Alternative Data Category Description
This category represents a heterogeneous group of alternative data datasets that provide unique insights into companies. These insights can come from a variety of alternative data sources, including customer data, market data, and operational data. Business insights can help companies identify trends, patterns, and areas for improvement, as well as inform strategy and planning. They can also help businesses to anticipate and respond to changes in the market, improve performance and efficiency, and make better-informed decisions. Technological innovation has allowed aggregators to collect alternative data from disparate sources and aggregate that alternative data in a format that is helpful for asset managers e.g., aggregators that track corporate advertising spending on various platforms and by campaign. Patent data is another example of how aggregators can collect unique insights into companies’ operations and R&D. Airlines flight data can also be used to uncover potential strategic changes and M&A activity.
Subcategory - Advertising Data
Advertising data refers to alternative data collected and analyzed about the performance and effectiveness of advertising campaigns. This type of alternative data can include metrics such as click-through rates, conversion rates, and audience demographics. It is used by companies to optimize ad targeting, improve ad creative, and measure the return on investment of advertising spending.
Advertising data vendors can help investors uncover how companies are running their campaigns. It can include information on ad creative assets, media platforms, landing page activity, the number of days/times the specific ads are encountered, etc. Utilizing these data, researchers can get an idea of branding strategy, compare/rank brands by brands, and calculate the share of voice. Advertising data exchanges gather data on consumer interests over time based on their internet browsing habits. This data could be used to track category popularity e.g., luxury products and financial products such as mortgages, automobiles, cybersecurity, etc.
Subcategory - Airlines Data
Flight data can be used to identify popular routes and destinations, as well as changes in travel patterns over time. This can inform investment decisions related to airline market share trends, airport infrastructure, tourism, and real estate. Flight data can be used to track the fleet of an airline, including the types of aircraft they operate, the age of their fleet, and their plans for fleet expansion or replacement. This alternative data can be useful in the analysis of companies supplying parts to aircraft manufacturers and parts for maintenance and repair.
Flight data can be used to track the number of flights operated by an airline and the passenger traffic they carry. This type of alternative data allows investors to potentially identify future corporate M&A activity based on private corporate flight activity. The output includes the frequency of the aircraft and the location.
Subcategory - Automotive Data
There is a wide variety of alternative data related to the Auto Industry and not all of it is available via conventional ways. These alternative data sources, that are available from many alternative data providers, providing insights into the automotive sector include datasets obtained from web scraping/crawling, exhaust data from business processes, social media, surveys etc. to name a few.
Automotive listing, pricing and transactional data, mainly collected through web scraping or manually from car dealership websites, auction houses and auto websites helps extract valuable insights like pricing trends, consumer demand to supplement investment research and competitive intelligence. Furthermore, crawl data from dealer websites can also give an overview of both the new and used car market by brand, sub-brands, body type by price and inventory, which many times is used as a leading inflation indicator. Social media data in the auto sector can be used to track mentions on specialist websites and Twitter for brands such as Tesla, GM and other auto brands in relation to electric vehicles and other key themes across the globe.
Subcategory - Business Trends Data
Business trends is a catch all sub-category for various alternative data points that can be useful for decision-makers, analysts, and investors seeking to gain a competitive edge in an ever-evolving market landscape. The spectrum of business data is as diverse as the industries it serves, and it extends beyond the confines of traditional data sources. This category of alternative data encompasses a myriad of sources that provide a unique perspective on business trends across different industries. These sources include web scraping/crawling, exhaust data from various business processes, social media, surveys, and more.
Subcategory - Energy Data
Energy data plays a crucial role in the investment process for asset managers, especially those who focus on energy-related industries or integrate environmental, social, and governance (ESG) factors into their investment strategies. Energy data could be collected by tracking global oil and gas cargo flows, or satellite images of oil inventories around the world to understand volumes and inventory, tank capacity or by tracking fracking activities in oilfields
Investors may analyse data related to energy price volatility, supply chain disruptions, or regulatory changes in the energy sector that could impact the financial performance of companies.
Subcategory - Healthcare Data
Medical alternative data encompasses a diverse range of non-traditional sources, such as patient-generated health data, wearables, mobile health apps, social media discussions related to health, and data from electronic health records (EHRs).
Leveraging alternative datasets from alternative data providers, investors can identify promising healthcare startups, assess the efficacy of new therapies, and predict market shifts with greater accuracy. By integrating these diverse alternative datasets into their investment strategies, healthcare investors can make more informed decisions and capitalize on new opportunities in this dynamic sector.
Subcategory - Patent Data
Companies with patents are more likely to introduce commercially successful products. Patent data can be a great alternative data source used to investigate company pipelines and estimate future earning potential. This can include information on the inventors, assignees, and examination history of a patent, as well as the claims and drawings included in the patent document.
Patent data can also include information on the legal status of a patent, such as whether it has been granted, expired, or is currently being litigated. This data is used by asset managers, companies, researchers, and government organizations to track the development of new technologies, identify potential licensing or partnership opportunities and monitor the patent activities of competitors.
Subcategory - Real Estate Data
Real estate investments can take various forms, including residential, commercial, industrial, land, and special purpose properties. Indirect investment can also be made via REITs (real estate investment trusts) or through pooled real estate investment funds.
There are multiple alternative data sources of real estate related alternative data on the market. Web scraped data to see the inventory of what is available, gauge migrations patterns of people. Weather data use cases to understand the impact or likelihood of impact of weather conditions at various asset locations. Location data used to understand where the stores/homes are and find patterns and trends of people/companies moving in or out of neighbourhoods. Much of the pricing data for real estate comes from scrape datasets or through direct relationships with brokers and real estate agents.
Subcategory - Telecommunications Data
The market share figures of mobile telecommunications service providers can be easy to estimate due to signals emitted from mobile phones that are collected by a variety of intermediaries. Furthermore, network quality metrics such as latency, calls dropped, upload & download speeds, the number of cell towers, etc. are also readily available. Another common use case is number portability and switching. Consumers keep their numbers but switch carriers. This can be used to monitor market share. This type of alternative data can be used to track subscriber numbers, including the number of new subscribers, churn rate, and revenue per user. Telecom data can also be used to track the spectrum usage of a telecom company, including the frequencies they operate on and the capacity of their network. Telecom data can also provide information on industry trends, such as the adoption of new technologies and the competitive landscape of the telecom market.
Data Structure
- Data is usually mapped to tickers.
- Depending on the data source, the delivery frequency can range from daily to weekly to monthly. Usually, the data is delivered by the week or by month.
- History can vary and typically dates back at least five years with some vendors up to 10 years.
- Most delivery methods are possible with this type of data, depending on the vendors' capabilities, but the top vendors in this category will be able to deliver to any cloud environment and also via an API.
Compliance Considerations
Business insights data can contain personal information, therefore rules around Personally Identifiable Information need to be observed. These include regulations such as the General Data Protection Regulation (GDPR) in the European Union and the California Consumer Privacy Act (CCPA) in the United States, which both govern the collection, use, and storage of personal data. Business insights data can also be scraped from sources that are open to the public. Because the information is considered to be part of the public domain and because it is not necessary to enter a password in order to view the information, it can be argued that web crawling falls within the realm of permissible activities. However, a user of the data needs to endure that the vendor obtained the data legally and complied with all website T&Cs and most importantly did not scrape anything behind a login or paywall. Any data obtained from third-party sources needs strong diligence on data provenance.