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Social CMI: Social data in context

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Social data is just one part of a rich tapestry of data available to brands, none of which should be viewed in silo for anyone seeking to really know their customer. The opportunities for joined-up consumer insight are huge, however data integration also presents considerable challenges. In this session we'll explore how social data can compliment and enhance other data in the research mix and how themes discovered through social can be further explored through data integration.

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Social CMI: Social data in context

  1. 1. Social Data in the Real World Challenges, Pitfalls, and Biases PAUL SIEGEL/ DATA SCIENTIST
  2. 2. BRANDWATCH.COM The Drunkard’s Keys
  3. 3. BRANDWATCH.COM • Social data is flawed • Your data is probably flawed, too • Combining them is hard! The Problem
  4. 4. Challenges
  5. 5. BRANDWATCH.COM • Who uses social? • Pitfalls of sampling Selection Bias
  6. 6. BRANDWATCH.COM • Direction of causation • Confounding variables Correlation/Causation
  7. 7. BRANDWATCH.COM • If you look for evidence, you will find it! Confirmation Bias
  8. 8. BRANDWATCH.COM • Limit your hypotheses • 80/20 rule Overfitting
  9. 9. BRANDWATCH.COM • Hidden signals • Simpson’s paradox Underfitting
  10. 10. General Tips
  11. 11. • Be explicit about your assumptions • Look for patterns before analysis: demographics, seasonality, etc. • Tell a story, and try to disprove it • Keep your model as simple as possible, but no simpler BRANDWATCH.COM

Social data is just one part of a rich tapestry of data available to brands, none of which should be viewed in silo for anyone seeking to really know their customer. The opportunities for joined-up consumer insight are huge, however data integration also presents considerable challenges. In this session we'll explore how social data can compliment and enhance other data in the research mix and how themes discovered through social can be further explored through data integration.

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