Demographic Partitions

Advanced Insights about your consumer sculpts relevant metrics creating impactful top-line strategic initiatives.

User Base Breakdown

Demographics impact how people express sentiment, what platforms they use, the tone used in sentiment, how aggressive/passive they will be in comments and many more factors. To truly understand sentiment, a user base breakdown is required.

Using demographic information and extracted data not available via platform (such as ethnicity and sexual orientation), Humanele will deliver actionable insights. Using our holistic approach we provide the most accurate assessment of a user’s sentiment portfolio

Historical Information/Interaction

Through the analysis of historical consumer data, Humanele is able to provide insights into platform and sentiment shifts. This data allows us to generate a predictive model for actionable marketing optimization and brand offerings, increase the chances of purchase and encapsulating that data for future strategic advertising trends.

Demographic Partitions

What are Demographic Partitions?

Demographics impact how people express sentiment, what platforms they use, the tone used in sentiment, how aggressive/passive they will be in comments and many more factors. To truly understand sentiment, a user base breakdown is required.

Using demographic information and extracted data not available via platform (such as ethnicity and sexual orientation), Humanele will deliver actionable insights. Using our holistic approach we provide the most accurate assessment of a user’s sentiment portfolio.

Through the analysis of historical consumer data, Humanele is able to provide insights into platform and sentiment shifts. This data allows us to generate a predictive model for actionable marketing optimization and brand offerings, increase the chances of purchase and encapsulating that data for future strategic advertising trends.

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Demographic Data Extraction

Varying levels of data extraction providing actionable consumer insights.

Combined

  • Gender
  • Age Range
  • Location
  • Likes/Dislikes
  • Public Information
  • Brand Overlap
  • Social Platforms

Extracted

  • Includes Combined
  • Access Method
  • Likes/Dislikes
  • Interactions
  • Brand Preference
  • Profession
  • Purchasing Classification

Conclusive

  • Includes extracted
  • Payment Methods
  • Mobile Data
  • Conversion Rates
  • Brand Ambassador
  • Purchasing History
  • Ethnicity
  • Sexual Orientation

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