‘Alternative data’ is a term that has become popular in the financial sector, as investors shift their attention away from quarterly earnings reports and press releases as exclusive sources of finance information. Instead, they’re looking for additional information that’s more readily available and can let them see the performance of potential assets through different lenses.
But where can they find this alternative data? What can (and can’t) it tell them? And how do they know the product they’re getting is correct, timely, and privacy-sensitive? We’ll explore these questions as we explain where to buy alternative data through the following sections:
We’ll start with a fuller explanation of what alternative data is and why it’s worth using.
Alternative data refers to financial analysis data a company sources from non-traditional areas. In other words, the company doesn’t create this data via its own operations, nor does it collect this data from official financial information outlets (such as news releases and government-mandated reports).
So why should you, as a financial analyst, use alternative data? The answer has to do with the fact that, comparatively speaking, official financial data is limited in scope and published rather infrequently. That is, it doesn’t provide many contextual signals as to why a company’s financial situation is going in the direction it is. And by the time the data is released, you’ll likely be scrambling to react to major financial shifts as they’re happening.
Alternative data, meanwhile, can provide clues about a company’s performance that may be more closely linked to its on-the-ground operations. These include things such as visits to its brick-and-mortar stores, or what its official accounts on social networks are posting. Alternative data is also produced much more often. So if you monitor it and analyze the trends you find in it, you may be able to predict major market events and prepare for them long before they are officially announced.
Alternative data use cases can generally be categorized according to the two major financial analyst role groups: buy-side and sell-side.
So where do analysts actually find the alternative data they need to carry out these functions? We’ll recommend some places in the next section.
There are all different kinds of alternative data out there: credit and debit transactions (online or offline), social media activity, mobile app usage stats, and even geospatial factors like weather or traffic. You need to find sources that are thorough, accurate, up-to-date, affordable, and privacy-compliant. Here are 23 of our top suggestions.
Major data types: points of interest, building footprints, foot traffic, transactions
SafeGraph provides detailed information for millions of locations around the world. We also build data that adds additional context to what happens at those locations, such as consumer foot traffic. Our Spend dataset gives anonymized transaction reports (both online and offline) for specific stores and brands in the US.
You can use our data for things like understanding consumers’ shopping habits and relationships with different stores and brands, as well as the relationships between the stores and brands themselves. You can also monitor how much patronage businesses get through visit attribution.
Major data types: property
BA45 has data on the specifications of over 125 million US land parcels. These specs include details from how many buildings are on a parcel and who owns those buildings (or the overall parcel) to how many rooms are in a building and what its walls are made out of. This all makes BA45’s data great info for performing due diligence if you’re thinking about investing in either commercial or residential real estate. It’s really affordable, too.
Major data types: imagery, roads
Microsoft’s search engine, Bing, has a map feature that includes the ability to see road networks and either aerial or satellite imagery for most places on Earth. It also has interactive street-level panoramic views for many US locations, as well as some locations in Europe and Canada. It’s a free and handy tool for scouting out real estate and business opportunities in an area based on how accessible the area is, what businesses are already there, and what the lay of the land looks like.
Major data types: point of interest and property (retail stores, restaurants, and shopping centers)
CAP Locations has general, real estate, and building footprint data for over 1.2 million retail stores and restaurants in the US and Canada. That includes up to 300 information attributes, including things like parking lot capacities and when a business was opened (or renovated). CAP Locations also has spatial hierarchy metadata on over 40,000 shopping centers, including polygon-based geofence models for about half of them. So it’s helpful for those investing in malls (or certain brands common to malls) who want to know what kinds of businesses will likely succeed there, based on local shopping patterns.
Major data types: demographics, human mobility, transactions, housing, road traffic, points of interest, environment, geography, social behavior
Originally an environmental conservation project, CARTO has grown into a leading alternative data hub. It features over 10,000 datasets from over 40 partnered data providers, most of which are geospatial in nature – human mobility, road traffic, local demographics, housing data, etc. These include over 750 pre-mapped datasets designed for specific analyses. In short, CARTO’s platform allows you to use many different types of alternative data towards pretty much any kind of financial analysis you’d want to do.
