If I want to monetize my data, should I use a 3rd party "data as a service" API or should I develop my own "data shopping cart"?
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Now that apps like http://WebServius.com, http://DataMarket.com, http://InfoChimps.com and Azure DataMarket offer 3rd party data metering and billing, what types of companies should utilize 3rd party API's and what types of companies should develop their own consumer data shopping carts?
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Answer:
Monetizing data is a difficult technological and operational challenge. If your goal is to unlock your data's full revenue potential, you need to be able to reach all possible data buyers and reach them efficiently, but doing so with an in-house solution takes a lot of effort: For example, buyers who are looking for data that can be integrated into their own applications may prefer the data in the form of an API. Creating a best-practices API that conforms to all necessary standards (e.g. REST, XML, JSON) and has the right authentication / API key mechanism, the right metering/pricing mechanism, the right level of documentation, etc, is a difficult task in itself. Other data buyers may be looking to download data in bulk, either in whole or in part (for example, to be analyzed in a spreadsheet). Here, one needs to create an online tool to select, pay for, download, and often re-download the right subset of data; The tool must have sufficient usability for non-technical data buyers, and must support all necessary data formats - again, a difficult set of challenges. Regardless of how the data is delivered, a data vendor needs to provide a mechanism for data buyers to sign up and pay for data online in a self-service way. Mechanisms are also needed for data vendors to validate buyers and prevent fraud, to view reports/analytics on data purchase activity, to set up data pricing rules (which may often be fairly complex) or other access plans such as free trials and promotions. Finally, there are the operational challenges: payments need to be processed from data buyers, payment issues need to be resolved, technical support must be provided (which is especially difficult in the case of buyers who access data via APIs), SLAs must be maintained, data needs to be hosted and continuously updated. WebServius, as well as a number of other companies, set out to solve all of the challenges above. There are economies of scale at play here, and it is far more efficient for these challenges to be solved once for all data providers on a particular platform, than for each provider to reinvent the wheel. For data vendors, we set out to offerr a true end-to-end data monetization experience: If you provide us with access to valuable data, we will provide you with a way to monetize it in a variety of compelling ways (APIs, bulk data download, etc.), without you having to worry about any of the difficult problems above, and with you staying in full control of the pricing, branding and terms. An analogy here is the sale of physical goods: If you are selling physical goods online, it is often much more efficient to leverage an existing platform (Amazon Stores, Amazon FBA, eBay, etc.) than to build out an entire e-Commerce solution from scratch. I see WebServius and some of our competitors as the "Amazon/eBay of data".
Eugene Osovetsky at Quora Visit the source
Other answers
makes a number of good points in his answer, but one major issue that Eugene doesn't touch on above is developer convenience. It's unlikely that anyone's going to build an app on just your data; platforms like and (the latter of which is my company) normalise data from a very large number of sources, making it easier to build things with a more, let's say, polytheistic worldview! This isn't an issue if you are Twitter, but very few people are Twitter.
Andrew Walkingshaw
Serious question: why assume that profiting from your data is the direct result of selling it to someone? As and point out, the infrastructure to host data in a flexible way is hard. Accepting payments is hard. Disbursing payments to data providers is hard. In business, hard is a quick way of saying "it's expensive, it takes a lot of time to get right, mistakes will be made and at the end of the day there's no guarantee we'll succeed". All things equal, it's only a matter of time before most people working with data realize that the real value of data comes from establishing context, humanization via narrative and making it harder for liars to lie. Solve problems in those domains, and you will make a lot more money than if you try to sell your data the same way your grocer sells bananas.
Pete Forde
Disclosure: I work for Infochimps. The advantage of using our service is two fold: 1.) People are looking for data when they come to us already. 2.) The infrastructure is not as easy as one might think. Some of our data sets are over a terabyte in size. Hosting and serving that out is not easy, especially if you want to make it available through an API.
Michelle Greer
I think more information is necessary before advice can be given. For example what is the volume of user data available? What category/categories does it fall under? What is the geo footprint?
Tom Bullock
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