But machine learning algorithms are playing a bigger role because there’s so much more and different information available. Asset managers are forecast to spend $1.7 billion this year on alternative data — facts and figures compiled by sources other than companies, government agencies and the like — compared with $232 million in 2016, according to AlternativeData.org, an association of analysts and engineers. That’s just on data, not the hardware and software that analyze it.

A report from the investment management firm Neuberger Berman detailed how the company uses such nontraditional data. It included scouring credit card receipts to see if men are shopping at Lululemon, a clothing chain viewed as a destination almost exclusively for women, and collating social media posts to get a clue whether Procter & Gamble’s employees approved of a major revamping effort. The fund provider also cited a program that evaluates natural speech for phrases that have correlations with future share price performance.

Causeway Capital Management, in a report of its own, said it used big data to help forecast the outcome of the 2019 parliamentary elections in India by hiring local people to classify 10,000 Twitter messages. That effort trained a machine-learning model that then did the same with many more tweets. Causeway said the exercise allowed it to anticipate a better-than-expected showing for the ruling coalition. Indian stocks shot up after the election, far outperforming emerging markets generally.

Causeway has also predicted stock price movements through so-called nowcasting: generating real-time statistics of one sort or another. By buying data from a vendor that tracked the use of apps on 1.3 billion Chinese phones, for instance, Causeway said it was able to gauge how popular the companies behind each app were and how their stocks were likely to perform.

“The sheer diversity of data is much larger than before,” said Jeff Shen, co-head of systematic active equity at BlackRock, which uses big data to analyze earnings reports and analyst calls, and study online search patterns relevant to certain businesses.

“Using new data sources allows us to predict macrotrends or future cash flows of companies better” than conventional research methods, Mr. Shen said. “It allows us to ask better questions we had not thought about asking.”

They are questions that continue to be asked under the current extraordinary market conditions. Throughout the stock market plunge, the alternative data that BlackRock uses “is providing valuable high-frequency information that is a timely reflection of what’s going on in the economy,” Mr. Shen said. “The additive nature of the data allows investors to dynamically navigate through the current market volatility.”