Following on from Part II in our healthcare series, which explored the application of machine-learning models to generate phase transition and approval predictions, we provide our view on the alternative datasets that pharma and biotech investors can use to augment their R&D pipeline analysis.

Slack, CrowdStrike, and PagerDuty – three SaaS companies have already gone public this year, and we are only halfway through 2019. For institutional investors that are active in this market, or simply curious about the space, we discuss some alternative approaches (and, of course, alternative datasets!) that could shed light on adoption, churn rates, recurring revenue, and acquisition costs of SaaS providers.

The growth of e-commerce has facilitated inflation tracking on a daily basis, namely from aggregating online pricing data. Moreover, the ubiquity of e-commerce in-itself is changing aggregate inflation dynamics. We believe product pricing datasets have a particularly potent use case in generating early inflation signals in opaque markets, such as LatAm, where official statistics are challenging to obtain. In this report, we review the academic literature that examines the behavior of online prices and its response to aggregate national shocks. We also outline where to find alternative sources of inflation data.

Cybersecurity risk ratings have recently drawn attention as a new player in the alt data arena. In this piece, we summarise the current academic status quo regarding cybersecurity breach incidents and financial market impact, before discussing the usability of relevant datasets from an event arbitrage and risk management perspective.

How much does alternative data cost? The million dollar question. We leverage our unique position in the industry and proprietary data on pricing to shed light on how much datasets really cost, which factors influence the price of a dataset, and whether funds are willing to pay the price for valuable datasets.

A structured database of companies that are filing for bankruptcy is a gold mine for institutional investors. Not only does it highlight distressed and/or turnaround investment opportunities, it can also be a valuable leading indicator to identify which other companies may soon share the same fate. For readers that are 1) actively searching for a bankruptcy database, 2) considering alternatives to the database(s) that they are currently subscribed to, or 3) simply curious about the space, we summarise a 2018 academic paper that details how to construct a company bankruptcy database using alternative data.

Using hiring activity data as a signal for future business growth is the most common investment use case for aggregating online job postings. But do other use cases exist for this type of data? For example, can it tell us a) how effective companies are at hiring highly demanded skills, b) whether any of their facilities have suspended operations or even c) a clearer picture of the economic activity in opaque markets? In this piece, we review the landscape of vendors providing job market data, outline possible use cases and discuss its limitations.

With great power comes great responsibility – or not? According to one academic paper, firm-level electricity consumption data provides a novel window into financial misreporting among South Korean firms. We discuss how an investor can take this use case from theory to practice with a number of alternative indicators for firm productivity.

Now Uber and Lyft have both gone public, we take a look at some of the alternative data captured on these companies. There are various sources of insight into performance and prospects for rideshare companies, spanning a number of dataset types. In this piece, we highlight insights derived from ESG and transactional datasets.

It has been nearly six months since we last discussed Net Promoter Scores (NPS) in one of our Intelligence reports - our report initially made the case against NPS. Despite refuting the controversial customer loyalty metric as a leading financial indicator, we at Neudata still continue to receive interest from a significant number of institutional investors for NPS datasets. In response, we revisit the topic and discuss a 2018 academic paper that investigated whether NPS could be predictive of consumer spending and company revenue.