What Kind of Data Do Hedge Funds Actually Buy? Is E-Commerce Scraping Sufficient or Should I Explore Other Data Sources?
Hey everyone,
I’m exploring the world of alternative data and am interested in understanding what types of data are valuable enough for hedge funds to buy. I’m particularly looking into e-commerce scraping (e.g., tracking prices, stock availability, product reviews) as an entry point, since it provides insights into consumer behavior. However, I want to make sure I’m not missing out on other valuable data sources that hedge funds would find more useful or actionable.
If you have any knowledge or experience with hedge funds and data acquisition, I’d appreciate any insights on the following:
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How valuable is e-commerce data alone? – Are hedge funds actively purchasing data that includes pricing trends, availability (stockouts), and customer reviews? Or is this data too generic without additional context?
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What other data sources are in demand? – Apart from e-commerce, what types of data are hedge funds willing to pay for? (e.g., social media sentiment, geolocation data, job listings, satellite imagery).
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How important is data uniqueness and exclusivity? – Do hedge funds care more about exclusive access to a dataset, or is it enough to offer unique insights derived from publicly available data?
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Are there specific industries or types of companies where alternative data is especially valuable? – For example, does consumer retail data hold more interest compared to tech or healthcare?
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Any recommendations for structuring the data? – For those of you who have sold data or have insights, what’s the preferred format or structure for hedge funds (CSV, APIs, SQL databases)?
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What’s the typical price range for alternative datasets that hedge funds are willing to pay for? If you’re aware, any guidance on pricing would be helpful.
I’m looking to create an MVP dataset that’s valuable enough to attract initial interest without a huge upfront investment. Thanks in advance for any guidance or advice you can provide!
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Student here so 100% of what I said could be wrong. Anyone who actually knows what their talking about feel free to correct.
1. Too generic without context especially if its commercialized data. Applying it/ interpreting it is 100x more important. Everyone is looking at alot of the same alt data.
2. Web Searches, Visits, Clicks, Length of Stay, ASP's, Receipt Scraping, Ticketmaster scraping, Twitter Scraping, Flight Data, Weather Data, TrX/EuTrx numbers. Basically everything and anything you can think of if its part of the strategy.
3. Depends on the strategy. Obviously a custom dataset that is internal is much more valueable than something like Placer.
4. Not sure so someone can correct me here but Consumer/Tech datasets are more mainstream but im sure every sector will use.
5. Whatever you want (R & Python are common)
6. Looked into a few datasets and was quoted 6 figures + semi annually depending on the set. Anecdotal tho
Look up M-Sci and Yipit. FWIW anything publicly available is not worth paying for. You need some sort of exclusive deal with retailers to justify the cost.
Most HFs are pretty good about having teams in-house to execute on basic scraping projects.
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