Forecasting retail sales just got smarter, thanks to Google searches

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Search trends predict future retail revenue up to three quarters in advance. Photo via Pexels

Imagine being able to predict the future of retail sales — not with months-old economic reports, but with real-time digital breadcrumbs left behind by consumers. Thanks to new research from K. Ramesh (Rice Business) and Gary Lind (University of Pittsburgh), that future is already here.

Key findings

  • Search trends predict future retail revenue — up to three quarters ahead.
  • Markets don’t fully price in search-based insights, especially before earnings announcements.
  • Trading strategies using search data outperform traditional asset-pricing models by 2–3%.
  • Analysts often underuse this data, resulting in predictable forecast errors.
  • At the macro level, search trends closely track — and often lead — official retail sales and GDP.

Their study shows that Google search trends are powerful predictors of consumer demand, capable of forecasting U.S. retail sales up to three quarters in advance. The implications span industries and audiences — from Wall Street traders to Main Street retailers, and from data-driven CFOs to curious business students.

A smarter, faster crystal ball for retail demand

Retail sales drive nearly 70% of U.S. gross domestic product (GDP), making them one of the most important indicators of economic health. Yet traditional forecasting relies heavily on backward-looking data and broad economic indicators. Ramesh and Lind’s work offers a leap forward: search data from Google Trends — publicly available and easy to use — can offer a faster, more precise signal of where sales are headed.

“If you want to understand consumer demand,” says Ramesh, the Herbert S. Autrey Professor of Accounting at Rice Business, “look at what people are searching for — not just what companies report after the fact. These digital footprints can tell us where revenue is going, often before the market catches up.”

This low-cost approach stands in stark contrast to expensive alternatives, such as satellite images of parking lots, in-store foot traffic from mobile data, or retail scanner feeds — tools often reserved for hedge funds and large institutional investors. Google Trends offers a scalable, accessible option for anyone seeking insight into consumer behavior.

Why this matters for investors and analysts

The researchers analyzed search patterns for nearly 200 publicly traded U.S. retail companies between 2004 and 2019. They found that firms with rising search volumes tend to report higher revenues — often well before analysts or investors react.

In fact, investment strategies built around these trends earned 2–3% higher returns than traditional models would predict. And most of these gains were concentrated around earnings announcements — a sign that markets were slow to recognize what search data had already revealed.

The advantage is even more striking for companies that fly under Wall Street’s radar. For firms with limited analyst coverage, the predictive power of search data on stock performance was more than 80% stronger.

A new tool for analysts — if they’ll use it

Despite the clear signal in the data, the study finds that analysts routinely fail to incorporate search-based insights into their forecasts. That gap translates into missed revenue predictions and market inefficiencies — which sophisticated investors can exploit.

“The search data are out there,” says Lind, a Rice Business Ph.D. ’19 graduate now on faculty at Pitt Business. “They’re public, powerful, and free. Analysts who ignore them are missing an opportunity.”

The impact of this research extends well beyond equity markets. By aggregating Google search data across the retail sector, the authors found strong alignment with U.S. Census retail sales figures and GDP trends. In other words, these digital signals reflect not just firm-level interest, but macroeconomic momentum.

A data wake-up call

This makes search trends a potentially valuable early-warning system for policymakers, central banks, and anyone responsible for interpreting the economic landscape. During volatile or uncertain periods, such tools could offer precious foresight into shifting consumer behavior.

In a digital era where consumers research before they shop — whether online or in-store — it’s no surprise that their Google queries leave valuable clues. What’s surprising is how often businesses, investors, and even economists still overlook them, Ramesh says. “Search data is a goldmine. And it's just sitting there, waiting to be used.”

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This article originally appeared on Rice Business Wisdom.

Lind and Ramesh, “Using Internet Search Data to Predict Aggregate Retail Sales and Enhance Firm-Level Revenue Expectations,” Contemporary Accounting Research (April 2025): 1-32. https://doi.org/10.1111/1911-3846.13043.

There's no crystal ball, but this researcher from Rice University is trying to see if some metrics work for economic forecasting. Photo via Getty Images

Houston researcher tries to crack the code on the Fed's data to determine economic outlook

houston voices

Research by Rice Business Professor K. Ramesh shows that the Fed appears to harvest qualitative information from the accounting disclosures that all public companies must file with the Securities and Exchange Commission.

