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Consumer Spending Data for Marketing Research
Consumer spending data records what people actually bought, from which merchant, and when, rather than what they recall buying in a survey administered weeks later. Because the records are continuous, a brand's sales can be observed before and after a price change, a campaign, or the arrival of a competitor, and the same panel shows where the spending went instead. Transaction and receipt panels also carry a household or device identifier, so repeat purchase, brand switching and category substitution can be traced over time in a way that aggregate retail sales statistics cannot support.
How marketing researchers use consumer spending data
Measuring advertising and targeting effects on realised purchases
Marketing researchers pair a change in advertising conditions, a platform policy shift or a targeting restriction with a transaction panel, and estimate the effect on purchases rather than on clicks or stated intent. The design turns on observing the same merchants before and after the change, so that shifts in conversion are separated from a general movement in category spending. The limitation is attribution: a transaction panel records that a purchase happened, not which impression preceded it, so campaign exposure has to come from a separate source or from the timing of the shock itself.
Brand switching, substitution and cross channel demand
Because merchant level records follow the same consumers across categories, researchers use them to ask where spending goes when a new option enters a market, whether an incumbent brand loses share to it or the category simply expands. The identifying variation is usually staggered entry across states or markets, with spending in unaffected markets serving as the counterfactual. The caveat is coverage of the wallet: a card or receipt panel observes only the merchants and payment methods it captures, so cash spending and any merchant outside the panel are invisible, and substitution towards them is read as a decline.
Payment friction, basket composition and trip frequency
Item level point of sale records let marketing researchers decompose a change in spending into its parts: whether consumers visited more often, added items to the basket, or traded up within a category. Studies of payment technology, loyalty programmes and in store promotions rely on this decomposition, since a rise in monthly spend has very different marketing implications depending on which margin moved. Item level detail is the constraint, as it exists only for the retailers and chains that supply their own scanner records, so the panel is a set of participating merchants rather than a representative sample of retail.
Consumer spending datasets available on Dewey
Consumer Edge
Consumer Edge assembles consumer transaction records at the merchant level, which marketing researchers use to track brand share, repeat purchase and switching between competing retailers over time instead of relying on recalled purchase behaviour.
View datasetPDI Technologies
PDI Technologies supplies point of sale transaction records, useful where the research question needs basket composition and trip frequency rather than a monthly spending total.
View datasetMeasurable AI
Measurable AI collects e-receipt records from consumers in emerging markets, covering platforms and countries where scanner panels and commercial market research rarely reach.
View datasetMore published work using consumer spending data
Dante Donati · Marketing Science · 2025
Christopher S. Armstrong, Yaniv Konchitchki, Biwen Zhang · Working Paper · 2025
Soyoung Kim, Randi Priluck · Journal of Theoretical and Applied Electronic Commerce Research · 2025
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