How do data providers (FB, Acxiom, 4square, etc) license out their data to enterprise with ideas around pricing?

As someone who has built TAM models for various industries - I can attest this isn;t always easy. Many analyst firms (former analyst here) typically do some surveys and research among public company revenue reports for the year and then do some pixie dust extrapolating. The hard thing about a market where startups like Datameer play is that it is a) a nascent market and b) not a "zero sum" game. This makes it difficult to a) fully understand WHICH companies actually are in the market for this flavor of BI and b) know how the space is developing in terms of white space AND disrupting the entrenched BI giants. You might want to look at the press published versions (read: free) of analyst market share reports, and extrapolate from their. Also, back-channel gossip may give you some revenue numbers on these players - and if you assume pipeline is 3-4x revenue, build a model from there. Hope this helps.

In my experience, this data has been at no cost. Most property appraiser sites offer sales data as an excel file for download. Each property can be looked at with exterior photos, or base floor plans. It would take quite alot of dara entry to input into a program, the issue would be the accuracy, if properties change hands within a year. Hope this helps! Warm Regards, Margie

There are so many ways to do it... Do you need this data for yourself, or you are planning to make a product around it? From what I see you can use Twitter API and Facebook Graph API (Are you comfortable programming?) Most of the students are active on social media so you will find lots of data. Facebook graph API will give you a number of likes and comments to all the posts of you competitors. You can analyze all the posts of your competitors. Using Twitter API you can get all the twits that use certain hashtags or mentions. If you are not into coding, but still want to get social media information, you can take a look at tools like IBM Watson ANalytics ($30 for personal use), it natively connects to Twitter API, and you don't have to be a programmer at all. It is intuitive and easy to learn. Analytics Canvas connects to Facebook Graph API (it's free for 30 days of trial). Unfortunately, you would not be able to collect any personal information from social media at large scale (age, income, gender, etc.), because it violates all the laws about privacy on the Internet. You can use census data instead. Google Sheets are a very handy tool if you are planning to use this information for personal research. You can set up a spreadsheet and add some Java script to make it collect all information from competitor's blogs, and also sites like Reddit. Finally, you can try web scraping (it's not the best, but can speed up the process). A tool like OutWitHub will collect information from websites (such as website reviews) based on the structure you provide (select html tags). You can collect thousands of reviews in one day if you automate it (paid version). Very easy to use. Note: not all the websites are open to this method, review their policies to make sure you are not violating their terms of service. Reviews belong to the website where they were published. If you REALLY need personal data (like how much they earn and how much they spend, etc.), just print out 100 questionnaires and go to Student Union Building of Dalhousie University. Most of the students will share any personal data in exchange for a Tim Horton's gift card that gets them a free coffee. It is probably the least technical and fastest way to get all the data you need. Hope this helps.

I would disagree with the premise that "big data" isn't being converted into valuable information. Modern advertising is being driven by exactly this ability. The problem lies not with the information, or lack thereof, but with the decision makers. Lack of vision at both the strategic and tactical levels of decision, fear of change, among other things are at the root of the problem.

Qualifications on the answer: Created the first website to be ever commercially licensed by a ministry of education for in-school use (Brainium 1996). Was a VC associate at a 500,000,000 firm called Knowledge Universe focused on all things education-related that intersected with technology. Short Answer: Yes and no. Longer Answer: Learning analytics is one of those "lightening in a bottle" kind of industries. Everyone knows it's going to happen, whomever makes it happen at scale first, will have a huge advantage, and even more niche plays in this space will still create massive value for shareholders and significant transformation of education as we know it. That's the good news. The problem is that funding startups in the education space that are dependent on "permission" being granted by existing institutions and their employees is very much hit or miss. It's getting easier to raise a $500-800k seed round for a good idea with a good team, but the problem is that getting the next bigger round is very challenging in that the models of most of these seed-funded companies are not growing fast enough to prove to institutional investors that a growth model of the idea being very big in a relatively short time-period is credible. So if you're intent on pursuing this, I'd be sure to focus entirely on how you can get growth and adoption with requiring little to no institutional buy-in which sounds almost impossible on the surface of the area you're exploring but I believe isn't actually impossible. I'm very passionate about this space and want something like what you're describing to succeed so would be happy to do a quick call to hear where you're at and see if I can provide you some actionable ideas on how to reduce the friction / improve adoption of your analytics product.