These SEC filings are typically used by creditors, investors and others to make firm-level investing and financing decisions; and while they include business leaders’ sense of economic trends, they are never intended to guide macro-level policy decisions. But in a recent paper (“Externalities of Accounting Disclosures: Evidence from the Federal Reserve”), Ramesh and his colleagues provide persuasive evidence that the Fed nonetheless uses the qualitative information in SEC filings to help forecast the growth of macroeconomic variables like GDP and unemployment.

According to Ramesh, the study was made possible thanks to a decision the SEC made several years ago. The commission stores the reports submitted by public companies in an online database called EDGAR and records the IP address of any party that accesses them. More than a decade ago, the SEC began making partially anonymized forms of those IP addresses available to the public. But researchers eventually figured out how to deanonymize the addresses, which is precisely what Ramesh and his colleagues did in this study.

"We were able to reverse engineer and identify those IP addresses that belonged to Federal Reserve staff," Ramesh says.

The team ultimately assembled a data set containing more than 169,000 filings accessed by Fed staff between 2005 and 2015. They quickly realized that the Fed was interested only in filings submitted by a select group of industry leaders and financial institutions.

But if Ramesh and his colleagues now had a better idea of precisely which bellwether firms the Fed focused on, they still had no way of knowing exactly what Fed staffers had gleaned from the material they accessed. So the team decided to employ a measure called "tone" that captures the overall sentiment of a piece of text – whether positive, negative, or neutral.

Building on previous research that had identified a set of words with negatively toned financial reports, Ramesh and his colleagues examined the tone of all the SEC filings accessed by Fed staff between one meeting of the Federal Open Markets Committee (FOMC) and the next. The FOMC sets interest rates and guides monetary policy, and its meetings provide an opportunity for Fed officials to discuss growth forecasts and announce policy decisions.

The researchers then examined the Fed's growth forecasts to see if there was a relationship between the tone of the documents that Fed staff examined in the period between FOMC meetings and the forecasts they produced in advance of those meetings.

The team found close correlations between the tone of the reports accessed by the Fed and the agency’s forecasts of GDP, unemployment, housing starts and industrial production. The more negative the filings accessed prior to an FOMC meeting, for example, the gloomier the GDP forecast; the more positive the filings, the brighter the unemployment forecast.

Ramesh and his colleagues also compared the Fed's forecasts with those of the Society of Professional Forecasters (SPF), whose members span academia and industry. Intriguingly, the researchers found that while the errors in the SPF's forecasts could be attributed to the absence of the tonal information culled from the SEC filings, the errors in the Fed’s forecasts could not. This suggests both that the Fed was collecting qualitative information that the SPF was not—and that the agency was making remarkably efficient use of it.

"They weren’t leaving anything on the table," Ramesh says.

Having solved one mystery, Ramesh would like to focus on another; namely, how does the Fed identify bellwether firms in the first place?

Unfortunately, the SEC no longer makes IP address data publicly available, which means that Ramesh and his colleagues can no longer study which companies the Fed is most interested in. Nonetheless, Ramesh hopes to use the data they have already collected to build a model that can accurately predict which firms the Fed is most likely to follow. That would allow the team to continue studying the same companies that the Fed does, and, he says, “maybe come up with a way to track those firms in order to understand how the economy is going to move.”

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This article originally ran on Rice Business Wisdom and was based on research from K. Ramesh is Herbert S. Autrey Professor of Accounting at Jones Graduate School of Business at Rice University.

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Baylor, Rice win $500,000 to launch humanities-driven health AI center

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Baylor College of Medicine and Rice University have been awarded a $500,000 grant from the National Endowment for the Humanities (NEH) to create the Center for Humanities-based Health AI Innovation (CHHAIN).

The new center and three-year initiative aims to create ethically responsible and trustworthy AI for health care that uses history and patient narratives to shape the technology, according to a release. It represents a collaboration between the Center for Medical Ethics and Health Policy at Baylor and the Medical Humanities Research Institute at Rice. Ultimately, the researchers aim to establish a national model for integrating the humanities into the design and implementation of health AI.

Vasiliki Rahimzadeh, assistant professor at Baylor in the Center for Medical Ethics and Health Policy, and Kirsten Ostherr, director of the Medical Humanities Research Institute at Rice, will serve as co-directors of the new center, which will be housed within the Center for Medical Ethics.

