Big Data and Competitive Intelligence
Finding Answers Outside the Firewall

 Presenters: Isai Shenker, VP of Product Management, Connotate
             Gina Cerami, VP of Marketing, Connotate

 Moderator: Christian Giaretta, VP of Sales Engineering, Connotate

 Date:       September 20, 2012
Presenters




         Isai Shenker                      Gina Cerami
  Vice President of Product Management   Vice President of Marketing
                Connotate                        Connotate
Today’s Discussion
• Competitive pricing: Insight from outside the firewall
   • Business case and operational challenges
   • Case study: Competitive pricing for online retail
   • Case study: Pricing optimization for specialty chemicals

• Customer sentiment: Digging into Deep Web
   • Sources of consumer sentiment
   • Process: Extracting consumer sentiment from YouTube
   • Case Study: Allergy medicine and consumer sentiment

• Manual versus automated approaches

• Q&A
Competitive Pricing
The Business Case



    Distributors and resellers prices


  15,000,000 prices
       Other competitor’s prices
Operational Challenges in Setting Prices

           Measuring the impact
            of pricing decisions

       Forecasting the impact of
       potential pricing decisions
                                      Getting
        Maintaining visibility into
                                      access to
         promotional profitability    robust,
              Getting access to       competitive
    robust competitive price data
                                      price data is a
  Making sure that stores change
    prices accurately and timely      big challenge
Keeping up with promotional deals     Retail Systems
 cut by buyers with manufacturers
                                      Research 2012
            Managing promotions       Benchmark Report
                across channels
Polling Question

Are you currently collecting competitive pricing data
from the Web?

   Yes – we are collecting pricing data from the Web

   No – we are not collecting pricing data from the Web
   but we have a project or plan to do this within the next
   6 months

   No – we have no plans to collect pricing data from
   the Web
Competitive Pricing:
Real-World Success Stories

Online Retailer of                             Specialized Retailer
                        National Store Chain   Goes Deep Web
New and Used Goods
• Checks 1M online      • Checks prices on     • Builds online
  prices per day to       3M items at            catalog by
  win business            national and local     going 3-7 layers
                          levels                 deep on direct mfrs’
                                                 Web sites for
                                                 product info



                      Automation is key to success
Competitive Pricing:
Real-World Success Stories

Online Retailer of                            Specialized Retailer
                       National Store Chain   Goes Deep Web
New and Used Goods


 LOWEST PRICE              OPTIMIZED          DOUBLED SIZE OF
                           MARGINS            ONLINE CATALOG




                     Automation is key to success
An Overview of the Automation Process

                                                         Connotate
                                                          Partners




                              {
                              {
             Collect Data                 Transform                  Deliver
Internal Sources    External Sources   • Structure               • Reports
• Database          • Social Media     • Classify                • Dashboards
• Market Basket     • Surface Web      • Prep for Analysis       • Workflow
• Inventory, etc.   • Hidden Web                                 • BI Plug-ins
                    •Secured Sites
Example: Pricing Flow Diagram
Price Optimization Case Study:
Sigma Aldrich
Sigma-Aldrich faced a “Big Data” challenge
• An overwhelming volume of pricing information on the Web




                           ?                     $
                                            Jeopardizing
    Manual              Inaccurate            a Sound
   Processes              Results              Pricing
                                              Strategy
Big Data and Competitive Intelligence
Results: Price Optimization Pays Off




            Increase revenue
                 2%- 4%
       $8.75M - $16B for Fortune 500 Company
Customer Sentiment
Customer Sentiment


  “The better and more quickly a company
  can measure customer sentiment,
  the sooner it can tell how well a product
  is likely to sell.”
                        – BusinessWeek, 2011
Customer Sentiment: Deep Web
A Fortune 50 consumer product goods company sought input
from social media on customer sentiment about a popular
class of products:
 • Twitter was easy to access via API but not useful; there was
   no in-depth discussion of features
 • Detailed product reviews existed on Amazon, Walmart, in
   microblogs and comments on YouTube videos
 • The firm wanted to access these sites and draw conclusions
   from this data to create a feedback loop for their continuous
   product design cycle
Differences in Web Sources
    Facebook
   Twitter, etc.
                                               D
                                               A
                                               T
Surface Web, Other                             A
   Social Media

