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Campaign Pack for Retail




                           1
Introduction
                      Campaign pack is a collection of solutions created for Retail Marketing
                      Managers to help them develop, execute, track and analyze campaigns
                                                 more effectively

           What is
           Campaig
            n Pack

                            Campaign pack contains solution for all the phases of campaigning
                             right from analytical models based campaign list generation for
               Why use      different customer segments to automated execution and tracking
Campaign       Campaig            to analytics driven insight generation on post-campaign
  Pack          n Pack
                                                        performance



                       • Its strength lies in highly simplified result delivery mechanism supported
           Benefits
                         by a very robust data and analytics engine
                       • The modeling factory platform allows the solution system to churn a
                         large number of models in very short time making it highly scalable
                       • It hides the marketing manager from all the data complexities and
                         straightway brings to him the target customer lists and insights through
                         simple automated reports (completely integrated with MS-Excel) 2
Campaign Pack: Components
                                                                              Campaign Manager

    Campaign List Generator                                               Campaign Manager is a dynamic
                                                                          solution, enabling enterprise-wide
                                                                                integration of customer
   This is a propensity modeling
                                                                           management strategies through
    solution. It helps to identify
                                                                         the power of seamless event-driven
     potential responders for a
                                                                                       marketing
         particular campaign

                                                                          It has large scale databases and
Generates probability scorecards for
                                                                         employs multiple communications
 all customers and then selects the
                                                                           and customer contact channels,
            top deciles
                                                                          including direct mail, email, SMS,
                                          Campaign Analyzer
                                                                           point of sale, call centre, branch
                                                                                 and dealer, as well as
                                       Analyzes the post-campaign
                                                                                       internet.
                                          performance. Generates
                                          comparison snapshots of
                                        performance across different
                                     channels, customer segments, time
                                               and geography

                                      Generates automated reports
                                      completely integrated with MS-
                                                   Excel
                                                                                                            3
Solution Framework

 Customer
                                          Campaign
Demographic
                                            Lists
   Data
                              Campaign
                 Data Audit      List
                              Generator
Transaction                               Automated
                                           Reports
  History
                    Data      Campaign
                 Enrichment   Manager
                                           Insights
 Campaign          Derived
                              Campaign
   Data           Variables
                               Analyzer
                  Addition

                                           MS-Excel
                                          Integration
Loyalty Data

                                                  4
Campaign List Generator
    It’s a propensity modeling solution. It generates the probability of customers to respond
                    and identifies the parameters which influences response.




                    Defining
                                                                 List of
                     target
                                               Probability    variables or
 Dividing the       variable
                                                scores of                                  Scoring of
                                                             characteristic
                                                                                                         Propensity
  data into        (customer
                                   Model                                        Model
                                                  each                                       new
                                                                s which
modeling set                                                                                            scorecard for
                      who
                                Development                                   validation   customer
                                              customer to      define the
                 responded to
     and                                                                                                the campaign
                                                             probability of                  base
                                               respond to
                     similar
validation set
                                              the festival    a customer
                  campaign in
                                                              to respond
                      past)




         ‘Modeling Factory’ platform helps to generate the
           models for every campaign in very short time                                                        5
Campaign Manager
It is a highly efficient, modular and flexible application that integrates all of the data and services
necessary to develop, execute and track campaigns. It combines fast access to constantly
enriched detailed customer level data and high volume transactions, consolidating customer insight
and interactions across all channels of communication.



 • Allows deliver simple to complex multi-stage, multi-wave campaigns
 • Integrates easily with all of all kinds of databases and flat files
 • Rapid implementation and integration to existing business systems, leveraging existing
   investments in IT
 • Support for all marketing campaigns including above and below the line
 • Allows local marketing teams to subscribe to central marketing campaigns and deliver them
   to local audiences
 • Storage of campaign creative and documentation
 • Campaign rules, for example, next best action, can be easily defined and delivered through all
   marketing channels
 • Configurable reports on campaign effectiveness, budget, costs and marketing ROI
 • Automatically refreshed reports, scorecards, indexes and campaign lists
 • Complete integration with MS-Excel
                                                                                                     6
Campaign Analyzer
                                Insights generated

             Performance comparison of different customer segment
               Comparison of sales with previous year performance
       Comparison of sales and number of visitors across different channels
         Distribution of purchase value bands before and after campaign
Performance comparison of different stores in terms of sales and number of visitors
                 Distribution of average ticket size before & after
                Geography-wise comparison (zone-wise, city-wise)
                       Sale distribution of items under offer
                      Channel-wise performance comparison
            Email category comparison for response rate and click rate

                                                                                      7
Campaign Analyzer: Snapshots
     Sales and number of visitors per day




                                            8
Campaign Analyzer: Snapshots
            Store wise average ticket size and growth


4,000                                                                               20%

                                                                                    15%
3,500
                                                                                    10%
3,000
                                                                                    5%
2,500
                                                                                    0%

2,000                                                                               -5%

                                                                                    -10%
1,500
                                                                                    -15%
1,000
                                                                                    -20%
 500
                                                                                    -25%

