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How Technologies like Big Data
and Social are Changing
Product Management

             By Edward Chenard
New Tools Mean New
Opportunities
   Social has taken off in the last five years
    to become a common place
    communication channel.
    ◦ Despite widespread acceptance, many
      companies still do not engage customers via
      social for product development.
   Big Data has taken off in the past three
    years and shows great potential.
    ◦ However, most companies still do not
      understand big data’s potential for innovation.
Product Management can Great
Benefit from These New Tools
 New product introduction can be A/B
  tested faster and for less money.
 The ability to test more product
  features faster is greatly improved.
 The ability to engage customers in
  new ways both directly and indirectly.
 Data has grown 1000% since 2005
  and growing faster!
Vitaminwater
 Vitaminwater used Facebook to create
  new flavors
 Fans on Facebook won $5,000 for
  their new product ideas.
 2 million people participated in the
  new product development effort
How eBay uses Big Data
  eBay manages over 40 petabytes of
   data (1 petabyte equals 10 billion
   photos).
  eBay runs multiple tests at the same
   time and these tests average 1MM
   users.
  The tests are used to identify patterns
   and insights to create new products
   offerings.
How Netflix uses Big Data
  75% movies are selected from
   recommendations.
  Netflix lives or dies by the way it uses
   data.
  New product test involves mass
   amounts of data and analysis that are
   used to create new products.
  The CEO spends 2-4 hours a week
   reviewing these tests.
Netflix and Social
 Netflix has been testing social
  recommendations overseas.
 Social driven recommendations are
  driving product changes.
 These changes are driving growth and
  bringing customers to Netflix in bigger
  numbers, in those overseas markets.
How to use Data to Improve
Product Management
 Understanding data is the key to
  improving the product development
  process.
 Impression data: What is shown,
  when and where.
 Personal data:
    ◦   -   Transaction data
    ◦   -   Social data
    ◦   -   Device data
    ◦   -   Personal identifiable data
Using Data to spot Trends
   Recency, Frequency, Monetary (RFM)
    ◦ How recently did someone search
    ◦ How often
    ◦ What is the monetary value of the
      searches
    Use RFM to help predict behaviors with
    your data among segmentations.
What you Need to Know About
Social
 You don’t control the conversation
 It is a dialogue with customers, so
  engage them, don’t sell to them.
 Social is a full contact channel
 Go Beyond Facebook and Twitter.
What you need to know about
Big Data
 This is not about IT, Business needs to
  drive this
 Understand the tools and roles i.e,
  Hadoop and Data Scientists
 Understand privacy issues when it
  comes to data collection
 It’s not just about the data
What is the Future?
 Combing personal attributes with
  behavioral information will give
  companies better insights into what
  new product features will resonate
  with customers.
 Combing attributes and behavioral is
  where social and big data converge.
What is the Future?
   Bayesian Learning Systems
    ◦ Easy for non-techies to learn
    ◦ Bayesian tools today make it easy for
      product managers to do their own
      analysis without the need for IT.
   Nearest biclusters
    ◦ - Neighborhood based data collection
What is the Future?
   Data and signal collaboration
    ◦ New product developing will involve
      customers more and more.
        Signaling
        Personal data hubs
        Device data
        New forms of communication
        Always keep changing!
Thanks you
 Find me on Linkedin
 Blog: Crosschannelprairie.com
 Email: edward@echenard.com


   Thank you
    ◦ Edward Chenard

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How technologies like big data and social

  • 1. How Technologies like Big Data and Social are Changing Product Management By Edward Chenard
  • 2. New Tools Mean New Opportunities  Social has taken off in the last five years to become a common place communication channel. ◦ Despite widespread acceptance, many companies still do not engage customers via social for product development.  Big Data has taken off in the past three years and shows great potential. ◦ However, most companies still do not understand big data’s potential for innovation.
  • 3. Product Management can Great Benefit from These New Tools  New product introduction can be A/B tested faster and for less money.  The ability to test more product features faster is greatly improved.  The ability to engage customers in new ways both directly and indirectly.  Data has grown 1000% since 2005 and growing faster!
  • 4. Vitaminwater  Vitaminwater used Facebook to create new flavors  Fans on Facebook won $5,000 for their new product ideas.  2 million people participated in the new product development effort
  • 5. How eBay uses Big Data  eBay manages over 40 petabytes of data (1 petabyte equals 10 billion photos).  eBay runs multiple tests at the same time and these tests average 1MM users.  The tests are used to identify patterns and insights to create new products offerings.
  • 6. How Netflix uses Big Data  75% movies are selected from recommendations.  Netflix lives or dies by the way it uses data.  New product test involves mass amounts of data and analysis that are used to create new products.  The CEO spends 2-4 hours a week reviewing these tests.
  • 7. Netflix and Social  Netflix has been testing social recommendations overseas.  Social driven recommendations are driving product changes.  These changes are driving growth and bringing customers to Netflix in bigger numbers, in those overseas markets.
  • 8. How to use Data to Improve Product Management  Understanding data is the key to improving the product development process.  Impression data: What is shown, when and where.  Personal data: ◦ - Transaction data ◦ - Social data ◦ - Device data ◦ - Personal identifiable data
  • 9. Using Data to spot Trends  Recency, Frequency, Monetary (RFM) ◦ How recently did someone search ◦ How often ◦ What is the monetary value of the searches Use RFM to help predict behaviors with your data among segmentations.
  • 10. What you Need to Know About Social  You don’t control the conversation  It is a dialogue with customers, so engage them, don’t sell to them.  Social is a full contact channel  Go Beyond Facebook and Twitter.
  • 11. What you need to know about Big Data  This is not about IT, Business needs to drive this  Understand the tools and roles i.e, Hadoop and Data Scientists  Understand privacy issues when it comes to data collection  It’s not just about the data
  • 12. What is the Future?  Combing personal attributes with behavioral information will give companies better insights into what new product features will resonate with customers.  Combing attributes and behavioral is where social and big data converge.
  • 13. What is the Future?  Bayesian Learning Systems ◦ Easy for non-techies to learn ◦ Bayesian tools today make it easy for product managers to do their own analysis without the need for IT.  Nearest biclusters ◦ - Neighborhood based data collection
  • 14. What is the Future?  Data and signal collaboration ◦ New product developing will involve customers more and more.  Signaling  Personal data hubs  Device data  New forms of communication  Always keep changing!
  • 15. Thanks you  Find me on Linkedin  Blog: Crosschannelprairie.com  Email: edward@echenard.com  Thank you ◦ Edward Chenard