Alternative Data

What is Alternative Data?

Alternative data is data used by investors to evaluate a company or investment using non-traditional data inputs like financial statements, company announcements/press releases, management presentations, SEC filings, etc. This non-traditional alternative data actually helps investors collect more accurate or granular insights into company performance faster and ahead of earnings announcements. Alternative data can be a very important competitive differentiator. Currently, dozens of companies have emerged to collect, clean, analyze, and interpret data and provide it as a product that could inform investment decisions.

Top Alternative Data Types

How is alternative data generated?

  • Individuals –  Social and Sentiment, Web Traffic, App Usage, Survey
  • Business Processes – Credit and Debit Card (Transaction Data), Webscraped Data, Public Data, Email/Consumer Receipts
  • Sensors – Geolocation, Satellite, Weather

What are the different categories of alternative data?

App Usage – Data on app engagement and reviews. The level of data accuracy and usefulness depends on the app panel size, functions and features collected, and the level of user engagement

  • Use case gaming, food delivery, streaming services

Credit and Debit Card – Transaction data generated from credit and debit cards. This data is considered highly accurate when the transaction panel is large and covers a consistent user sample. These panels are some of the more expensive data licenses on the market

  • Use case Retail revenue tracking

Email/Consumer Receipts –  Transaction data generated from email receipts. This data is accurate with a smaller panel and can be biased depending on the nature of the email receipt collection whether from opt-in email or rewards app

  • Use case Retail revenue tracking

Geolocation – Foot traffic data available from WiFi signals (limited granularity and accuracy) or bluetooth beacons (higher accuracy, more expensive, less coverage)

  • Use case Geography-specific retail foot traffic tracking

Public Data – Open source data, publicly available. In its original form, this data is often difficult to access, not clean, not in a usable format (e.g. excel file or PDF). The value add of public data providers is the work of collecting, aggregating, and making the data actionable

  • Examples include SEC filings, patent data, government contracts, import/export data, etc
  • Use case patent data for tech company; supply chain imports for manufacturing; government contracts for construction company.

Satellite – Data collected from satellites or low-level drones. This data is expensive and of variable quality. Image processing is as important as data collection (raw data is not valuable to most investment teams). Satellite data on parking lots is only useful if a more direct measurement of store activity (geolocation data) or spend (credit card, email receipt) data is not available

  • Use case supply chain disruption tracking; agriculture yields tracking; construction tracking; oil & gas production/storage

Sell-side Broker Data – Alternative data teams within large sell-side institutions. Combine new data and processing techniques with traditional sell-side research

Social/Sentiment – Data obtained from text processing of social media, news, management communications, and other sources. Sentiment data is relevant for some companies (think younger, more trading volume, more volatile) more than large, established corporations. The data is often more relevant to shorter-term traders as it does not always reflect fundamental business aspects

  • Use case Event-driven sentiment tracking; brand and marketing campaign success

Survey – Data collected from surveys. This requires opt-in and panel diversity is variable depending on how good the provider is. This is a direct line in to consumer sentiment, rather than collecting it from text processing as in social/sentiment data

  • Use case brand preference; consumer behavior

Weather – Data on weather patterns collected from sensors

  • Use case agriculture and commodities

Web Data – Data scraped from public websites. This data comes in a wide range, from highly accurate and expensive to extremely raw and relatively inexpensive. This data is applicable where KPIs can be tracked by aggregating and analyzing large amounts of public-facing information, such as companies that publicize quantity sold and prices on each item page. Data is raw and can be very granular

  • Use case e-commerce; auto sales; airlines bookings; travel bookings; job postings

Web Traffic – Data on quantity, demographics, and clickstream of users visiting a certain website

  • Use case travel bookings; e-commerce and generally for tracking e-commerce efforts

Other – Point-of-sale data, ad spend data, pricing data, etc.

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