   -                                                                                -30%




                                              Ticket size   Growth in ticket size




                                                                                           9
Campaign Analyzer: Snapshots
                      Store wise Comparison – Number of visitors and sales

            30,000                                                                                           120




                                                                                                                       Hundreds
Thousands




            25,000                                                                                           100




            20,000                                                                                           80




            15,000                                                                                           60




            10,000                                                                                           40




             5,000                                                                                           20




                0                                                                                            -




                             2007 Sales   2008 Sales   2007 -Number of customers   2008 -Number of customers visited
                                                                                                                   10
Campaign Analyzer: Snapshots
                                                                                            Lag effect of e-mailer sent

450                                                                                                                                                                                                                                                                                         3,500

400
                                                                                                                                                                                                                                                                                            3,000

350
                                                                                                                                                                                                                                                                                            2,500
300

                                                                                                                                                                                                                                                                                            2,000
250

200                                                                                                                                                                                                                                                                                         1,500

150
                                                                                                                                                                                                                                                                                            1,000
100
                                                                                                                                                                                                                                                                                            500
 50

  0                                                                                                                                                                                                                                                                                         -




                                                                                                                                                                                                                                                                            1-Nov
                                                                                                                                                                                                                                                                                    2-Nov
      2-Oct
              3-Oct
                      4-Oct
                              5-Oct
                                      6-Oct
                                              7-Oct
                                                      8-Oct
                                                              9-Oct
                                                                      10-Oct
                                                                               11-Oct
                                                                                        12-Oct
                                                                                                 13-Oct
                                                                                                          14-Oct
                                                                                                                   15-Oct
                                                                                                                            16-Oct
                                                                                                                                     17-Oct
                                                                                                                                              18-Oct
                                                                                                                                                       19-Oct
                                                                                                                                                                20-Oct
                                                                                                                                                                         21-Oct
                                                                                                                                                                                  22-Oct
                                                                                                                                                                                           23-Oct
                                                                                                                                                                                                    24-Oct
                                                                                                                                                                                                             25-Oct
                                                                                                                                                                                                                      26-Oct
                                                                                                                                                                                                                               27-Oct
                                                                                                                                                                                                                                        28-Oct
                                                                                                                                                                                                                                                 29-Oct
                                                                                                                                                                                                                                                          30-Oct
                                                                                                                                                                                                                                                                   31-Oct
                                                                                                                                                                    Number of customers visited                                                                        Ticket size
                  Note:                                                line indicates Weekend


                                                                                                                                                                                                                                                                                                11
About Cequity
CEQUITY is a “marketing automation & analytics” firm combining tier 1 advisory skills
  with a highly qualified and world-leading analytics engine delivered in an Onsite-
                                   Offshore model



We help organizations
• Manage data present across different data silos
• Reduce dependency on IT and give more power in the hands of marketing managers to be
  able to perform train-of-thought analysis and generate insights from their data
• Build analytical models and scorecards on their data to identify right target segments for
  campaigning
• Develop , execute and manage campaigns to show ROI generated



 We bring our strong domain, data and analytical expertise through specialized solutions to our
                  highly satisfied and rapidly growing client list spread across
                   Retail, Banking, CPG, Telecom, Travel, DTH and Insurance.



                                                                                                  12
INDIA                                        USA
                                                       Worldwide OfficesOFFICE: 626, GROVE
                                               1ST
                    MUMBAI OFFICE: 105-106,          FLOOR,      CHICAGO
                    STREET, ANAND ESTATE, 189-A, SANE GURUJI          EVANTSON, IL 60201
                    MARG, MAHALAXMI, MUMBAI – 400 011
                    PHONE: +91 22 43453824
                    F: +91 22 43453840




                                            www.cequitysolutions.com
                                            info@cequitysolutions.com
For the latest thinking in Analytics & insights on Customer management, check out our blog at http://blog.cequitysolutions.com/
                                                                                                                                  13

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Campaign pack for retail marketing

