# Alternative data sources: what they are and how to read them > A plain-English guide to alternative data sources: what alternative data means, the six main types, who actually buys them, and how to judge any source before you trust it. By Maya Koeva · 2026-08-20  **Alternative data** is any information about a company that does not come from the company itself or from the market's official feeds. Filings, earnings calls, prices, and analyst reports are the traditional diet. Alternative data is everything else that leaves a measurable trace: credit card swipes, satellite photos of parking lots, job postings, app downloads, and what thousands of people are saying online. A company reports its quarter once every three months, but the quarter itself happens every day, in stores and on websites and in hiring plans. Alternative data sources are attempts to watch it happen instead of waiting for the announcement. ## What counts as alternative data Traditional data is whatever every investor receives on a schedule: quarterly reports, SEC filings, price and volume, official economic releases. Alternative data is the exhaust a business gives off between those announcements. The differences fit in one table: | | Traditional data | Alternative data | |---|---|---| | What it is | Filings, earnings, price and volume | Card swipes, satellites, job posts, chatter | | Arrives | On a schedule, quarterly | Continuously, as business happens | | Audited | Yes | No | | Who sees it | Everyone, at the same moment | Whoever collects it | | [Priced in](/learn/what-does-priced-in-mean) | Almost instantly | Slowly, if at all | The last two rows are the appeal and the catch in one: alternative data can be early because few people see it, and it can be wrong in ways nobody checks. ## The main alternative data sources Six types cover most of what gets bought and sold under this label: | Source | What it watches | The famous case | |---|---|---| | **Transaction data** | Card-panel spending at consumer companies, weeks before the earnings call | Bloomberg's Second Measure: a panel of more than 20 million US consumers, updated within days of the swipe | | **Web and app activity** | Traffic, downloads, daily active users, review counts | Snapchat's 2018 redesign: one-star reviews and falling downloads preceded the first reported drop in daily users | | **Satellite and location** | Parking lots, ports, oil-tank shadows, foot traffic | Analysts counted cars in Walmart parking lots to estimate quarterly sales ahead of the report | | **Hiring data** | Job postings and headcount changes | Apple's car project surfaced in 2015 when reporters traced a hiring spree of automotive and battery engineers | | **Supply chain records** | Customs manifests and bills of lading | Panjiva and ImportGenius index public US import records, shipment by shipment | | **Social sentiment** | What investors say in public, and who says it | GameStop, January 2021: the trade came together in threads anyone could read | Two things the table understates. Each source has a blind spot the vendor rarely advertises: the cards in a panel may not shop like the average customer, and a job posting can mean a new product line or a backfill. And the six are not equally reachable: the first five are institutional products, while the sixth sits in public, the most accessible source on the list and the noisiest. We wrote a full explainer on [market sentiment](/learn/what-is-market-sentiment). ## Who buys alternative data Mostly not individuals. The classic buyers are hedge funds, buying through specialist vendors on contracts that run five or six figures a year. A large fund might subscribe to dozens of datasets and employ a team to clean and test them. The "multi-billion-dollar alternative data industry" you read about is funds buying from vendors, not apps for retail investors. Not all of it is locked up, though. Some of the most useful sources were never behind a paywall: job postings, app reviews, search trends, and public conversation are all free to anyone willing to read them carefully. The barrier for individuals is the reading, not the access: separating signal from noise takes work that funds pay teams to do. ## How to judge any alternative data source Whatever the source, the same five questions decide whether it deserves your trust: 1. **What does it see?** Every source covers a slice, never the whole. A card panel sees its cards, a sentiment feed sees the accounts it follows. And when a source shows nothing, ask which kind of nothing it is: did it watch and see nothing, or did it not watch? 2. **Is it early, or just different?** A dataset only helps if it moves ahead of the reported numbers. Some alternative data restates what the price already knows, with extra steps. 3. **Who is in the sample?** Panels skew young or urban, app data skews tech-savvy, social data skews loud. Each skew is a way to be confidently wrong. 4. **Has it been graded?** The only fair test of a signal is its record against real outcomes. A source that has never been [scored against what happened](/learn/how-a-track-record-is-graded) is a story, not a signal. 5. **What happens when everyone has it?** The more widely a dataset is sold, the faster its edge gets traded away. Yesterday's exotic satellite feed is today's consensus input. ## Where Quantral fits Social sentiment is the one alternative data source individuals can reach, and raw, it fails most of the five questions above: unknown sample, no grading, and a volume of noise that [buries the signal](/learn/volume-vs-signal). Quantral's approach is to treat it the way a fund would treat any raw dataset. We track a defined set of accounts across [finance X](/learn/what-is-fintwit), Reddit, and Substack, grade every directional call those accounts make against what the stock did, and weight the conversation by each account's [credibility score](/learn/what-is-a-credibility-score). The result is one alternative dataset, cleaned and graded, readable [at a glance](/learn/what-is-a-stock-signal), without the fund-sized contract. What that gives you in practice, from our own published write-ups: | The job | What the graded data showed | |---|---| | **Holding through fear** | Nebius fell 48% and [the accounts with records held close to 8-to-1 bullish through the whole drawdown](/blog/nebius-stock-sentiment); the stock came back 75% off the low | | **Telling a hot sector's names apart** | Headlines treated the memory trade as one story, while [graded calls ran 3.5-to-1 bullish on Micron and 2-to-1 bearish on Western Digital](/blog/memory-stocks-stock-sentiment); the two stocks went different ways | | **Catching a turn** | SpaceX scored 19 for a month, then [flipped to 77 while the raw crowd stayed two to one bearish](/blog/spacex-stock-sentiment); it cleared its lockup, up 21.8% since the post ran | | **Vetting a voice you follow** | The chip leaker [jukan05 grades out at 58.6% right across 70 calls](/blog/who-is-jukan05), third on our six-month accuracy board, and wrong roughly four times in ten | The first row of that table, drawn from the raw feed, looks like this: *[Chart: Nebius mentions across the accounts Quantral tracks, July 14 to August 12, 2026, spanning the last leg of a 48% drawdown and the rebound off the July 29 low. Green is bullish, red bearish. The red band never takes the day.]* ## The bottom line Alternative data is any measurable trace of a business outside its official reporting: transactions, traffic, satellites, hiring, shipping, and conversation. Most of it is built for and sold to institutions, but the mindset behind it is free to borrow: watch the quarter happen instead of waiting for it, know what your source can and cannot see, and do not trust a signal nobody has graded. --- *Quantral surfaces signals and context from public sources to support your own research. Nothing here is financial advice or a recommendation to buy or sell.*