, they think of the problem
in depth and challenge the thinking, and usually come up with innovative
methodologies that best achieve the objectives”



                     “Superb planning and teamwork, ensuring high quality data collection in almost
                        clockwork fashion. I am absolutely delighted by the business relevance of the
                                         findings in helping us take an important business decision”



“IMRB showed a high degree of professionalism, rigour and discipline. An excellent
level of Client servicing and need fulfillment, pro-activeness and analytical focus”


                   “Thank you for your quick and valuable inputs during the study. You have proved
                                                                yet again that we can depend on you”



“As a team they produce thoughtful proposals, excellent fieldwork and
presentations. They are constantly involved in the work. They feel like a version of
our own office”


                                                                                                   32
Infrastructure and Security
                  Infrastructure                                               Security

•      Delivery centers in New Delhi, Mumbai,            •   General security/ Physical security/ Employees/
       Bangalore, Pune and Kolkata                           Third-parties
                                                         •   Secure cabinets for data storage
•      Technology and network infrastructure to          •   Data kept with only designated individuals
       ensure data secure environments
                                                         •   Data is processed only in a physically secure
                                                             area
•      Client connectivity infrastructure includes VPN   •   Machines/ files are password protected
       (Virtual Private Network) links between IMRB
                                                         •   Employee Training on Information Security
       and Client networks
                                                             every 3 months
                                                         •   Manual data is shredded when deemed not
•      Constantly enhance our infrastructure based           required
       on our own and Client's business requirements
                                                         •   Personnel required to sign appropriate non-
         ISO 27001                                           disclosure agreements
       Certification for                                 •   Restricted Swipe Card access to production
    Information Security
                                                             areas
                                                         •   Writeable media banned from production areas




                                                                                                               33
So what makes us DIFFERENT??

                    Loyal Client
                   relationships




                    WHAT’S
                  DIFFERENT?




                   Multi-country
                    research
                    capability
                                   34
Thank You

For business queries please contact:

Surya Kiran (Manager - Business Development)
Email: surya.kiran@imrbint.com
Office Line: +91 11 40893238
Mobile: +91-9873336087
Or
Bart Zehren
Email: bz@your-research-resource.com
Phone: +1 847-864-7159
                                               35

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Abacus MA Presentation - Non MR Analytics