  • 1. Campaign Pack for Retail 1
  • 2. Introduction Campaign pack is a collection of solutions created for Retail Marketing Managers to help them develop, execute, track and analyze campaigns more effectively What is Campaig n Pack Campaign pack contains solution for all the phases of campaigning right from analytical models based campaign list generation for Why use different customer segments to automated execution and tracking Campaign Campaig to analytics driven insight generation on post-campaign Pack n Pack performance • Its strength lies in highly simplified result delivery mechanism supported Benefits by a very robust data and analytics engine • The modeling factory platform allows the solution system to churn a large number of models in very short time making it highly scalable • It hides the marketing manager from all the data complexities and straightway brings to him the target customer lists and insights through simple automated reports (completely integrated with MS-Excel) 2
  • 3. Campaign Pack: Components Campaign Manager Campaign List Generator Campaign Manager is a dynamic solution, enabling enterprise-wide integration of customer This is a propensity modeling management strategies through solution. It helps to identify the power of seamless event-driven potential responders for a marketing particular campaign It has large scale databases and Generates probability scorecards for employs multiple communications all customers and then selects the and customer contact channels, top deciles including direct mail, email, SMS, Campaign Analyzer point of sale, call centre, branch and dealer, as well as Analyzes the post-campaign internet. performance. Generates comparison snapshots of performance across different channels, customer segments, time and geography Generates automated reports completely integrated with MS- Excel 3
  • 4. Solution Framework Customer Campaign Demographic Lists Data Campaign Data Audit List Generator Transaction Automated Reports History Data Campaign Enrichment Manager Insights Campaign Derived Campaign Data Variables Analyzer Addition MS-Excel Integration Loyalty Data 4
  • 5. Campaign List Generator It’s a propensity modeling solution. It generates the probability of customers to respond and identifies the parameters which influences response. Defining List of target Probability variables or Dividing the variable scores of Scoring of characteristic Propensity data into (customer Model Model each new s which modeling set scorecard for who Development validation customer customer to define the responded to and the campaign probability of base respond to similar validation set the festival a customer campaign in to respond past) ‘Modeling Factory’ platform helps to generate the models for every campaign in very short time 5
  • 6. Campaign Manager It is a highly efficient, modular and flexible application that integrates all of the data and services necessary to develop, execute and track campaigns. It combines fast access to constantly enriched detailed customer level data and high volume transactions, consolidating customer insight and interactions across all channels of communication. • Allows deliver simple to complex multi-stage, multi-wave campaigns • Integrates easily with all of all kinds of databases and flat files • Rapid implementation and integration to existing business systems, leveraging existing investments in IT • Support for all marketing campaigns including above and below the line • Allows local marketing teams to subscribe to central marketing campaigns and deliver them to local audiences • Storage of campaign creative and documentation • Campaign rules, for example, next best action, can be easily defined and delivered through all marketing channels • Configurable reports on campaign effectiveness, budget, costs and marketing ROI • Automatically refreshed reports, scorecards, indexes and campaign lists • Complete integration with MS-Excel 6
  • 7. Campaign Analyzer Insights generated Performance comparison of different customer segment Comparison of sales with previous year performance Comparison of sales and number of visitors across different channels Distribution of purchase value bands before and after campaign Performance comparison of different stores in terms of sales and number of visitors Distribution of average ticket size before & after Geography-wise comparison (zone-wise, city-wise) Sale distribution of items under offer Channel-wise performance comparison Email category comparison for response rate and click rate 7
  • 8. Campaign Analyzer: Snapshots Sales and number of visitors per day 8
  • 9. Campaign Analyzer: Snapshots Store wise average ticket size and growth 4,000 20% 15% 3,500 10% 3,000 5% 2,500 0% 2,000 -5% -10% 1,500 -15% 1,000 -20% 500 -25% - -30% Ticket size Growth in ticket size 9
  • 10. Campaign Analyzer: Snapshots Store wise Comparison – Number of visitors and sales 30,000 120 Hundreds Thousands 25,000 100 20,000 80 15,000 60 10,000 40 5,000 20 0 - 2007 Sales 2008 Sales 2007 -Number of customers 2008 -Number of customers visited 10
  • 11. Campaign Analyzer: Snapshots Lag effect of e-mailer sent 450 3,500 400 3,000 350 2,500 300 2,000 250 200 1,500 150 1,000 100 500 50 0 - 1-Nov 2-Nov 2-Oct 3-Oct 4-Oct 5-Oct 6-Oct 7-Oct 8-Oct 9-Oct 10-Oct 11-Oct 12-Oct 13-Oct 14-Oct 15-Oct 16-Oct 17-Oct 18-Oct 19-Oct 20-Oct 21-Oct 22-Oct 23-Oct 24-Oct 25-Oct 26-Oct 27-Oct 28-Oct 29-Oct 30-Oct 31-Oct Number of customers visited Ticket size Note: line indicates Weekend 11
  • 12. About Cequity CEQUITY is a “marketing automation & analytics” firm combining tier 1 advisory skills with a highly qualified and world-leading analytics engine delivered in an Onsite- Offshore model We help organizations • Manage data present across different data silos • Reduce dependency on IT and give more power in the hands of marketing managers to be able to perform train-of-thought analysis and generate insights from their data • Build analytical models and scorecards on their data to identify right target segments for campaigning • Develop , execute and manage campaigns to show ROI generated We bring our strong domain, data and analytical expertise through specialized solutions to our highly satisfied and rapidly growing client list spread across Retail, Banking, CPG, Telecom, Travel, DTH and Insurance. 12
  • 13. INDIA USA Worldwide OfficesOFFICE: 626, GROVE 1ST MUMBAI OFFICE: 105-106, FLOOR, CHICAGO STREET, ANAND ESTATE, 189-A, SANE GURUJI EVANTSON, IL 60201 MARG, MAHALAXMI, MUMBAI – 400 011 PHONE: +91 22 43453824 F: +91 22 43453840 www.cequitysolutions.com info@cequitysolutions.com For the latest thinking in Analytics & insights on Customer management, check out our blog at http://blog.cequitysolutions.com/ 13