Major data types: real estate; weather and environment
Those considering investing in residential real estate in the US should definitely have a look at ClimateCheck. It combines property data on over 140 million US homes with historical US weather data, extrapolated over the next 30 years based on over 25 international climate change models. This allows ClimateCheck to offer an assessment of how vulnerable a property is to weather-related damage or destruction, including wildfires, storms, and floods.
Major data types: weather and environment; satellite imagery
CustomWeather offers a variety of weather data solutions. It has current and real-time condition monitoring; short-term and long-term forecasting; airport delay forecasting; severe weather tracking; maritime conditions and travel routes forecasting; satellite imagery; and historical weather comparisons for over 8,500 places worldwide. It also has special reports for things like sun & moon cycles, wildfire danger, ski conditions, and air quality.
Weather can impact all kinds of industries, and affects certain geographic areas more than others. So checking alternative data on it from a company like CustomWeather can help you mitigate risk in terms of what you invest in, and where.
Major data types: satellite imagery, demographics, transactions, social behavior, corporate summaries, environmental, foot and vehicle traffic, properties, points of interest, boundaries
Similar to CARTO, Esri is a rather catch-all company when it comes to places to buy alternative data – and geospatial data in particular. Its software platform, ArcGIS, is one of the most powerful mapping and location analysis tools available. A major reason why is that Esri has filled it with all kinds of alternative data you can analyze, from property details and satellite pictures to company summaries and consumer spending habits. So ArcGIS can be customized to support any kind of geography-based financial analysis you need.
Major data types: property
First American Data & Analytics offers comprehensive property data that covers the entire US housing market. Much of its data relates to legal and ownership matters, such as sale prices, property taxes, mortgages, and foreclosures. But it also has data on property elements such as basic location and characteristics, land use zoning, flood vulnerability, and school catchment area. All of this is usable information for assessing the potential value or risk (either physical or financial) of investing in real estate or homeowners for a specific property.
Major data types: finance, employment statistics
Greenwich.HR’s specialty is data on worldwide labor markets. Its data lets you look inside the hiring practices of over 5 million companies across over 200 countries. See things like how much new talent a company is looking to onboard, which kinds of positions are in demand, and what salary ranges for specific positions look like (Greenwich.HR boasts a nearly 80% completion rate for this in its data). Data like this can give you a different perspective on what kinds of companies are likely to be successful in the near future.
Major data types: Points of interest, property, and address (UK); PDF documents
HARNESS Data’s “Addressable” dataset is the most comprehensive list of points of interest, property details, and addresses in the UK. In fact, HARNESS Data is so sure that its product is the best that it offers, as a free sample, a list of prices per square meter for over 16 million pieces of real estate across England and Wales. So if you’re investing in the British Isles, you’ll want to go to HARNESS Data to get alternative data.
HARNESS Data also sells a tool called “PDFx” that extracts data points from PDF document files, which can help speed up manual research.
Major data types: property, demographics, phone & email communication, automotive & other transactions, addresses
Infutor is the authority on the economic activity of over 260 million Americans, and sells alternative data on many different subjects. These include car sales, phone & email communications, consumer demographics & purchases, and property attributes & addresses. Infutor’s wide variety of datasets can be useful whether you’re investing in real estate, automotives, telecommunications, or other specific businesses.
Major data types: footfall, brand affinity
Locomizer’s main offering is foot traffic data around points of interest in the UK. What sets them apart, however, is their brand affinity estimate dataset. This uses a blend of footfall data and mobile application use data, fed through a machine learning algorithm, to determine how likely a person in a particular place at a specific time is to engage in a brand-related activity. That could be eating at a particular restaurant chain, watching a specific athlete or sports team play, taking a branded mode of transportation somewhere, and so on. This is very valuable for investors to know not only that people gather in certain locations, but also make educated guesses as to why they might be there and what they might do.
