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

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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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Houston robotics co. unveils new robot that can handle extreme temperatures

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Houston- and Boston-based Square Robot Inc.'s newest tank inspection robot is commercially available and certified to operate at extreme temperatures.

The new robot, known as the SR-3HT, can operate from 14°F to 131°F, representing a broader temperature range than previous models in the company's portfolio. According to the company, its previous temperature range reached 32°F to 104°F.

The new robot has received the NEC/CEC Class I Division 2 (C1D2) certification from FM Approvals, allowing it to operate safely in hazardous locations and to perform on-stream inspections of aboveground storage tanks containing products stored at elevated temperatures.

“Our engineering team developed the SR-3HT in response to significant client demand in both the U.S. and international markets. We frequently encounter higher temperatures due to both elevated process temperatures and high ambient temperatures, especially in the hotter regions of the world, such as the Middle East," David Lamont, CEO of Square Robot, said in a news release. "The SR-3HT employs both active and passive cooling technology, greatly expanding our operating envelope. A great job done (again) by our engineers delivering world-leading technology in record time.”

The company's SR-3 submersible robot and Side Launcher received certifications earlier this year. They became commercially available in 2023, after completing initial milestone testing in partnership with ExxonMobil, according to Square Robot.

The company closed a $13 million series B round in December, which it said it would put toward international expansion in Europe and the Middle East.

Square Robot launched its Houston office in 2019. Its autonomous, submersible robots are used for storage tank inspections and eliminate the need for humans to enter dangerous and toxic environments.

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This article originally appeared on EnergyCapitalHTX.com.

Houston's Ion District to expand with new research and tech space, The Arc

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Houston's Ion District is set to expand with the addition of a nearly 200,000-square-foot research and technology facility, The Arc at the Ion District.

Rice Real Estate Company and Lincoln Property Company are expected to break ground on the state-of-the-art facility in Q2 2026 with a completion target set for Q1 2028, according to a news release.

Rice University, the new facility's lead tenant, will occupy almost 30,000 square feet of office and lab space in The Arc, which will share a plaza with the Ion and is intended to "extend the district’s success as a hub for innovative ideas and collaboration." Rice research at The Arc will focus on energy, artificial intelligence, data science, robotics and computational engineering, according to the release.

“The Arc will offer Rice the opportunity to deepen its commitment to fostering world-changing innovation by bringing our leading minds and breakthrough discoveries into direct engagement with Houston’s thriving entrepreneurial ecosystem,” Rice President Reginald DesRoches said in the release. “Working side by side with industry experts and actual end users at the Ion District uniquely positions our faculty and students to form partnerships and collaborations that might not be possible elsewhere.”

Developers of the project are targeting LEED Gold certification by incorporating smart building automation and energy-saving features into The Arc's design. Tenants will have the opportunity to lease flexible floor plans ranging from 28,000 to 31,000 square feet with 15-foot-high ceilings. The property will also feature a gym, an amenity lounge, conference and meeting spaces, outdoor plazas, underground parking and on-site retail and dining.

Preleasing has begun for organizations interested in joining Rice in the building.

“The Arc at the Ion District will be more than a building—it will be a catalyst for the partnerships, innovations and discoveries that will define Houston’s future in science and technology,” Ken Jett, president of Rice Real Estate Company, added in the release. “By expanding our urban innovation ecosystem, The Arc will attract leading organizations and talent to Houston, further strengthening our city’s position as a hub for scientific and entrepreneurial progress.”

Intel Corp. and Rice University sign research access agreement

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Rice University’s Office of Technology Transfer has signed a subscription agreement with California-based Intel Corp., giving the global company access to Rice’s research portfolio and the opportunity to license select patented innovations.

“By partnering with Intel, we are creating opportunities for our research to make a tangible impact in the technology sector,” Patricia Stepp, assistant vice president for technology transfer, said in a news release.

Intel will pay Rice an annual subscription fee to secure the option to evaluate specified Rice-patented technologies, according to the agreement. If Intel chooses to exercise its option rights, it can obtain a license for each selected technology at a fee.

Rice has been a hub for innovation and technology with initiatives like the Rice Biotech Launch Pad, an accelerator focused on expediting the translation of the university’s health and medical technology; RBL LLC, a biotech venture studio in the Texas Medical Center’s Helix Park dedicated to commercializing lifesaving medical technologies from the Launch Pad; and Rice Nexus, an AI-focused "innovation factory" at the Ion.

The university has also inked partnerships with other tech giants in recent months. Rice's OpenStax, a provider of affordable instructional technologies and one of the world’s largest publishers of open educational resources, partnered with Microsoft this summer. Google Public Sector has also teamed up with Rice to launch the Rice AI Venture Accelerator, or RAVA.

“This agreement exemplifies Rice University’s dedication to fostering innovation and accelerating the commercialization of groundbreaking research,” Stepp added in the news release.

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