Credit and debit card transaction data

What is Consumer Edge?

Consumer Edge is a consumer insights company founded in 2009 that builds high resolution views of consumer spending behavior from credit and debit card transactions. They source data directly from banks and payment processors through formal partnerships, with anonymization applied before transactions ever reach Consumer Edge. Their work was originally built for hedge funds and corporate strategy teams modeling firm level revenue, which is why so much of the value sits in the ticker level tagging of merchants.

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What academic researchers should know about Consumer Edge transaction data

Consumer Edge publishes five U.S. datasets on Dewey: company and ticker level aggregated transactions, macro consumer spend broken out by NAICS code, a behavioral and demographic transaction file, a delivery service provider file, and Brand Tracker. The panel draws from more than 100 million U.S. credit and debit cards, captures more than 13,000 merchants at the brand, category, and store location level, and runs back to January 2014 with consistent year over year coverage from 2019. Transactions are categorized by online versus offline channel, attributed carefully across cases like delivery platforms where a single purchase touches multiple brands, and tagged with NAICS industries through more than 130 narrower buckets that roll up into 30 broader categories. The ticker level mapping links each transaction to the public company that benefits from it, which is what makes the data useful for firm level revenue work.

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Why academic researchers choose Consumer Edge on Dewey

Card transaction data has become essential for modern empirical research in finance, marketing, and macroeconomics, and the quality of the panel matters enormously for any conclusion that depends on the level or trend of consumer spending. Consumer Edge's direct relationships with banks and payment processors mean transactions come from the source rather than from third party aggregators, and the ticker level tagging is the work that makes firm level revenue research practical out of the box. On Dewey, Consumer Edge pairs naturally with Advan Research for foot traffic at the store locations behind the spending, Similarweb for the online channel that runs in parallel, and Context Analytics for how social sentiment shifts. Consumer Edge was built for institutional investors, and Dewey is how academics get their hands on it.

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Consumer Edge academic research ideas and use cases

Nowcasting and earnings forecasting. The ticker level mapping makes Consumer Edge especially useful for finance researchers studying how high frequency consumer signals predict firm earnings, revenue surprises, and stock returns. Researchers can construct daily or weekly spending series for hundreds of public retailers, restaurants, and consumer brands, then test whether those series lead reported revenue and how the market prices that information. Pair with Context Analytics for the social sentiment that often moves in parallel.

Macroeconomic policy and stimulus. Consumer Edge's depth back to 2014 spans multiple shocks including the 2018 tax reform, the COVID period and subsequent stimulus rounds, inflation in 2022, and the rate hike cycle that followed. Researchers can study how households reallocate spending across categories in response to fiscal transfers, interest rate changes, and price shocks, and whether responses differ by income, age, or geography using the behavioral and demographic file. The NAICS rolled macro file lets researchers benchmark against official BEA series.

Marketing, brand competition, and category dynamics. The brand level granularity supports research on category share shifts, the spillover effects of advertising or new product launches, and customer loyalty and retention. Brand Tracker is built precisely for this kind of work. Pair with Similarweb to study how brand consideration on the open web translates into actual purchase, and OpenBrand for the durable goods categories where survey context adds value alongside transaction outcomes.

Delivery platforms and the gig economy. The dedicated delivery service provider file isolates transactions where a single purchase touches a restaurant, grocer, or other merchant alongside a delivery brand like DoorDash or Instacart. That setup is purpose built for research on platform competition, take rates, the substitution between in store and delivery channels, and how restaurants and grocers fared as the delivery economy expanded. Pair with LinkUp postings for delivery worker hiring patterns and PassBy for store level visits.

Local economic activity and urban economics. Consumer Edge's store location level granularity lets researchers study how spending shifts geographically in response to events like minimum wage increases, the opening or closing of a major employer, transit changes, or housing policy. Pair with the behavioral and demographic file for income and age splits, ATTOM for the real estate context, and PassBy or Advan Research for the foot traffic that produces or follows the spending.