Data science employs techniques from many fields including mathematics, statistics, computer science, and information science. Data scientists use a scientific approach to analyze big data and identify patterns to predict future outcomes and guide decision making. Examples of data science applications include predicting flu outbreaks, ranking web pages, targeting online ads, and optimizing email campaigns. Data science skills in high demand include SQL, Python, R, machine learning, and statistical analysis.

1. Data Science in Marketing
Forest Cassidy, CEO LeadFerret, Inc.

2. What is Data Science?

3. Wikipedia: “Data science employs techniques
and theories drawn from many fields within the
broad areas of:
• mathematics,
• statistics,
• operations research,
• information science,
• and computer science….

4. …Wait, there’s more
• including signal processing,
• probability models,
• machine learning,
• statistical learning,
• data mining, databases,

5. • data engineering,
• pattern recognition and learning,
• visualization,
• predictive analytics,
• uncertainty modeling,
• data warehousing,
• data compression,

6. • computer programming,
• artificial intelligence,
• and high performance computing.”

7. Drew Conway’s Definition
Author of Machine Learning for Hackers and co-founder of DataKind

8. • Business intelligence is querying the past,
while data science is using data from the past
and present to build models to predict and/or
affect the future within a scientific framework.
• Ask what if questions, then answer them
based on observed and measured patterns.

9. What do Data Scientists Do?
• Data scientists use a scientific approach to
refining big data into products, intelligence,
and action.
• They use a scientific method not unlike the
one you learned when creating your 7th grade
science fair project.

12. Data Scientist Skills
frequency per 1,000 social profiles with title =“data scientist”
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13. What is Big Data?

14. • Big data is not just about the size of the data, it’s
about:
– Volume
– Variety
– velocity
• Big data in its purest state is
like noise, everywhere at once,
never at rest, and continuously
moving extremely fast.

15. Examples of Data Science at Work
• Google 2009: Predicts
which regions of Mexico
are at highest Ebola risk
based on flu related
searches
• Google’s page ranking is
data science
• Google uses data science
for ad targeting

16. • “You want to connect
with this person” on
social networks
• “You might also like this
product” on Amazon,
Netflix, Etc.
Examples of Data Science at Work

17. • Video games
• Voice recognition
• Fraud detection
• Airline route planning
• Price comparison sites
• Delivery logistics
• Coming soon: self driving
cars and robots
Examples of Data Science at Work

18. • Predicting which content
will resonate
• Predict which social
networks your prospects
are likely to be listening on
• Predict which offers will
work with which customers
• PPC Optimization
• Retargeting Optimization
Data Science in Marketing
• Churn prediction
• Email campaign
optimization
• Custom messaging
• Message timing
optimization

19. • Start with a question and
hypothesis
• Compile the data to test your
hypothesis
• Maintain your control
• Query the data
• Analyze your results
• Draw your conclusion
• Take action accordingly
• Tweak and start over
Identifying Patterns in Customers and Prospects

20. Start with question and hypothesis:
Identifying Patterns in Customers and Prospects
disclaimer: pseudo-data science

21. Compile the data to test your hypothesis:
Identifying Patterns in Customers and Prospects

22. Maintain your control(s):
Identifying Patterns in Customers and Prospects

23. Query the data and Analyze your results:
Identifying Patterns in Customers and Prospects

24. Draw your conclusion:
Identifying Patterns in Customers and Prospects

25. Take action accordingly:
Identifying Patterns in Customers and Prospects

26. Tweak and start over:
Good Data science should never end.
Identifying Patterns in Customers and Prospects

27. Questions?