                                               A
                             Processing
                                               N
    Deep Web                                   A
 (traverse links)
                                               L
                                               Y
                                               S
    Password-                                  I
  Protected Sites
                                               S
 Data Sources                Analysis


                                          18
Automation Opens Access to Deep Web and Secured Sites

   Facebook
  Twitter, etc.
                                                  D
                                                  A
                                                  T
  Surface Web,                                    A
  blogs, forums

                                                  A
                                     Processing
                                                  N
    Deep Web                                      A
 (traverse links)
                                                  L
                                                  Y
                                                  S
   Password                                       I
 Protected Sites
                                                  S
                                      Analysis
Data Sources


                                                        19
Obtaining Customer Sentiment from YouTube

      Manually search YouTube for <“product name”> <“review”>




            Use the Connotate automation package to find
          <“product name”> <“review”> in posted comments



                     Use Connotate to follow links
                 to other sites with <“product name”>




         Feed input into analytical engine to reveal sentiment


            Graphical User Interface/Presentation of Insights
Refining Data for Business Insights: Customer
Sentiment
A major pharmaceutical company wants to understand the
competitive landscape for allergy medications.

  • Decided to focus on data available online
  • Used Connotate to collect product information, prices and

    4,700 customer reviews on 465 products
  • Analyzed data and found insights using Luminoso text analytics

  • Time from idea to initial findings:   6 hours
Customer Sentiment Around Allergy Drug Cost
as Displayed by Sentiment Analysis Tool
Customer Sentiment Around the Word
“Generic”




         Customer Sentiment Around Allergy Drug
         Cost
         as Displayed by Sentiment Analysis Tool
The Value of the Data is in the Delivery
Another Look at the Automation Process
                                                             Your internal BI tools or
             Connotate                    Connotate           Connotate partners
             Collect Data                  Transform                Deliver
                                                                      • Reports
Internal Sources    External Sources
                                       • Classify                     • Dashboards
• Database          • Social Media
                                       • Structure                    • Workflow
• Market Basket     • Surface Web
                                       • Prep for Analysis            • BI Plug-ins
• Inventory, etc.   • Hidden Web
                    •Secured Sites




    Connotate provides precise quality data, structured
    for delivery to your analysis and presentation tools.

    Connotate maximizes the value of your investment
    in business intelligence, text analytics and semantic
    analysis tools.

                                                                              Excel
Polling Question: Customer Sentiment

Are you currently collecting customer sentiment data
from the Web?

   Yes – we are collecting customer sentiment data
   from the Web

   No – we are not collecting customer sentiment data
   from the Web but we have a project or plan to do this
   within the next 6 months

   No – we have no plans to collect customer sentiment
   from the Web
Manual versus Automated Approaches

 Your Data Needs                           To Automate or Not?

                                           ? May want to consider
 Complex product-matching tasks
                                             crowd sourcing

 Small amount of data, needed a few        ? A manual approach may
 times per year                              suffice

 Specific external data (under $5K/year)   ? Purchase from 3rd party

  High volume data monitoring               Automate

 Variety of sources                         Automate

 Frequent updates and/or monitoring         Automate

 Need for data post-processing              Automate
Vast Resources of Competitive Intelligence are
Outside the Firewall

Automation is                       Price
the key to                          optimization
extracting
precise quality                     Product design
data
                                    Deliver new
                                    online services
Automation is
needed when
                                    Dynamically
the initiative is
                                    adjust product
strategic
                                    positioning
Selected Connotate Partners for
Competitive Intelligence
                        Text and Sentiment Analysis




                                                         Data Integration and
 Pricing Intelligence          CrowdSourcing
                                                               Business
                                                             Intelligence




                        Special thanks to Nikki Baird,
                          Retail Systems Research,
                           www.rsrresearch.com
Q&A

Connotate will email a link to this presentation as well as a
copy of the slides to you within 2 business days.


