Data-driven strategies are the key to disruption in the consumer landscape. Every day, marketing, sales, product, and strategy teams are making decisions to drive growth. Data is essential to implementing the right strategy.
Successful execution of data-driven strategies is less common, as many organizations still struggle to turn their findings into actionable insights.
In this guide, we will give an overview of how to better understand consumer transaction data, and how to leverage the power of consumer insights.
What are the different types of consumer spending data?
The main sources of consumer spending data are transaction data and syndicated retail sales data (also known as point-of-sale or “POS” data).
Consumer transaction data from credit cards, debit cards, and ACH payments
Consumer transaction data is third-party data that paints a broad picture of a consumers’ spending habits over time. This includes transaction amounts seen on credit/debit card statements, along with merchant and date info. Transactions are tied to an anonymized user account, so changes in spending behavior and demographic information can be tracked over time. This data is anonymized and aggregated. It needs to be heavily cleansed, parsed, organized, and transformed by data scientists before relevant information can be derived.
While extremely valuable, unstructured data from these transactions can be virtually useless without a data engineering team to extract actionable insights. Maintaining a team to process unstructured data in-house can be costly. Outsourced partnerships are often a more viable alternative for organizations.
While debit and credit transaction data is useful in understanding where consumers are spending and how their preferences have changed over time, it has pitfalls. This information is limited and doesn’t provide expansive insights into purchase details, such as products, brands, pricing and discounts, or quantities of items purchased.
Point-of-sale (POS) data
Syndicated retail sales data is another viable alternative source of consumer spending data and insights. POS data pertains to transactions completed through a POS system, like checkout at a retail store or handheld POS hardware. Unfortunately, this data is limited and leaves gaps because it excludes purchases outside of certain retailers and specific POS systems.
Transaction data is typically not enough to fully harness the power of consumer spending insights. Digital and in-store receipts add another level of clarity when understanding consumer purchases.
Receipt data includes information on what items were purchased, with details such as brand, size, and quantity. It also includes the price and any discounts or coupons applied. This data exposes consumer demographics. Similar to transaction data, it is anonymized and aggregated.
Receipt data can be collected both actively (based on incentives) or passively. For an illustration of passive receipt data collection, consumers can provide email access within an app, in exchange for a service. In some cases, shoppers may decide to unsubscribe from mass marketing emails. Passive collection can be advantageous, as it allows access to many consumers’ email receipts. This compares to active collection. Applying the same example, in this method, an app incentivizes consumers to self-submit their receipts in exchange for benefits, like gift cards or points. Panels including receipts from consumers’ active submission are limited because of their reliance on the consumer to submit his or her receipt.
Consumer spending data alone is often not enough
There are many other sources of consumer spending data with different panel sizes and dynamics. However, consumer spending data is not enough to inform winning strategies. Many leading data-driven companies typically combine insights from consumer spending with other forms of digital data, DTC and e-commerce data, foot traffic data, customer loyalty and engagement data, and brand awareness data for themselves and their competitors.
How M Science can help
M Science is a global data-driven research and analytics firm, with nearly 20 years of experience uncovering new insights for some of the world’s largest corporations and financial institutions. We revolutionize research by discovering new datasets and pioneering methodologies to provide actionable intelligence. Learn more at: mscience.com/corporate intelligence. M Science is a portfolio company of Leucadia Investments, a division of Jefferies Financial Group Inc. (NYSE: JEF).
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