Synopsis: Hedge funds are turning to unconventional signals like private-jet movements, satellite imagery, and online trends to get ahead of the market. Alternative data, once a niche tool, is now reshaping investing strategies worldwide, offering early insights into corporate moves, consumer behaviour, and market trends long before traditional reports emerge.
In today’s markets, information moves fast, but some of the best investing clues still come from places most people never notice. One of the most talked-about examples is a quiet strategy used by some hedge funds, where they watch for unusual movements of private jets to spot early signs of major corporate activity. A plane showing up where it normally shouldn’t, or flying the same odd route again and again, is sometimes enough to get investors whispering.
These small aviation hints have quietly pointed to big corporate moves long before the public hears anything. It is one of the many surprising clues that have pushed investors to explore a rapidly growing new source of insight known as alternative data.
What Exactly Is Alternative Data?
Alternative data, within the world of finance, refers to any information used for investment decision-making that does not come directly from a company’s traditional disclosures. Instead of relying solely on investor presentations, SEC filings or press releases, institutional investors analyse datasets produced indirectly through a company’s daily operations. These datasets can come from varied and often unconventional sources such as financial transactions, mobile devices, sensors, satellite feeds, public databases and digital activity across the internet.
Because these datasets are massive in size and complexity, they usually fall under the broad category of big data. They are often too intricate for simple tools like spreadsheets and require advanced software, machine-learning systems and specialised analytics platforms. Unlike traditional financial data that is clean, structured and publicly issued by a company, alternative data tends to be messy, less accessible and far more unstructured. Yet these characteristics are precisely what make it valuable. It captures real-world business activity in near-real time, offering insights long before official results are published.
Who Uses Alternative Data?
When the use of alternative data started picking up in the mid-2000s, its audience was narrow. Only elite hedge funds with the money and technology to acquire and process these datasets could afford to use them. The costs were steep, and the infrastructure needed to interpret such vast streams of information was prohibitively expensive. As a result, alternative data was once a luxury for high-frequency traders hunting for short-term opportunities.
Over the years, however, the landscape has changed dramatically. Alternative data has now become a standard resource across a wide range of investment organisations. Algorithmic traders and quantitative funds remain the primary users, building sophisticated models that incorporate these unconventional inputs, especially for equity trading. But long-term investors also increasingly rely on alternative data to evaluate companies, spot early trends and take positions based on insights that would have otherwise gone unnoticed.
Beyond public markets, the use of alternative data has spread into private equity and corporate strategy. Industry insiders note that companies themselves use these datasets to guide product decisions, assess competitive threats or benchmark performance. Private equity firms examine alternative data when evaluating acquisition targets or shaping deal strategies. In essence, alternative data has moved from being a niche advantage to becoming a central tool in modern financial intelligence.
What Are the Different Types of Alternative Data?
Alternative data spans a wide spectrum of sources, each offering a different window into economic and corporate behaviour. Some of the most influential categories include:
Web Traffic and App Usage
One of the clearest signals of a digital business’s momentum comes from tracking the flow of visitors and users. Traders analyse whether a software company’s website or application is attracting more users or losing them, or whether an entire category of products is suddenly seeing a spike in online interest. These patterns help investors anticipate growth or slowdown well before earnings reports.
A major provider in this space is SimilarWeb, which supplies extensive datasets covering roughly one billion websites and eight million mobile apps. Its analytics are available through a user-friendly platform or direct API access. In 2021, SimilarWeb became the first alternative-data company to go public, reflecting the growing importance and commercial value of its information.
Social Sentiment and Product Reviews
Investment firms now study social-media behaviour in much the same way marketers track online buzz. For example, Thinknum offers datasets built from platforms like Facebook, tracking follower counts, check-ins and other engagement metrics for over 130,000 companies across more than eight years. Similar datasets exist for other social networks.
Product reviews also hold valuable predictive power. As noted by Thinknum’s media arm, Business of Business, negative reviews for Peloton treadmills using words such as “terrible,” “awful,” “poor,” “bad” or “broken” surged from three in 2019 to 31 shortly before the company recalled the equipment. Investors monitoring such data could have interpreted this as an early warning signal to sell.
Satellite Imagery
Satellite imagery emerged as a powerful financial tool as early as 2009. According to reporting in The Atlantic, RS Metrics used several years of satellite data to test Sam Walton’s belief that counting cars in Walmart parking lots could indicate revenue strength. Although e-commerce has complicated the picture, satellite imagery remains widely used to monitor environmental changes, natural disasters or disruptions that may affect supply chains. With companies like SpaceX and OneWeb driving up satellite launches, the flow of imagery-based insights continues to expand rapidly.
Geolocation Data
Where consumers go reveals a great deal about spending patterns. GPS data transmitted by mobile phones helps analysts study traffic flows, venue visits and overall movement trends. Demand for such information surged in 2020, when pandemic-related disruptions made old forecasting models unreliable. Providers such as SafeGraph saw record interest from financial institutions seeking clarity on how people were behaving in real time.
