Alternative Data Platform Thinknum Adds Product, Gains Sell-Side Clients

Thinknum, a NY-based alternative data platform, has expanded its product offering and gained increased traction with sell-side analysts, according to an interview with co-founder Justin Zhen.

Since we initially profiled the firm nearly a year ago, Thinknum has added fifteen public datasets, bringing its total offering to 65 datasets.  The platform focuses on public data such as government contracts, product pricing data, store locations, as well as extensive social media data from sources such as Twitter, Facebook, Instagram.

Store locations, Tesco vs. Sainsbury’s

Thinknum uses web scraping to create proprietary datasets from publicly available information, such as product pricing derived from online sales (a chart for pricing of Samsonite products shown below).

Average price for all Samsonite products updated daily

The power of the platform is that all the data is organized by publicly traded companies, so for each ticker users can see all the relevant databases available, and can link them together to build a financial model for revenue forecasts.  The company has added non-US coverage and doubled its company coverage to 4,000.

Number of tenants for REIT Macerich, updated daily

Thinknum’s clients are primarily hedge funds, but the firm also been adding sell-side clients.  Sell-side users now represent about 20% of the client base.  Thinknum has recently been cited in reports from Goldman Sachs, Jefferies, RBC and Wells Fargo.  The firm’s flat fee of $400 per user per month is priced to be broadly attractive across client groups.

The company originated in 2014 as a financial model sharing site, similar in concept to GitHub which allows programmers to share open source code.  Zhen was previously a hedge fund analyst and co-founder Gregory Ugwi worked as application developer at Goldman Sachs.  The two met while attending Princeton University.

The firm pivoted its product focus from helping analysts build models to gathering alternative data because hedge fund clients were asking for alternative data inputs for their models.  The firm still offers modeling capabilities, but with the rise of well-financed model distribution sites such as Visible Alpha and Canalyst, we suspect that Thinknum’s focus will remain on alternative data.

Thinknum was funded with an initial seed round in 2014 through the accelerator 500 Startups.  According to Zhen, the firm is currently profitable and growing quickly so it does not require funding.

Our Take

There are a growing number of alternative data providers but Thinknum is unusual in how well it has integrated the data for financial analysts, and the ease of its analytics.  The firm is also differentiated in its pricing strategy.  Unlike data providers trying to skim hedge funds with high priced product, Thinknum has priced its product at a level to appeal to broad constituencies, including corporates.  Partly the pricing strategy reflects a product focus on integrating publicly available datasets rather than trying to acquire private datasets exclusively.

We are not surprised by the growing use of the platform by the sell-side since Thinknum provides an interesting and affordable option, even for independent research firms, since the firm is not exclusively focused on the buy side.