On March 23rd 2017, Eagle Alpha published a research note analyzing the launch of Ubisoft’s (UBI:FP) flagship game for the quarter, Ghost Recon Wildlands. The game significantly underperformed against last year’s major launch, the Division, on key online metrics.
Asset managers constantly ask Eagle Alpha for case studies that demonstrate how alternative data can add value to their investment process. In response to this demand Eagle Alpha will regularly publish a compilation of case studies. This document is the first in this series.
Asset managers have been integrating alternative datasets in their processes but they should be highly attentive and avoid sources that contain personally identifiable information (PII).
Eagle Alpha Web Queries is a query based tool that enables clients to obtain analytics on over 90 million web sources including: blogs, image and video sites, forums, review sites, social media and news sites. It is especially useful when analyzing consumer reactions to new releases.
CRISIL, majority-owned by S&P, prepared a report (attached) analyzing the state of big data adoption in the asset management industry. CRISIL surveyed asset managers finding that in 2017 over 80% of their respondents were planning to increase investments in big data (figure 1).
Google Trends is a public web facility based on Google Search that shows how often a particular search term is entered relative to the total search-volume over time across various regions of the world.
The aim of this project was to build revenue indicators for US retailers using online search activity as a barometer of future company sales.
On April 5th 2017, Eagle Alpha published a research note analyzing the launch of the Samsung Galaxy S8. We used Web Queries/Twitter, search data and online pricing to give a read on initial reaction to the product, and some early indication on likely success.
Google Trends is a public web facility based on Google Search that shows how often a particular search term is entered relative to the total search volume over time across various regions of the world.
The goal when working with e-commerce data is to build the most complete picture of the online performance of a specific company.
In the initial testing process of the predictive value of app data, we evaluated the relationship of the data with a company’s quarterly revenue.