If you have an immediate need and would like us to contact
you about a forthcoming project, please check the appropriate
box in the last polling question or call us at 732-296-8844.


You may also visit www.connotate.com for more information.
Thank You

If you have an immediate need and would like us to contact
you about a forthcoming project, please check the appropriate
box in the last polling question or call us at 732-296-8844.


For more information, visit www.connotate.com.

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Big Data and Competitive Intelligence

  • 1. Big Data and Competitive Intelligence Finding Answers Outside the Firewall Presenters: Isai Shenker, VP of Product Management, Connotate Gina Cerami, VP of Marketing, Connotate Moderator: Christian Giaretta, VP of Sales Engineering, Connotate Date: September 20, 2012
  • 2. Presenters Isai Shenker Gina Cerami Vice President of Product Management Vice President of Marketing Connotate Connotate
  • 3. Today’s Discussion • Competitive pricing: Insight from outside the firewall • Business case and operational challenges • Case study: Competitive pricing for online retail • Case study: Pricing optimization for specialty chemicals • Customer sentiment: Digging into Deep Web • Sources of consumer sentiment • Process: Extracting consumer sentiment from YouTube • Case Study: Allergy medicine and consumer sentiment • Manual versus automated approaches • Q&A
  • 5. The Business Case Distributors and resellers prices 15,000,000 prices Other competitor’s prices
  • 6. Operational Challenges in Setting Prices Measuring the impact of pricing decisions Forecasting the impact of potential pricing decisions Getting Maintaining visibility into access to promotional profitability robust, Getting access to competitive robust competitive price data price data is a Making sure that stores change prices accurately and timely big challenge Keeping up with promotional deals Retail Systems cut by buyers with manufacturers Research 2012 Managing promotions Benchmark Report across channels
  • 7. Polling Question Are you currently collecting competitive pricing data from the Web? Yes – we are collecting pricing data from the Web No – we are not collecting pricing data from the Web but we have a project or plan to do this within the next 6 months No – we have no plans to collect pricing data from the Web
  • 8. Competitive Pricing: Real-World Success Stories Online Retailer of Specialized Retailer National Store Chain Goes Deep Web New and Used Goods • Checks 1M online • Checks prices on • Builds online prices per day to 3M items at catalog by win business national and local going 3-7 layers levels deep on direct mfrs’ Web sites for product info Automation is key to success
  • 9. Competitive Pricing: Real-World Success Stories Online Retailer of Specialized Retailer National Store Chain Goes Deep Web New and Used Goods LOWEST PRICE OPTIMIZED DOUBLED SIZE OF MARGINS ONLINE CATALOG Automation is key to success
  • 10. An Overview of the Automation Process Connotate Partners { { Collect Data Transform Deliver Internal Sources External Sources • Structure • Reports • Database • Social Media • Classify • Dashboards • Market Basket • Surface Web • Prep for Analysis • Workflow • Inventory, etc. • Hidden Web • BI Plug-ins •Secured Sites
  • 12. Price Optimization Case Study: Sigma Aldrich Sigma-Aldrich faced a “Big Data” challenge • An overwhelming volume of pricing information on the Web ? $ Jeopardizing Manual Inaccurate a Sound Processes Results Pricing Strategy
  • 14. Results: Price Optimization Pays Off Increase revenue 2%- 4% $8.75M - $16B for Fortune 500 Company
  • 16. Customer Sentiment “The better and more quickly a company can measure customer sentiment, the sooner it can tell how well a product is likely to sell.” – BusinessWeek, 2011
  • 17. Customer Sentiment: Deep Web A Fortune 50 consumer product goods company sought input from social media on customer sentiment about a popular class of products: • Twitter was easy to access via API but not useful; there was no in-depth discussion of features • Detailed product reviews existed on Amazon, Walmart, in microblogs and comments on YouTube videos • The firm wanted to access these sites and draw conclusions from this data to create a feedback loop for their continuous product design cycle
