How technologies like big data and social media are changing product management

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