Data strategy is a necessary component of every company but the approach and skills can vary widely as a product and its users grow. Data ensures that each product feature released can be measured as to its impact and effectiveness. Data also surfaces latent market needs that can be leveraged into further product value. Carbon Five has been using data to solve tricky product problems with companies like Square, Altschool, StitchFix, Prosper, and Fandango for over 15 years. Come join the conversation if you are interested in what skills are necessary to drive data science at your company, how to hire data science talent, and what data strategy looks like for different companies. - See more at: http://schedule.sxswv2v.com/events/event_V2VP46093#sthash.oPukb2oW.dpuf

1. Data Strategy
How & When to Invest
@chemphill
@carbonfive
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2. Data Frenzy
“Information scientists work every day on the
design, delegation and choice of classification
systems and standards. Each standard and each
category valorizes some point of view and
silences another.”
-Sorting Things Out: Classification and its
Consequences
Geof Bowker & Susan Leigh Star
@chemphill
@carbonfive
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3. @chemphill
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4. Types of data
• Quantitative and Objective
- Information collected in sufficient quantity that
significance can be determined numerically
• Qualitative and Subjective
- Information collected where significance is
determined experientially
@chemphill
@carbonfive
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5. Measuring of data
• Quantitative and Objective
- Instrumenting an app with tracking code, querying
the database or log files
• Qualitative and Subjective
- Interacting one-on-one with users
@chemphill
@carbonfive
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6. Solving Big ProblemS.

7. Big Data
- AI and adaptive systems
- gross patterns in technology and users
- challenge to core biz assumptions
- dispel old fashioned market ideas
- statistical significance!
@chemphill
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8. Big Data
- What signals?
- What inputs (devices)?
- Scaling issues?
- External data sources?
@chemphill
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9. Solving New ProblemS.

10. New (small) Data
- match to qualitative
- iterative design and data collection for formative
and generative design
- summative methods (data w/in experience and
context)
- high information density rather than high
volume
@chemphill
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11. New (small) Data
- Data with user base of 0?
- When to start?
- Mining APIs (Twitter, Google, Facebook)?
- Process?
@chemphill
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12. solving Good ProblemS.

13. Good Data(data for good)
- open data
- health care, government, transportation, etc
- understandings of human psychology and/or
social behavior
- harness knowledge and collective good of the
crowd
- behaviors outside of market/product context
@chemphill
@carbonfive
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14. Good Data(data for good)
- Socrata?
- health care, government, transportation, etc?
- Ethnography, research institutions?
- Surprising findings?
@chemphill
@carbonfive
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15. Skills for data
• Quantitative and Objective
- Data scientists, researchers in labs, statisticians,
mathematicians
• Qualitative and Subjective
- Cognitive psychology, anthropology, HCI experts,
product managers, ethnographers
@chemphill
@carbonfive
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16. Data Culture
• Proactive vs Reactive
• Integration into whole company
• Valued from the top down
• Budgeted for and prioritized
@chemphill
@carbonfive
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17. Measuring Impact
• Optimizations
• Generating new ideas
• Informed recommendations
• Dispelling old fashioned ideas about markets/
user behavior
@chemphill
@carbonfive
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18. How we work with data
Design & BuildCollect & Analyze
Define goals &
Craft hypotheses

19. How we communicate data

21. How we communicate data

22. How we communicate data

24. Prosper

25. Prosper
• Qual + Quant across devices
• EDD + TDD
• Continuous experiments testing
aesthetics, multi-variant funnels,
messaging and interaction design.
• Roughly tripled mobile conversion rates
• $354.9 Million in 11 Rounds from 25
Investors

26. Isilon InfoIQ

27. • Crunches 50 Gb of metric data per hour
• Manage petabytes of data (1,000,000
gigabytes)
• Shows dataset growth trends, past
performance to predict future needs
• Diagnose historical and real-time system
needs
• Fully manage resources via quota and de-dup
reports
Isilon InfoIQ

28. Opower

29. • Data from current weather, season,
time of day etc
• Data from user behaviors and
settings
• AI got better and better over time
• 85 utility partners + 18M customers
Opower

30. SimpleGov

31. SimpleGov
• Aggregating open data from multiple
government agencies
• Data from response rates to show
most proactive agencies
• Tagging of open data to easily find
issues by various metrics

32. Resources• UserTesting
• Heap
• Segment.io
• Optimizely Testing in iOS
• Testing with PhoneGap
• Rainbow Spreadsheet
• Socrata
• Data.gov

33. Tools• Proto.io (mobile/iOS)
• Flinto (iOS)
• Brief (iOS)
• Solidify (User Testing)
• Easel (Responsive Web)
• InVision (Designing+Prototyping)