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#bigdataretail




   high-speed retail
   analytics
   courtesy of a new approach to big
   data     Amos Schwartzfarb
            VP, Customer Development
                                       Dhruv Bansal
                                       Chief Science Officer,
                                                                Tim Gasper
                                                                Product Manager
            BlackLocus, Inc.           Co-founder               Infochimps, Inc.
                                       Infochimps, Inc.
#bigdataretail




                 poll
#bigdataretail




                    1

                 volume

                 velocity

                 variety
#bigdataretail




    retail + big data
    “Multichannel” has given way to “omnichannel” in
    the retail world, with shoppers driving the charge
    with their new devices and retailers rushing to
    keep up with them.

    - CMO Magazine
    http://www.cmo.com/mobile/technology-becoming-easy-sell-retail-marketers
#bigdataretail




 http://practicalanalytics.wordpress.com/2012/01/19/omni-channel-retail-analytics-a-big-data-use-case/
#bigdataretail




 http://practicalanalytics.wordpress.com/2012/01/19/omni-channel-retail-analytics-a-big-data-use-case/
#bigdataretail
#bigdataretail




            staff

       expertise

            time
We collect and match massive amounts of
competitive price and assortment data,
then make it actionable for our retail
customers

 >>   “I’ve never seen a partner’s product go viral inside our
      organization as fast as BlackLocus. We had our biggest
      quarter ever, the quarter following our initial engagement
      with BlackLocus”
      – Chairman, IR Top 75 Retailer
#bigdataretail




                 poll
the problem we solve for
 retailers
 Consumers have instant and
 complete price and                                           Seasonality

 assortment transparency
                                                                                       Social
 Consumers have all the tools to    Competitor Pricing
                                                                                     Sentiment
 price and buy instantaneously


 There is too much data for                               PRICE TO WIN
 retailers to analyze              Promotions
                                                                                          Inventory
                                    / Reviews
 Retailers have limited tools to
 set the:
• Right price at the
• Right time to the                                                         Brand
                                                 Assortment
                                                                            Equity
• Right customer
the problem we solve
MULTI-SOURCE, BIG DATA ANALYTICS TO OPTIMIZE PRICE AND
ASSORTMENT

“Which of my products             “What are the margin,         “How do I utilize every
are under- or over-priced         conversion and profit         relevant data point to
relative to my                    implications from             optimize price and
competition?”                     dynamic pricing?”             assortment?”

Real-time competitive             Integrated platform for       Big, multi-source data
Pricing intelligence              changing price and tracking   analytics to optimize price
                                  conversions/ profit
           Today                             2012                          2013



                                                                  There is so much
                                      When I change price
I have no scalable way to track                                   available data, how
                                      daily, weekly or
competitive pricing at the SKU                                    do I determine its
                                      monthly is it
level.                                                            impact on price and
                                      profitable?
                                                                  assortment?
our technology and approach
DATA SCIENCE AND MACHINE LEARNING: WHY DO YOU CARE?



                                          Math and
More than just acquiring                  Statistics
data

                               Insight
More than just analyzing         and                   Machine
data                          Analysis                 Learning


Deep insight into what
data actually means
                                          Software
                                         Engineering       Data Science
Ability to scale and adjust
quickly through
automation.
our technology and approach
BLACK LOCUS DATA PIPELINE


          Collect    Extract     Ingest     Learn     Analyze    Deliver



 Collect – collect semi-structured and structured data from different
  sources
 Extract – clean and transform semi-structured data into structured
 Ingest – store and make the data available via search and/or query
 Learn – iterative machine learning to identify product matches
 Analyze – intelligence, metrics, and verification
 Deliver – integration into the platform
#bigdataretail




    The Platform of Big Data
    Technology




                                 +
                               The “Right Product, Right Price, Right Time”
                               Big Data Application
#bigdataretail




     big data infrastructure made simple

     some of our customers   our partners
#bigdataretail




                 poll
#bigdataretail



                                                  Analytics
                                                Applications &
                                                 Workflows

                    Analytics
                 Technology &
                 Big Data Platform
                 Infrastructure
  Analytics
Applications &
 Workflows
                                 Price and Assortment
                                      Intelligence
#bigdataretail

           Retail Big Data Architecture
           BI Systems
Demo-                           collect & analyze ask questions,
graphics
                    Foot Traffic real-time data     build apps
ERP
              CRM

           POS
            Social Media


RFID
                    Mobile                      predictive
Clickstream
                  Ratings &                     analytics
                  Reviews
#bigdataretail




                                 provide customers
      Prices from
                                    with pricing
      Across the    collect data    information
      Web




