Reelgood for Education & Research
Streaming Industry Data
for Academic Research.
Reelgood supplies the underlying data for academic and institutional research on the streaming industry: what exists, where it streams, when it arrived, when it left, and how that differs across 300+ services and 25+ countries. Bring a research question, and Reelgood will scope the dataset that answers it.
Researchers at these institutions have licensed Reelgood data for research
The Data
One dataset, built on a canonical title structure.
Reelgood data carries all of the elements below, and every one of them resolves to the same title, season, and episode identifiers. Catalog, availability, metadata, and popularity join cleanly without manual reconciliation. Extracts are scoped to the elements, services, countries, and date range your study actually needs.
Streaming catalog data
The full catalog of every tracked service, refreshed continuously. Study catalog size and composition, how libraries turn over month to month, and how much any two services overlap.
Title availability and windows
Where a title streams and on what terms, with exact open and close dates for each window. Historical availability reaches back up to seven years depending on the market, which supports longitudinal work on licensing, exclusivity, and churn.
International coverage
The same catalog and availability structure across countries, so a single title can be traced market by market. Useful for comparative media studies and questions about how content travels between territories.
Extensive title metadata
More than 4MM titles carrying cast and crew, production companies, release dates, runtimes, ratings, awards, genres, descriptive tags, imagery, and a canonical show, season, and episode hierarchy.
Popularity signals
Title level popularity scores and weekly Top 10 rankings, drawn from Reelgood's consumer application audience across web and mobile. These let you pair what is available with what people are actually watching for.
Identifier crosswalks
Reelgood identifiers map to industry standard identifiers like EIDR and others, so a Reelgood extract merges with box office, ratings, awards, or survey data you are already working with.
For field level detail, see the Reelgood Sample Data Export spreadsheet, which lists every available field with a tab per data folder.
Research Angles
Questions this data is built to answer.
Reelgood data has supported work across media economics, communication studies, computer science, and public policy. A few directions researchers have taken it, offered as starting points rather than a menu.
Licensing economics and windowing
How long titles stay on a service, how often they move, and what exclusivity is worth. Window open and close dates make licensing behavior measurable rather than anecdotal.
Market structure and consolidation
Catalog overlap, concentration, and differentiation across services, before and after mergers. Historical catalogs let you measure what actually changed rather than what was announced.
Global content flows
Which titles cross borders, how quickly, and in which direction. Country level catalogs across markets support comparative work on cultural trade and local content requirements.
Representation and genre studies
Genre and tag taxonomies applied consistently across millions of titles, joined to cast, crew, and production company records, for content analysis at a scale manual coding cannot reach.
Access, cost, and policy
Which titles a viewer can actually watch with a given set of subscriptions, how much of the catalog sits behind ad supported versus paid tiers, and how that mix shifts over time.
Recommendation and ML research
A large, clean, entity resolved corpus for work on catalog search, entity matching, and recommendation, including the messy real world case of the same title appearing across many services and markets.
For a wider view of how this data gets applied outside the academy, see Reelgood's streaming data use cases.
Access
Reduced academic and research pricing.
Reelgood offers reduced academic and research pricing for non-commercial work at accredited institutions and non-profit research organizations. Pricing depends on the scope of the extract, the countries and date range involved, and whether the project needs a one-time dataset or ongoing delivery.
Data arrives in the format that fits the project: CSV or JSON exports, scheduled S3 delivery, or API access for work that needs to query continuously. In return for the reduced rate, we ask that Reelgood be credited as the data source in any resulting paper, presentation, or publication.
Tell Reelgood what you are studying rather than which fields you want. Most projects are scoped faster that way.
Who qualifies
- Faculty and research staff at accredited colleges and universities
- Graduate and undergraduate students working on a defined research project or thesis
- Instructors using streaming data in coursework
- Non-profit research institutes, think tanks, and journalism research desks
Please request access from an institutional email address and include a short description of the project. Commercial and consulting work is priced under Reelgood's standard enterprise terms.
Step 01
Describe the project
Send the research question, the institution, and the rough timeline. A paragraph is enough to start.
Step 02
Scope the dataset
Reelgood's team maps the question to specific fields, services, countries, and date ranges, then quotes the academic rate.
Step 03
Receive the data
Delivery by export, S3, or API, with documentation covering the schema, the methodology, and the known limits of the data.
Questions
Common questions from researchers.
Historical availability data reaches back up to seven years, with depth varying by geography and by service. The exact date range available for your markets is confirmed during scoping, before anything is committed to.
Yes. Findings derived from Reelgood data can be published, presented, and cited freely. We ask that Reelgood be credited as the data source, which is part of what makes the reduced academic rate possible. Redistribution of the raw dataset itself is handled separately in the data agreement, so mention it upfront if your funder or journal requires an open data deposit.
CSV and JSON exports for one-time extracts, scheduled delivery to an S3 bucket for recurring pulls, and REST API access for projects that need to query continuously. Every delivery ships with schema documentation. The S3 export documentation covers the folder structure, file relationships, and record counts in detail.
Reelgood data is highly accurate. Availability is verified against direct service feeds, third party catalogs, and machine learning matching, then refreshed continuously rather than on a weekly batch. For an outside reference point, Reelgood's analysis of LLM streaming availability accuracy measured how far general purpose models drift on the same questions. Methodology notes and known limitations ship with each delivery, so they can be described accurately in a methods section.
The same data runs in production at leading streaming services, studios, content distributors, technology companies, and search engines, where it powers where-to-watch answers, catalog operations, and competitive analysis. Academic projects work from that production data rather than a stripped down sample of it.
Tell us what you're researching.
Send the research question, your institution, and a rough timeline. Reelgood's team will come back with the dataset that fits and the academic rate for it.
Please use an institutional email address where possible.
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© Copyright 2026. All rights reserved.
T&C | Privacy Policy