  • 1. Abacus Market Analytics (division of IMRB International – Kantar Group) 1
  • 2. Agenda • Introduction • Marketing Research and Analytics Services • Advanced CRM Analytics Services • Technology and Research Software Services • Client Engagement/Methodology • Quality Metrics • Appendix Case Studies Testimonials Infrastructure and Security What makes us Different 2
  • 3. Corporate Identity WPP PLC 138,000 employees in over 107 countries £ 38 billion in billings The Kantar Group Revenues of £ 2.3 billion, 26,500 staff in 80 countries IMRB International PQR CSMM BIRD QUANTI SRI MnP MSG/BS Abacus 3
  • 4. Specialist Units by Research Method Quantitative custom research units in Mumbai, Delhi, Kolkata , Bangalore and Chennai Probe Qualitative Research Partners in Managing Stakeholder Relationships The Marketing Sciences Group MindTech Systems & Software Advertising testing and Brand tracking Analytics & Data Processing House International Field & Tab 4
  • 5. …and Specialist Units by Industry Sector Research-based consultancy Social & Rural Research for B2B and Technology Markets Institute 5
  • 6. Abacus Market Analytics Overview Abacus MA is a full service research Abacus MA Fast Facts provider catering to the global data collection, survey programming, data processing, advance analytics and Parent formed in 1971, Abacus in 2000 reporting needs of companies in North America, Europe and Asia Part of The Kantar Group/WPP 300+ Full- time Analysts We are part of one of the largest and most respected research agencies in India, with a team size of over 300 highly Clients across Asia Pac, Africa, UK, USA qualified analysts based at our operations centers in India. Member of ESOMAR & MRA ISO 9001:2008 and ISO 27001 Research in 65 Languages 6
  • 7. Abacus MA – a Snapshot Staff strength of 300, majority of whom are Masters in Statistics, Computer Applications, Operations Research and Engineering Tools/Software expertise – SPSS Dimensions, Quantum, Statistica, SPSS, Delphi, Our clients are in UK, USA, South Africa, Japan, France, Australia and most of Asia ISO 27001 ISO 9001 Certification for Moving to Six Certification for Processes & Quality Information Security Sigma level of delivery capability: automating tasks and eliminating non-value added work 7
  • 8. Agenda • Introduction • Marketing Research and Analytics Services • Advanced CRM Analytics Services • Technology and Research Software Services • Client Engagement/Methodology • Quality Metrics • Appendix Case Studies Testimonials Infrastructure and Security What makes us Different 8
  • 9. Market Research Solutions  Awareness/familiarity of your brand across various market segments Brand  Brand perception vis-à-vis competitor brands in the market Management  Performance on what parameters drive your brand’s perceptions?  Current positioning of your brand in the target segment’s mind Determine right price for various types of product types Pricing Research Determine overall price/value and specific price point sensitivities Determine sensitivities to changes in product, pack size, price or distribution  Determine the perceived attractiveness of the product/service for the target segment New Product/  Determine the ideal price and optimal design for the product/service Concept Testing  Identify possible matches/mismatches between unmet needs and new features  Predict off-take rates of alternative price-feature configurations  Are users aware of the full functionality of your product? Usage & Attitude  What is the usage pattern of different features of your product? Measurement  Which product features are the most difficult to use?  Are customers using your product over multiple locations? 9
  • 10. Market Research Solutions- Cont…  Evaluate overall effectiveness of your ad campaigns Advertising  Measure positive influences of the campaign on awareness, perception, intention to use Effectiveness  Evaluate effectiveness of your ad campaign in communicating intended message  Identify the best medium for advertising  Prioritize areas of product/service improvement Customer  Segment customers on the basis of their satisfaction and loyalty Satisfaction  Incorporate customer satisfaction results into your marketing/communications strategy  Influence customer behavior in-line with your strategic objectives  Measure satisfaction and derive action-points to improve employee retention Employee  Identify factors that employees consider when evaluating their experience with your firm Satisfaction  Determine satisfaction on each of these factors  Segment your employees to deliver focused training and implement retention programs  Measure impact of event association on the customers’ image of your brand Event Effectiveness  Assess impact of your association on industry analysts and competitors  Evaluate the success of the event in communicating your intended message  Measure impact on likelihood of purchase or recommendation 10
  • 11. Market Research Services Research & Analytics Value Chain Survey Design and Primary Data Processing and Analytics Reporting Research • Online & CATI survey scripting • PowerPoint templates • Uniform processes and standard • Programming & non-English software platforms • Charting & Graphs language overlays • Data entry, data cleansing & coding • Commenting and Data insights • Quota management, project • Topline, Preliminary and Final • Advanced statistical analysis Reports with executive summary, management and study completion support • Modeling advanced analysis, conclusions and recommendations • Data mining • Global online & CATI data collection • Dashboards • Predictive analytics • Best in class F2F, CLT’s, mall • Decision trees intercept & qualitative interviews in India • Simulation techniques • Clustering • Language capabilities in more than Tools: E-Tabs Enterprise, VB.net 65 languages across continents based online apps Tools: FoxPro, Quantum, Pascal, Tools: Dimensions, In- house Quanvert, SPSS, Espri, SPSS, applications, 4 CATI centers with Statistica, Dataminer 150 interviewers 11