      Customer
      Data
                                   analyze
#bigdataretail


         benefits we provide retailers
   we are
   •   an end-to-end solution
   •   a flexible big data foundation to build upon
   •   your outsourced big data partner

   we generate insights you need
   •   quickly
   •   without capital investment (cloud)
   •   without investing in new talent (managed)
   •   tailored for your business
#bigdataretail



                     learn more >>

         sales@infochimps.c            amos@blacklocus.co
         om                            m
         1-855-328-2386                415-505-7398

         Request a Demo:               Request a Demo:
         http://bigdata.infochimps.c   http://resources.blacklocus.co
         om/request-a-big-data-        m/requestyourdemo/
         platform-demo/

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[Webinar] High Speed Retail Analytics

  • 1. #bigdataretail high-speed retail analytics courtesy of a new approach to big data Amos Schwartzfarb VP, Customer Development Dhruv Bansal Chief Science Officer, Tim Gasper Product Manager BlackLocus, Inc. Co-founder Infochimps, Inc. Infochimps, Inc.
  • 3. #bigdataretail 1 volume velocity variety
  • 4. #bigdataretail retail + big data “Multichannel” has given way to “omnichannel” in the retail world, with shoppers driving the charge with their new devices and retailers rushing to keep up with them. - CMO Magazine http://www.cmo.com/mobile/technology-becoming-easy-sell-retail-marketers
  • 8. #bigdataretail staff expertise time
  • 9. We collect and match massive amounts of competitive price and assortment data, then make it actionable for our retail customers >> “I’ve never seen a partner’s product go viral inside our organization as fast as BlackLocus. We had our biggest quarter ever, the quarter following our initial engagement with BlackLocus” – Chairman, IR Top 75 Retailer
  • 11. the problem we solve for retailers Consumers have instant and complete price and Seasonality assortment transparency Social Consumers have all the tools to Competitor Pricing Sentiment price and buy instantaneously There is too much data for PRICE TO WIN retailers to analyze Promotions Inventory / Reviews Retailers have limited tools to set the: • Right price at the • Right time to the Brand Assortment Equity • Right customer
  • 12. the problem we solve MULTI-SOURCE, BIG DATA ANALYTICS TO OPTIMIZE PRICE AND ASSORTMENT “Which of my products “What are the margin, “How do I utilize every are under- or over-priced conversion and profit relevant data point to relative to my implications from optimize price and competition?” dynamic pricing?” assortment?” Real-time competitive Integrated platform for Big, multi-source data Pricing intelligence changing price and tracking analytics to optimize price conversions/ profit Today 2012 2013 There is so much When I change price I have no scalable way to track available data, how daily, weekly or competitive pricing at the SKU do I determine its monthly is it level. impact on price and profitable? assortment?
  • 13. our technology and approach DATA SCIENCE AND MACHINE LEARNING: WHY DO YOU CARE? Math and More than just acquiring Statistics data Insight More than just analyzing and Machine data Analysis Learning Deep insight into what data actually means Software Engineering Data Science Ability to scale and adjust quickly through automation.
  • 14. our technology and approach BLACK LOCUS DATA PIPELINE Collect Extract Ingest Learn Analyze Deliver  Collect – collect semi-structured and structured data from different sources  Extract – clean and transform semi-structured data into structured  Ingest – store and make the data available via search and/or query  Learn – iterative machine learning to identify product matches  Analyze – intelligence, metrics, and verification  Deliver – integration into the platform
  • 15. #bigdataretail The Platform of Big Data Technology + The “Right Product, Right Price, Right Time” Big Data Application
  • 16. #bigdataretail big data infrastructure made simple some of our customers our partners
  • 18. #bigdataretail Analytics Applications & Workflows Analytics Technology & Big Data Platform Infrastructure Analytics Applications & Workflows Price and Assortment Intelligence
  • 19. #bigdataretail Retail Big Data Architecture BI Systems Demo- collect & analyze ask questions, graphics Foot Traffic real-time data build apps ERP CRM POS Social Media RFID Mobile predictive Clickstream Ratings & analytics Reviews
  • 20. #bigdataretail provide customers Prices from with pricing Across the collect data information Web Customer Data analyze
  • 21. #bigdataretail benefits we provide retailers we are • an end-to-end solution • a flexible big data foundation to build upon • your outsourced big data partner we generate insights you need • quickly • without capital investment (cloud) • without investing in new talent (managed) • tailored for your business
  • 22. #bigdataretail learn more >> sales@infochimps.c amos@blacklocus.co om m 1-855-328-2386 415-505-7398 Request a Demo: Request a Demo: http://bigdata.infochimps.c http://resources.blacklocus.co om/request-a-big-data- m/requestyourdemo/ platform-demo/