Market intelligence is information about companies, industries, science and trade, gathered from filings, shipment records, patents and the public web, and sold by subscription. Strategy teams, investors, lenders and research offices buy it to understand what is happening outside their own company.
Consider an electric scooter maker in Hosur that is planning its next model. It wants to know five things, and each answer comes from a different kind of data.
What did its listed rivals tell investors last quarter? A financial research platform searches company filings and transcripts of results calls. A language model then summarises what each rival said about prices and battery costs.
How many scooters did each brand sell last month, and in which regions? Automotive market data collects vehicle registrations and forecasts of future sales.
Who imports battery cells into India, and from which suppliers? Global trade data, built from customs shipment records, answers this.
Who already holds patents on the battery cooling design that the company wants to use? Citation and patent databases list patents, and the research papers that cite each other.
What prices are rivals charging on their websites and on marketplaces this week? A web scraping service copies the prices from public pages every day.
A sixth kind of data, alternative data, is bought mainly by investment funds. It uses signals such as card spending to estimate a company's sales before the company reports them.
All of these are examples of data as a service (DaaS). The vendor collects data from many sources, matches it every day and sells the dataset itself. The biggest change is that buyers increasingly do not search the data themselves. An AI data analyst has read the whole dataset, and it answers the question directly. The best-known financial datasets are sold through financial data terminals, and records of how businesses repay their debts through credit bureaus.