  • 18. Differences in Web Sources Facebook Twitter, etc. D A T Surface Web, Other A Social Media A Processing N Deep Web A (traverse links) L Y S Password- I Protected Sites S Data Sources Analysis 18
  • 19. Automation Opens Access to Deep Web and Secured Sites Facebook Twitter, etc. D A T Surface Web, A blogs, forums A Processing N Deep Web A (traverse links) L Y S Password I Protected Sites S Analysis Data Sources 19
  • 20. Obtaining Customer Sentiment from YouTube Manually search YouTube for <“product name”> <“review”> Use the Connotate automation package to find <“product name”> <“review”> in posted comments Use Connotate to follow links to other sites with <“product name”> Feed input into analytical engine to reveal sentiment Graphical User Interface/Presentation of Insights
  • 21. Refining Data for Business Insights: Customer Sentiment A major pharmaceutical company wants to understand the competitive landscape for allergy medications. • Decided to focus on data available online • Used Connotate to collect product information, prices and 4,700 customer reviews on 465 products • Analyzed data and found insights using Luminoso text analytics • Time from idea to initial findings: 6 hours
  • 22. Customer Sentiment Around Allergy Drug Cost as Displayed by Sentiment Analysis Tool
  • 23. Customer Sentiment Around the Word “Generic” Customer Sentiment Around Allergy Drug Cost as Displayed by Sentiment Analysis Tool
  • 24. The Value of the Data is in the Delivery
  • 25. Another Look at the Automation Process Your internal BI tools or Connotate Connotate Connotate partners Collect Data Transform Deliver • Reports Internal Sources External Sources • Classify • Dashboards • Database • Social Media • Structure • Workflow • Market Basket • Surface Web • Prep for Analysis • BI Plug-ins • Inventory, etc. • Hidden Web •Secured Sites Connotate provides precise quality data, structured for delivery to your analysis and presentation tools. Connotate maximizes the value of your investment in business intelligence, text analytics and semantic analysis tools. Excel
  • 26. Polling Question: Customer Sentiment Are you currently collecting customer sentiment data from the Web? Yes – we are collecting customer sentiment data from the Web No – we are not collecting customer sentiment data from the Web but we have a project or plan to do this within the next 6 months No – we have no plans to collect customer sentiment from the Web
  • 27. Manual versus Automated Approaches Your Data Needs To Automate or Not? ? May want to consider Complex product-matching tasks crowd sourcing Small amount of data, needed a few ? A manual approach may times per year suffice Specific external data (under $5K/year) ? Purchase from 3rd party High volume data monitoring  Automate Variety of sources  Automate Frequent updates and/or monitoring  Automate Need for data post-processing  Automate
  • 28. Vast Resources of Competitive Intelligence are Outside the Firewall Automation is Price the key to optimization extracting precise quality Product design data Deliver new online services Automation is needed when Dynamically the initiative is adjust product strategic positioning
  • 29. Selected Connotate Partners for Competitive Intelligence Text and Sentiment Analysis Data Integration and Pricing Intelligence CrowdSourcing Business Intelligence Special thanks to Nikki Baird, Retail Systems Research, www.rsrresearch.com
  • 30. Q&A Connotate will email a link to this presentation as well as a copy of the slides to you within 2 business days. If you have an immediate need and would like us to contact you about a forthcoming project, please check the appropriate box in the last polling question or call us at 732-296-8844. You may also visit www.connotate.com for more information.
  • 31. Thank You If you have an immediate need and would like us to contact you about a forthcoming project, please check the appropriate box in the last polling question or call us at 732-296-8844. For more information, visit www.connotate.com.