Data Trends for Investment Professionals

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Data Monetization: Pricing Your Data Product

Pricing Your Data Product You’ve built your data product and are ready to put it on the market. You’ve done your due diligence, making sure that your data is clean, predictive and completely scrubbed of sensitive information. You’ve created great relationships with hedge funds and consultants. Everything seems to be in order until you make that first call with a potential client. They ask, “How much do you charge for your data?” In other words, is there any logic to the way you are pricing your data product. What do you charge, indeed: Is your asking price too high, too...

Data Monetization: Marketing and Selling Your Data Product

In the last post, we covered compliance concerns and data privacy and discussed what hedge funds expect in their data products. In this post, let's assume your product is fully developed and ready to be sold. Just get your marketing team on it, right? Not exactly. Even if you're a data company, marketing and selling data products to Wall Street is a unique process. Active managers make their wealth partly by keeping their circles closed. Therefore, despite having successfully productized your data assets, you may still not be able to penetrate the coterie that is Wall Street — your key demographic....

Data Monetization: Compliance and Privacy

In our previous post, we completed our discussion of data productization, focusing on the importance of robust delivery systems and packaging. Next, we will discuss the data compliance and privacy concerns most often expressed by data providers. The media has made much of datasets used by Wall Street that are not “anonymized”, but the reality is that professional investors do not care one bit about an individual’s information. They only care about data that moves markets. That Lucy Morgan, 37, of Louisville, Kentucky just bought six family-sized bars of Hershey’s chocolate using her MasterCard at Costco does not interest them in...

Data Monetization: Delivering Your Data

As discussed in part one of our Data Monetization series, Building a Data Product, in order to sell data to finance professionals, your product must be clean and predictive. Data hygiene and predictiveness, however, are just one of many prerequisites on the path to productization. Though you are not expected to provide trading insights or make stock predictions, analysts and investors don’t want to have to corral your data. They want to be able to consume it easily without doing too much legwork. In this post we cover two key components to minimize data wrangling: How to properly package your...

Data Monetization: Building a Data Product

One thing we are often asked here at Quandl is how to go from raw data to a salable data product. We're the first to admit that the process of data monetization is complex and tedious, but ultimately worthwhile for your company. Whether you're a start-up or a publicly traded corporation, taking the time and upfront investment to transform your existing data into a market-ready product can pay handsome dividends in the long-run. Our specialty lies in developing data products and marketing them to a Wall Street audience. By this, we mean any institutional investor who is interested in consuming data to...

API for Stock Data

Quandl offers a simple API for stock market data downloads. Our daily data feeds deliver end-of-day prices, historical stock fundamental data, harmonized fundamentals, financial ratios, indexes, options and volatility, earnings estimates, analyst ratings, investor sentiment and more. This post describes how our stock market data is organized, and explains how to access it. Data Organization: Time-series vs. Tables Quandl's data products come in many forms and contain various objects, including time-series and tables. Through our APIs and various tools (R, Python, Excel, etc.), users can access/call the premium data to which they have subscribed. (Our free data can be accessed...

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