Although geolocation was once considered less impactful than satellite data, it has become increasingly valuable whenever consumer movement deviates sharply from expectations.
Jet-Tracking and Aviation Data
Tracking private-jet movements is one of the most dramatic examples of alternative data’s predictive power. Jets leave behind digital traces through public flight feeds, transponders and aviation databases. When analysed in the right context, these patterns can reveal early hints of mergers, acquisitions or corporate negotiations. This technique has grown from a niche curiosity into a serious informational advantage for traders seeking to predict high-stakes corporate decisions.
The Jet-Tracking Strategy: How It Works
The Globe and Mail’s “The Data Game” report, authored by Abraham Thomas, recounts how hedge funds discovered the lucrative potential of analysing corporate jet movements. The strategy is intuitive: major transactions such as mergers and acquisitions typically require senior executives and legal teams to meet in person. When they travel discreetly on private jets, those journeys are still recorded in various aviation databases.
Hedge funds began cross-referencing public flight-tracking feeds with aircraft ownership registries, operator licences and corporate-structure databases. By matching tail numbers to specific companies and identifying unexpected or repeated flights to certain destinations, analysts could infer when confidential deal discussions might be underway.
One of the best-known cases involved Johnson & Johnson’s pursuit of Actelion in 2017. A cluster of funds noticed J&J’s Gulfstream jet parked for several days at a Swiss airport located close to Actelion’s headquarters. This unusual detail was interpreted as a strong sign of acquisition negotiations. Those who acted quickly purchased Actelion shares, and weeks later J&J announced a US$30 billion takeover, validating the jet-tracking hypothesis and generating substantial gains for early traders.
Another example featured Encana Corp. Analysts observed the company’s jet landing repeatedly in areas where Newfield Exploration had major oil assets, including Oklahoma, Utah and Montana. At the same time, Newfield’s own jet made unexplained visits near Denver, home to Encana’s CEO. The mirrored travel patterns indicated discussions between the two companies. Shortly after, Encana revealed its US$5.5 billion acquisition of Newfield, further proving the predictive value of aviation-based signals.
Today, subscribers rely on aviation datasets not only to anticipate M&A activity but also to defend short positions against sudden takeover announcements or to monitor wider strategic corporate movements. What began as an unconventional method has evolved into a powerful information advantage, showing that even the sky leaves data trails worth analysing.
Risks, Pitfalls & Ethical Debates
Despite its explosive growth, the alternative-data industry faces significant concerns relating to quality, privacy, fairness and potential misuse.
Inconsistent Quality
Because alternative data comes from many unrelated sources and is used in varied ways, quality can be uneven. The lack of a single regulatory framework means datasets may contain errors or overlook critical scenarios. For instance, if fraudulent activity goes unnoticed in transaction data, it may exaggerate a company’s spending patterns and distort investor decisions.
Lack of Transparency and Trust
Many consumers are unaware of how financial firms gather information about their behaviour. Tracking people’s GPS signals or online actions without clear consent can damage public trust. Companies risk harming customer relationships if data collection practices are not transparent or ethically managed.
Privacy and Security Risks
Alternative data often contains sensitive personal information. Mishandling it can create serious security vulnerabilities. Financial institutions must comply with national and local privacy laws; failing to do so can lead to penalties, reputational harm and long-term consumer backlash.
Variable Manipulation
As alternative data becomes more influential, individuals and companies may try to manipulate their digital footprints. A firm might remove negative reviews, while a consumer may curate their online activity to appear more creditworthy. This intentional distortion can undermine data reliability.
Alternative Data Market Outlook
According to research from Grand View Research, the global alternative-data market was valued at USD 11.65 billion in 2024 and is projected to reach USD 135.72 billion by 2030, representing a remarkably high CAGR of 63.4 percent between 2025 and 2030. This growth is driven primarily by the expanding use of alternative data across investment and financial-services industries worldwide.
North America held a dominant 56.8 percent share of the market in 2024, reflecting the region’s strong fintech ecosystem and advanced adoption of big-data analytics. Demand in the United States continues to surge as financial institutions increasingly integrate alternative datasets into their decision-making frameworks.
Among data types, credit and debit card transaction data commanded a 17.2 percent share in 2024, making it the largest category due to its direct connection to consumer behaviour and spending patterns. In terms of industry adoption, the BFSI sector led the market with a 16.5 percent share, driven by the need for real-time insights in banking, financial services and insurance.
From an end-user perspective, hedge fund operators dominated the space with a substantial 68 percent share in 2024, highlighting their strong dependence on alternative datasets for building trading strategies, identifying market trends and gaining informational advantages.
Looking ahead, Asia Pacific is expected to become the fastest-growing region, fuelled by rapid digital adoption and expanding financial markets. The overall trajectory underscores the increasing centrality of alternative data in the global investment landscape and its growing influence in shaping financial analysis, decision-making and competitive intelligence.
Written by Manan Gangwar
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