This document discusses the power of small data compared to big data for marketers. It argues that small data, which involves filtering data by segments like time, location, or profiles and measuring important metrics, can provide valuable insights when analyzed properly. The key is to start small by identifying relevant data sources, defining metrics and goals, and testing and refining analytics on segmented slices of data rather than trying to analyze all data at once. Small, targeted data analysis focused on important metrics can allow businesses to make better real-time decisions.

1. The Power of Small Data
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2. Defining Big Data
Petabyte
Terabyte
Unstructur
ed Date
Gigabyte
Megabyte
Kilobyte
New
Analytics
Data
Site
hits
1980’s
Social
Data
1990’s
Site
hits
2000’s
Social
Data
New
Analytics
Data
Site
hits
2010’s
Social
Data
New
Analytics
Data
Site
hits
Present

3. Defining Big Data
Volume of Data
• Explosion of data sources especially social
• Tera/PetaBytes of data warehouse
Velocity
• Frequency of data collection
• Social streams / real-time and geo-sensor
Variety of Data Sources
• Multiple disparate data sources
• Transaction
• Owned / Un-owned data properties
Insight
• Segmentation
• Intersection
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4. Defining Big Data
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5. Big Data is Not the Holy Grail for Marketers
Risks
• Amplifying quantifiable perspectives at expense of valid and real
human intuition
Not Fully Automated
• No black box
• Human error, invalid data, inaccuracies
• Complex to create intersection, deal with large volumes of data
Human Insight
• Needs process, KPIs and metrics
• Needs human interaction to interpret
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6. Big Data is Not the Holy Grail for Marketers
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7. Identifying Small Data
Segmentation
• Filtering by slices
(time, geo, profile,
etc)
• Intersection of
multiple data
sources
Measure things
that are important
• Outliers and
trends
• Watch for out of
context data
The Last Millisecond
• Ability to collect data to create
information that allows you to make
better business decisions
• Insight to effect the decision at the right
moment
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8. How Do You Start?
Plan and Start Small
ID Data Sources
• Site Analytics
• Social Streams
• Transaction
• Un-Owned
Determine KPI Metrics
• Cross-references / intersection of data
• Measure key data points often in an aggregate manner
Leverage Technical Tools
• ETL
• Aggregation, reporting
Define Your Target and Goals
• Segmentation of audience
• What slice of data needs to be analyzed
Test and Adjust
• Analyze trends, outliers using analytics and graphical tools
• Refine – learn what works and does not and make adjustments
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