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A New Source of Revenue for Data Scientists: Selling Data

What kind of data is salable? How can data scientists independently make money by selling data that is automatically generated: raw data, research data (presented as customized reports), or predictions. In short, using an automated data generation / gathering or prediction system, working from home with no boss and no employee, and possibly no direct interactions with clients. An alternate career path that many of us would enjoy!

There are a number of companies making money by selling cured (or even raw) data:

  • Web traffic statistics to allow advertisers to compare publishers to buy the most efficient traffic, or to help pricing a web site, and for competitive intelligence in general. Compete.com, Alexa.com and Quancast.com are three examples. They also provide demographics and keyword data for the millions of websites that they track.
  • Salary data and jobs trends, for thousands of occupations. Companies such as Payscale.com, Glassdoor.com and Indeed.com gather salary data from millions of visitors and job postings. Such job reports can also be used for economic forecasting or stock trading models.
  • Keyword lists, with number of impressions, clicks and average cost-per-click, as well as related keywords, to help advertisers purchase more and better keywords. Google offers this service via an API. It is not free.
  • Black lists and white lists of IP addresses or email addresses used in fraud, Botnet activity or forum spam. An example of company selling this type of data is ProjectHoneyPot.org, with data based on consumer reports an other sources.
  • Home values (real and estimated) for all houses in US, see Zillow.com.
  • Pricing for all standard medical procedures, for each hospital (real and estimated). This is actually a good idea for a big data start-up.
  • Stock market data, consumer reviews (Yelp.com), lists of thousands of job titles for data scientists (we are working on this), and so on
  • Your predictions (we sold stock market trading signals in the past, available via an API, and the service was not free).
  • Selling scores, such as click scores or any other scores. FICO was one of the first companies to do so.

Do you have other ideas, as well as ideas to inexpensively collect massive amounts of data to produce and sell scores or predictions, or just simply to sell the data that you gathered?

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Comment by Sameer Soi on December 3, 2013 at 10:22am

Another source of data that can be capitalized upon is the trove of data locked up in unfriendly government databases (although the Obama administration has made some strides in engaging the data science community). For example FDAble takes the FDA's adverse drug event reporting system's raw data dump and provides a searchable web-interface with full reports for sale in addition to custom predictions of potential drug interactions.

Comment by Dr. Z on December 3, 2013 at 6:20am

I never understood why data scientists were in such high demand (and are expected to be in even higher demand in the future) until I read this article. Abundance of info-rich data is not something of tomorrow but something of today. Thanks for sharing this info-rich article.

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