  • 12. Programming for a Healthcare Research Agency A leading global market research agency, specializing in healthcare and headquartered in Europe Project Description Abacus MA Deliverables 12 Countries, 8 Languages Customization of the questionnaire for online research TG: Surgeons and General Physicians Designing the layout of the interface 2 Screener Sections, 4 General Sections Programming the online survey in English Programming in SPSS Dimensions Translating the online survey into eight languages Hosting the survey and monitoring the fieldwork Real time reporting on data collected during fieldwork Data validation and delivery of clean data 12
  • 13. Primary Research for a Leading Commercial Bank Online Data Collection for a leading commercial bank based in China and Japan Project Description Abacus MA Deliverables Formulate go to market strategies Finalize the recruitment and survey questionnaire TG: Retail banking customers 1,500 surveys to be completed across China and Japan N=1500, Japan and China 3D Quota with multiple skip patterns Programming in SPSS Dimensions Voice based recruitment and phone/Web completion Questionnaire translation and localization Programming, hosting and management of Web survey Survey Coding/Design of data reporting files in SPSS Real time reporting on data collected during fieldwork Final presentation with study findings Efficient and effective management of the entire program involving secondary research, questionnaire design, sample allocation, recruitment, surveys and reporting/presentation with recommendations/findings Met the stringent timeline of 14 weeks of the client Multi channel-recruitment by phone, and survey completion on 13
  • 14. Advanced Survey Analytics • Z-Test • Multiple Regression Analysis • T-Test • Discriminant Analysis • ANOVA • Logistic Regression • Chi-Square Test • Conjoint Analysis • Canonical Correlation Analysis • Path Analysis Hypotheses Dependence Testing Techniques Data Mining Interdependence Techniques Techniques • Cluster analysis • Decision Trees/Segmentation • Multidimensional Scaling • MARSpline • Correspondence Analysis • Market Basket Analysis • Factor Analysis 14
  • 15. Churn Prediction for a Telecom Client Gather customer Run Various requirements including Descriptive Using Data Mining Evaluate results churn definition, Analyses and Techniques, Build and select the variable information transform Models best models etc variables Data Mining Techniques Outputs- Best Result Lift Values and Graphical Pane Descriptive Analysis Lift Chart - Lift value Cumulative; Category: 1 Analysis sample;Number of trees: 1377 Lift Chart - Lift value Cumulative; Category: 1 Test set sample;Number of trees: 1377 4.0 3.0 3.8 2.9 2.8 3.6 Boosting Trees 3.4 3.2 2.7 2.6 2.5 2.4 3.0 2.3 2.8 2.2 Random Forests 2.6 2.4 2.1 2.0 1.9 2.2 1.8 Lift value Lift value 2.0 1.7 1.8 1.6 Support Vector Machine 1.6 1.4 1.5 1.4 1.3 1.2 1.2 1.0 1.1 1.0 0.8 0.9 Baseline 0 10 20 30 40 50 60 70 80 90 100 110 Baseline Detailed Steps Model 0 10 20 30 40 50 60 70 80 90 100 110 Model Percentile Percentile Data selection Data transformation Binning and Sampling Use of modeling technique Results using Lift Charts 15
  • 16. Segmentation for a Telecom Client Objectives of the Study Methodology Identify rules for needs based segmentation at macro level Create Segments Test the goodness of fit of this sample for the entire user base of Client Identify Key Drivers Replicate segments across the user database Identify Most Important Variables Gain customer insights for better campaign management Run Cluster Algorithms Run Cluster Algorithms multiple times Statistical Techniques K-Means Clustering Graph of means for c ontinuous variables EM Clustering Num ber of c lus ters : 4 0.5 Random Forests 0.4 Boosting Trees Normalized means 0.3 0.2 0.1 Clus ter 1 Clus ter 2 0.0 Clus ter 3 S MS Inc oming Calls S TD Clus ter 4 Outgoing Calls Roaming 16
  • 17. Path Analysis A Model relating customer satisfaction to real business out-comes Network Quality .41 .51 .16 Overall Quality of Customer Care Experience service .11 .58 Recharge experience Value for Money .69 .87 .69 Intention to Continue Tariff plan .69 .91 .10 .45 Cost Accuracy of balance reduction 17
  • 18. Agenda • Introduction • Marketing Research and Analytics Services • Advanced CRM Analytics Services • Technology and Research Software Services • Client Engagement/Methodology • Quality Metrics • Appendix Case Studies Testimonials Infrastructure and Security What makes us Different 18
  • 19. Advanced Analytics Solutions Core Objectives Analytics Solutions Behavioral Segmentation Customer behavior analysis Demographic Segmentation Psychographic Segmentation Acquire New Customers Customer Acquisition Response Modeling Improve Efficiency of Acquisition Offer Testing Campaigns Increase Wallet-Share Grow Customers Modeling in existing customers Improve Efficiency of Cross-Sell / Cross-sell/up-sell model Up-sell Campaigns Marketing Effectiveness Understand Effect of Different Market Mix Modeling Retain Existing Marketing Drivers Customers Customer Retention Churn modeling Reduce Customer Attrition Survival Analysis Special tools used by the team :  Random Forests  Support vector machine  Multivariate Adaptive Regression Splines (MARS)  Boosted Trees  Memory based reasoning 19
  • 20. Data Analytics Methodology & Processes (CRISP) Abacus follows the industry accepted CRISP methodology Business Data Data Analysis & Reporting & objectives Evaluation study preparation modeling deployment • Evaluate • Identify data • Standard • Select • Compare • Deployment business needs operating modeling with desired planning objectives procedures technique outcomes • Map data on data • Resource • Decide on needs to • Build model • Evaluate allocation the planning sources • Data results horizon cleaning • Generate • Periodic • Identify data test design • Review & screening & • Determine gaps & • Data qc for revisit model scrutiny of data mining mismatch missing • Test run on model goals fields, sample data • Client • Evaluate values, feedback and • Reporting as data sources mismatch • Assess domain based on model application client • Suggest data • Transition to requirements sources standard templates • Explore data type and • Data quantity formatting 20