The team will also engage in strategic collaborations with Kirstin Matthews, Rice’s Baker Institute for Public Policy and its fellow in science and technology policy, as well as Dr. Quianta Moore, executive director of the Meadows Mental Health Policy Institute. An interdisciplinary team of medical humanities and bioethics scholars from Baylor, Rice, and partners in the Houston area will complete the group.

“CHHAIN represents a bold new model for integrating the humanities into health innovation,” Ostherr said in a news release. “It will create a collaborative space where humanities scholars, patients, developers and clinicians can come together to explore the human dimensions of health AI—trust, narrative and lived experience. These are essential perspectives that are too often missing from technology development, and CHHAIN is designed to change that."

CHHAIN’s work will revolve around three key points:

  • Defining trustworthy AI through patient voices
  • Translating humanities insights into clinical AI settings
  • Public engagement and policy translation

“For AI to truly improve health outcomes, it must be designed with patient trust and wellbeing at its core,” Rahimzadeh said in the news release. “CHHAIN will provide a dedicated space to explore critical bioethics questions, such as how we ensure AI respects patient autonomy, addresses the needs of underserved communities and integrates meaningfully into clinical care. Our goal is to translate these insights into real-world health settings where AI is already shaping patient experiences."

CHHAIN's research mission was also developed thanks to pilot funding from the Margaret M. and Albert B. Alkek Department of Medicine at Baylor and a grant from Rice's Provost's TMC Collaborator Fund.

Texas A&M, the University of North Texas and the University of Texas at El Paso were also home to some of the 97 projects that received a portion of the $34.79 million in fundning from the NEH. See the full list here.

Houston booms as No. 2 U.S. market for retail construction in 2025

Construction Zone

Get ready for a gigantic cartload of new shopping opportunities in Houston. A new report indicates the equivalent of 21 Walmart supercenters is under construction in the region.

The report, published by commercial real estate services provider Lee & Associates, says Houston has nearly 3.9 million square feet of retail space under construction, making it the second most active market for new retail space in the U.S.

To put that in perspective, given the average Walmart supercenter measures 182,000 square feet, the 3.9 million-square-foot total would work out to 21 new supercenters being built in the region.

Dallas-Fort Worth is by far the most active U.S. market for new retail space; DFW leads more than 60 U.S. retail markets with nearly 7.15 million square feet of space under construction. The amount of retail space going up in DFW represents 15 percent of all retail space under construction in the more than 60 U.S. markets tracked by Lee & Associates.

Houston and Austin aren’t too far behind Dallas-Fort Worth, though.

Third-ranked Austin area has more than 3.4 million square feet of retail space being built.

What’s behind the surge in retail construction across Texas? Population growth.

Data recently released by the U.S. Census Bureau shows Houston was the second-fastest-growing metro from 2023 to 2024. DFW was the country’s third-fastest-growing metro from 2023 to 2024, based on the number of new residents, and Austin landed at No. 13.

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This article originally appeared on CultureMap.com.

Intuitive Machines to acquire NASA-certified deep space navigation company

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Houston-based space technology, infrastructure and services company Intuitive Machines has agreed to buy Tempe, Arizona-based aerospace company KinetX for an undisclosed amount.

The deal is expected to close by the end of this year, according to a release from the company.

KinetX specializes in deep space navigation, systems engineering, ground software and constellation mission design. It’s the only company certified by NASA for deep space navigation. KinetX’s navigation software has supported both of Intuitive Machines’ lunar missions.

Intuitive Machines says the acquisition marks its entry into the precision navigation and flight dynamics segment of deep space operations.

“We know our objective, becoming an indispensable infrastructure services layer for space exploration, and achieving it requires intelligent systems and exceptional talent,” Intuitive Machines CEO Steve Altemus said in the release. “Bringing KinetX in-house gives us both: flight-proven deep space navigation expertise and the proprietary software behind some of the most ambitious missions in the solar system.”

KinetX has supported deep space missions for more than 30 years, CEO Christopher Bryan said.

“Joining Intuitive Machines gives our team a broader operational canvas and shared commitment to precision, autonomy, and engineering excellence,” Bryan said in the release. “We’re excited to help shape the next generation of space infrastructure with a partner that understands the demands of real flight, and values the people and tools required to meet them.”

Intuitive Machines has been making headlines in recent weeks. The company announced July 30 that it had secured a $9.8 million Phase Two government contract for its orbital transfer vehicle. Also last month, the City of Houston agreed to add three acres of commercial space for Intuitive Machines at the Houston Spaceport at Ellington Airport. Read more here.

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