I am hoping to find a dataset of consumer demographics for individual products (e.g., age, gender, income, education level).

For example, say 40% of people with an Iphone are women, 32% are between 24-34, and 20% make over $100,000 a year. Whereas maybe Android users are 45% women, 28% between 24-34, and 25% make over $100,000 a year (arbitrary numbers).

Or for example, people that buy Snickers Bars are 12% women, 78% between 24-34, and 11% make over $100,000 a year.

I have been able to find demographic information for website traffic using Quantcast but I would like to augment that information with demographic information for individual consumer products/brands.

I suspect that this data exsists but I'm not sure if there's an open dataset available for it.

More directly, I would like to use this data to infer a user's demographic information from something like the twitter handles they follow or the products they Like on Facebook.


1 Answer 1


The iPhone/Android demographics can be manually parsed out of this article: What kind of person prefers an iPhone

Here is a snippet:

Characteristics of iPhone people versus Android people:

Highest level of education attained? iPhone people are more educated: they over-weight +27% for graduate/PhD education and under-weight -33% for high school education. Android people show the same pattern to a much smaller degree: +8% for graduate/PhD, -12% for high school.

Household income? iPhone people are more affluent: they over-weight +11% for >$75,000(3), +30% for >$100,000(3) and +48% for >$125,000(3). Android people are much less affluent but still have above average means: they over-weight for income categories above $50,000 but to a much smaller degree: +4% to +14%.

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(data from CivicScience)

  • Thank you for your response. I was only using iPhone and Android as an example. I'll try out CivicScience to see if I can access data for other products.
    – mech
    Mar 3, 2016 at 20:28

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