Alternative Data Providers: Where to Get Alternative Data for Unique Insights

Key Takeaways

  • Alternative data is increasingly used by financial institutions to gain early and differentiated market insights.
  • Choosing the right alternative data provider depends on scope, accuracy, freshness, cost, and interoperability.
  • High-quality alternative data should be analysis-ready and easy to join with other datasets.
  • Different providers specialize in different data types, making provider selection highly use-case dependent.
  • Geospatial and behavioral data play a growing role in investment research and risk assessment.

Financial institutions are turning more and more to alternative data to predict how the investment market will change from day to day. This data can be all kinds of things: weather, foot traffic, social media trends, news analysis, online transactions, mobile app use, and more.

But where do you find all of this information? Or, to put it more specifically: where do you find this information in a form that’s ready to analyze and pull insights from without needing a bunch of preparatory organization work? That’s what we’ll attempt to answer here by pointing you towards some of the top alternative data providers in business today. Here’s what’s inside:

  • What to look for in an alternative data provider
  • 8 top alternative data providers: leveraging data for deeper insights

Before we get into the best places to get alternative data from, we’ll start with some questions and considerations to keep in mind when evaluating an alternative data source.

What to Look for in an Alternative Data Provider

Not all alternative data companies are equal, at least not for your specific investing strategy. There are a number of factors you should consider when choosing who to source your data from, including the following:

  • Scope– You want to make sure the data provider you choose has a large enough sample size. If your data pool is too small (e.g. constrained to too specific a transaction type or too short a time period), you could accidentally identify what appears to be a unique trend, when a more wide-angle look would tell you that it’s simply an anomaly.

  • Cost– On the other hand, you don’t want to go too wide and incorporate data that isn’t conceivably relevant to the sectors you’re thinking of investing in. You want your data to generate more worth than what you invested in it, so be sure to buy only the data you need. Otherwise, you risk going on a wild goose chase for insights that don’t actually exist, or that have no relevance to your strategy. And that can cost you a lot of wasted time and money. ‍

  • Accuracy – Inaccurate data can lead to costly mistakes, especially in the financial sector where the stakes are often very high. Buy-side and sell-side analysts both need to make detailed reports with recommendations on whether to buy or sell investments. So the data they use to make those reports needs to be correct. ‍

  • Freshness – Even if data is accurate, it may not be as valuable if it doesn’t reflect current real-world conditions. Up-to-date data gives analysts an edge when making their reports, as it ensures they are making financial decisions with the most recent information available. ‍

  • Interoperability– Alternative data is almost always more powerful when connected with other alternative datasets. This is because investment decisions often need to be evaluated from multiple angles, and with various factors taken into account. Datasets that can be easily joined or related to each other make analyzing alternative data that much easier. For example, Placekey provides a standard for identifying places on Earth while avoiding the problem of having to match addresses that use different formats and conventions. ‍

  • Detailed attribution – The more information analysts have at their fingertips, the more precise and comprehensive their recommendations can be. Alternative datasets with many detailed attributes give analysts more to work with when generating their models and reports.

8 Top Alternative Data Providers: Leveraging Data for Deeper Insights

1. SafeGraph

Cost: charged on a per-dataset basis
Major data types: points of interest, building footprints
Key use cases: retail investment, consumer insights, risk assessment, real estate investment

SafeGraph is one of the top alternative data providers for points of interest. Our datasets include detailed information and accurate spatial representations of millions of commercial buildings, historic monuments, and other landmarks globally.

2. HARNESS Data

Cost: $0.005/record; charged on a per-dataset basis
Major data types: internal documents and communication, address, property, points of interest
Major use cases: real estate investment, insurance risk assessment, logistics planning, fraud prevention

Harness Data provides three distinct services. First, their PDFx tool allows for extracting actionable data points out of PDF files. This can include elements such as images, contact information, organization names, tables & schedules, and more.

3. Veraset

Cost: contact for pricing
Major data types: foot traffic, visit attribution
Key use cases: retail investment, real estate investment

Veraset provides two sets of alternative data: Movements and Visits. Movements uses multiple sources to get an estimate of human traffic around points of interest in over 150 countries around the world.

4. Transparent

Cost: $0.05/record; charged on a per-dataset basis
Major data types: vacation rental properties
Key use cases: real estate investment, hotel competitor research, tourism marketing

The short-term rental market has exploded since the introduction of rental property booking websites like Airbnb and HomeAway. With that in mind, Transparent was created to provide a granular breakdown of what’s on the rental housing market.

5. Vertical Knowledge

Cost: $800-$7,000/month (average is $2,500-$3,000/month)
Major data types: automotive transactions, online transactions, home rentals, company metrics
Key use cases: real estate investment, automotive investment, equity research, employment trends

Vertical Knowledge stands out among alternative data vendors by specializing in the privacy-compliant collection of publicly-available information on the internet.

6. Greenwich.HR

Cost: $0.05/record; charged on a per-dataset basis
Major data types: financial, employment
Key use cases: workforce analytics, talent acquisition and management

In addition to having standard financial data, Greenwich.HR is one of a handful of alternative data firms that has data on corporate hiring practices.

7. Infutor

Cost: $8,000-$10,000/month
Major data types: real estate, automotive transactions, consumer demographics, email
Key use cases: equity research, automotive investment, consumer insights, real estate investment

8. ClimateCheck

Cost: $0.05/record, charged on a per-dataset basis
Major data types: environment, weather, real estate
Key use cases: real estate investment, risk assessment

ClimateCheck is a unique entry in our list of alternative data providers. It combines US property data with historical weather and climate data, processed through over 25 aggregated international climate change models.

FAQ’s

  1. What is alternative data in investing?
    Alternative data refers to non-traditional datasets such as foot traffic, transactions, weather, employment, or location data that help investors gain insights beyond standard financial reports.

  2. Why do investors use alternative data providers?
    Alternative data can reveal trends earlier, validate assumptions, and provide real-world signals that traditional financial data may miss.

  3. How do you evaluate an alternative data provider?
    Key factors include data accuracy, coverage, update frequency, ease of integration, cost, and relevance to the investment strategy.

  4. Is alternative data always better than traditional data?
    No. Alternative data is most powerful when combined with traditional financial data and used with a clear analytical objective.

  5. Can alternative datasets be combined?
    Yes. Interoperable datasets that can be easily joined often produce more valuable insights than isolated data sources.