Ahead of the 2018 holiday season we look back to Black Friday 2017 and perform a proprietary analysis of how investors can utilise advertising and clickstream datasets to predict the performance of retailers over this period. In particular, we focus on three large US retailers: Walmart, Target, and Kohl’s.

We recently discussed how the American Customer Satisfaction Index (ASCI) generates superior returns at a lower systematic risk. In this piece, we discuss Net Promoter Scores (NPS) – a popular measurement of customer loyalty – and whether it is an appropriate metric for investment managers aiming to predict company financial performance.

We explore the use of fund ownership data and analysis, highlighting a research piece produced by a Neudata-listed alternative data provider. In this piece, portfolios of specialist healthcare investors are analysed and ownership trends are identified for specific healthcare subsectors. We also highlight a number of alternative data providers offering this type of data, as well as a selection of healthcare data providers.

We discuss the key regulatory issues concerning the collection, processing and usage of geolocation data. Starting with the definition of geolocation data as ‘personal data’, we draw attention to several cautionary tales of data misappropriation or privacy leakage, before discussing best practices according to GDPR, as well as the logistical and legal challenges associated with data anonymization. We also draw attention to several future policy developments that should be on the radar of any informed user of geolocation data.

In this report we argue why paying attention to company diversity can yield value to investors. In short, we provide evidence that suggests 1) board and managerial diversity has a positive correlation to financial performance, 2) increasing regulatory requirements on diversity disclosures is set to drive the growth of diversity-based financial products, and 3) this will likely impact company valuations, as well as the ability for certain companies to raise capital.

We explore the idea that companies with higher levels of customer satisfaction generate superior returns at lower systematic risk based on two research studies, one of which analyses the relationship between customer satisfaction and stock market returns over a 15-year period. We highlight key findings, illustrating the stock-specific use cases for customer satisfaction data. We also highlight a number of alternative data providers who offer measures of customer satisfaction.

We discuss the Skyscraper Index - the principle that the world’s tallest buildings are often completed on or around the precipice of economic downturns, making it a useful leading macroeconomic indicator. We also examine whether there is any merit to construction activity data, in general, being an indicator of economic growth, whilst highlighting a few relevant alternative data sources for readers interested in incorporating such data into their decision-making processes.

In the first part of this series, we introduced the ways in which location information (ideally coordinate-based) is generated and subsequently made available to third parties. In the second part, we provide an overview of the technologies and challenges associated with contextualizing raw location data.