Major data types: boundaries, road networks & traffic, human mobility
Mapbox’s geospatial data is sourced from hundreds of platforms, fed by over 500 million monthly active users. That’s why it’s confident that it has the most accurate global datasets for over 4 million administrative boundaries, 20 billion daily human mobility updates, and over 30 billion road segments worth of typical and live traffic data. Mapbox’s data is great for real estate portfolio management, accessibility and logistics analysis, demand forecasting, impact modeling, and more.
Major data types: property
Regrid is a superb place to purchase alternative data if you’re investing in US real estate. It has up to 120 attributes worth of details on over 150 million US land parcels across over 3,000 counties. That includes over 155 million polygon-based building footprints. Regrid has flexible pricing options for its data, so if you’re only interested in properties within a certain area of the US – or certain details about them – you can choose a data package tailored and priced to suit your needs.
Major data types: social media, demographics
Spatial.ai takes data on social media activity, particularly posts where the user identifies where they’re posting from, and blends it with US demographic data. The result is what it calls “geosocial profiles”, approximations of people’s lifestyles in US census block groups based on activity indicated on social networks as being from nearby locations. These profiles can be very useful for investors trying to figure out what businesses are popular, or are likely to be successful, in specific US neighborhoods.
Major data types: weather and environment
Tomorrow.io’s software platform and data are designed to help businesses plan and work to minimize disruptions to their operations caused by weather. With historical weather data for millions of places around the world, this is definitely a company to check out if you’re looking to get alternative data for factoring weather into your financial analysis.
Major data types: short-term rental properties
Transparent’s data focuses on short-term property rentals, with over 50 data attributes on over 35 million listings around the world. Now that the industry has gone mainstream with the advent of businesses like Flipkey and Airbnb, it can be important to pay attention to if you have certain investment objectives. It’s obviously a factor in real estate investment, but it can also be one for travel and tourism investment as many people rent these properties for vacations. Hotel financiers can also see the degree of competition their selected sites are getting.
Major data types: boundary, property, and nearby demographic information for parks
The Trust for Public Land is an expert on public parks data, as it’s committed to conserving and expanding natural spaces for public recreational use. It offers free data on property information and geographic boundaries for parks in over 14,000 communities across the US. It also tracks some demographic attributes of populations who live near parks. This could be useful to investors for understanding the public recreation habits of people who live in a defined geographic area.
Major data types: demographics, boundaries
SafeGraph provides a cleaned-up version of the US Census Bureau’s American Community Survey, suitable for a bulk data download. The report includes geometric representations of US census block groups, as well as over 7,500 demographic attributes of the people who live within those neighborhoods. This is incredibly valuable information for investors to understand who consumers are in a given area of the US, and thus which businesses they are likely to patronize.
Major data types: points of interest, boundaries, roads & transportation, addresses
The US Department of Transportation’s National Address Database project has recorded over 65 million confirmed US street addresses. Investors could use this to verify location details of businesses and real estate assets in the US. A sub-organization of the USDOT, the Bureau of Transportation Statistics, also has all sorts of pre-mapped datasets that can be analyzed for transportation investment or assessing the accessibility of places. And all of this data is free and publicly available.
Major data types: property, foot traffic
Veraset gives you a choice of two geospatial datasets. Its “Movement” dataset covers over 150 countries around the world, using hundreds of billions of anonymized GPS signals to track daily footfall around various points of interest. Its “Visits” dataset currently only covers the US, but combines foot traffic data with precise polygon property models to count daily visits to over 6 million businesses. Either dataset is handy if you’re looking at a company’s performance through the lens of how busy locations near their stores get, but “Visits” in particular makes it easy to attribute visits to a specific store.
Major data types: online purchases, property rentals, transportation transactions, corporate insights, points of interest
Vertical Knowledge is another company that has a little bit of all different kinds of alternative data, as it sources its datasets from what’s publicly available on the Internet. You’ll find data there on things like best-selling books, air travel, cruises, car rentals & purchases, short-term housing rentals, company summaries, and retail points of interest. So whatever your investment strategy, you’ll likely find some alternative data from Vertical Knowledge that will provide you with insights.
Hopefully you now have a better idea of what kinds of alternative data are out there, and where some of the most reliable places to get it from are.