  • 21. Consumer Panel Analytics Market Market Mix Structure Modeling • Identify the most • Likely to buy • Impact of profitable • Identify the which brand Advertising segment interaction with Promotion, other categories Distribution Price Usage Predicting Segmentation Market Basket Cox Regression Pooled Fixed or Cluster Analysis Analysis random effects model 21
  • 22. Agenda • Introduction • Marketing Research and Analytics Services • Advanced CRM Analytics Services • Technology and Research Software Services • Client Engagement/Methodology • Quality Metrics • Appendix Case Studies Testimonials Infrastructure and Security What makes us Different 22
  • 23. Technology and Research Software Solutions • Customized Graphics tool • Template Designing • Better Insights • Query Filtering • Excel Based • Migrating daily data • Flash Based • User friendly GUI • Windows Based • Web Based interface • Web Based Dashboards OLAPs Automated Marketing Tools •Choice based conjoint tool •Media measurement tools •Pricing Research tools 23
  • 25. Normative Database Merged Data for Different CRA Studies conducted for Multiple industries Data Uploading Module Data Analyzing Module Master File Creation Data of Multiple Studies Unique Code for each Variable User can select specific data type Restructuring for Data Merging Scores are averages of studies Specific Format using Visual Basic Multiple data at one place 25
  • 26. Using Data Fusion to measure ROI  Two way fusion of housewife TV viewership from TAM and her purchases of FMCG from the Household purchase panel  Helps in identifying the Return on Investment of advertising  User friendly software - IMRB MagicBox to analyze advertising impact on purchases 26
  • 27. Agenda • Introduction • Marketing Research and Analytics Services • Advanced CRM Analytics Services • Technology and Research Software Services • Client Engagement/Methodology • Quality Metrics • Appendix Case Studies Testimonials Infrastructure and Security What makes us Different 27
  • 28. Client Engagement Ad-hoc and On Demand Client Engagement Blended Model Dedicated Research Center Features and Benefits • One off projects to handle client peak loads • Quick project initiation and turn around time • Dedicated project managers and single point of contact • Scale up depending on client requirements 28
  • 29. Agenda • Introduction • Marketing Research and Analytics Services • Advanced CRM Analytics Services • Technology and Research Software Services • Client Engagement/Methodology • Quality Metrics • Appendix Case Studies Testimonials Infrastructure and Security What makes us Different 29
  • 30. Quality Metrics Customized Quality Metrics for each client Separate ‘Quality Certification & Audit’ cell Member of ESOMAR and MRA ISO 9001 Certification for ISO 9001:2008 and ISO 27001 certified Processes & Quality Quality Norms Exhaustive Training Program for each Analyst Regular updated training modules Training Live Monitoring by Quality Team members One to One feedback with Analysts Individual exhaustive development plans Feedback 30
  • 31. Agenda • Introduction • Marketing Research and Analytics Services • Advanced CRM Analytics Services • Technology and Research Software Services • Client Engagement/Methodology • Quality Metrics • Appendix Testimonials Infrastructure and Security What makes us Different 31
  • 32. Client Testimonials “The research team does not act on the research brief as is, they think of the problem in depth and challenge the thinking, and usually come up with innovative methodologies that best achieve the objectives” “Superb planning and teamwork, ensuring high quality data collection in almost clockwork fashion. I am absolutely delighted by the business relevance of the findings in helping us take an important business decision” “IMRB showed a high degree of professionalism, rigour and discipline. An excellent level of Client servicing and need fulfillment, pro-activeness and analytical focus” “Thank you for your quick and valuable inputs during the study. You have proved yet again that we can depend on you” “As a team they produce thoughtful proposals, excellent fieldwork and presentations. They are constantly involved in the work. They feel like a version of our own office” 32
  • 33. Infrastructure and Security Infrastructure Security • Delivery centers in New Delhi, Mumbai, • General security/ Physical security/ Employees/ Bangalore, Pune and Kolkata Third-parties • Secure cabinets for data storage • Technology and network infrastructure to • Data kept with only designated individuals ensure data secure environments • Data is processed only in a physically secure area • Client connectivity infrastructure includes VPN • Machines/ files are password protected (Virtual Private Network) links between IMRB • Employee Training on Information Security and Client networks every 3 months • Manual data is shredded when deemed not • Constantly enhance our infrastructure based required on our own and Client's business requirements • Personnel required to sign appropriate non- ISO 27001 disclosure agreements Certification for • Restricted Swipe Card access to production Information Security areas • Writeable media banned from production areas 33
  • 34. So what makes us DIFFERENT?? Loyal Client relationships WHAT’S DIFFERENT? Multi-country research capability 34
  • 35. Thank You For business queries please contact: Surya Kiran (Manager - Business Development) Email: surya.kiran@imrbint.com Office Line: +91 11 40893238 Mobile: +91-9873336087 Or Bart Zehren Email: bz@your-research-resource.com Phone: +1 847-864-7159 35