Consumer Transaction Data: Unveiling Trends and Spending Patterns

by Dallán RyanApr 11, 2024Blog, Featured

What Is Consumer Transaction Data?

Consumer transaction data is one of the most popular and widely deployed types of alternative data by investment managers. This type of alternative data is also used extensively by private equity and corporates with exposure to the retail segment of the economy. Quants and discretionary managers typically deploy consumer transaction data to predict quarterly revenue growth and earnings. As the data is available before quarterly earnings are released, it is ideal to gauge if a company is going to beat or miss Wall Street estimates.

Figure 1: The Growth of Consumer Transaction Datasets over Time on Eagle Alpha’s Explorer Platform (Source: Eagle Alpha)

Understanding the Role of Consumer Transaction Data

Consumer Behavior and Company Performance:

Transaction data from consumers provides valuable early indicators of revenue growth and earnings for companies, especially within retail sectors.
Investment professionals utilize this data to anticipate if a company will surpass or fall short of financial analyst predictions.

Insight into Spend Trends:

Available before the release of quarterly financial reports, it serves as a tool for estimating future performance.
A notable correlation exists between transaction data and reported company revenues, as illustrated in available studies.

Strategic Business Decisions:

Beyond revenue predictions, it aids long-term investors in understanding shopper behaviors and responses to new products.
The impact of sales promotions and discounts on consumer spending habits can be assessed through a thorough examination of transaction data.

Resource Hub for Transaction Data Application:

Industry experts have amassed a wealth of knowledge, including practical use cases, workshops, and key legal considerations in utilizing consumer transaction data.
It proves to be an essential feed for diverse industries to align their strategies with consumer dynamics.

Exploring Consumer Financial Interactions

Consumer financial interactions encapsulate a broad array of information arising from an individual’s purchases and business dealings. This detailed financial snapshot includes:

Payment methods used such as credit cards and debit cards
E-receipt collection from email inboxes
Insights from point-of-sale (POS) systems
Data from fintech applications like PayPal

With its near-instantaneous nature, this financial interaction ledger offers a potent indicator of a company’s performance. Here’s how this data is utilized:

Aggregate Analysis: Broad sector-level overviews.
Detailed Assessment: Examination at merchant, company, or product scales.

Given its depth and immediacy, obtaining this data can be expensive; certain card transaction data has changed hands for as much as $1 million per year. Traditionally, this has meant that only a select few, typically affluent funds, could access these consumer transaction datasets. However, vendors have innovated by offering data on specific stock tickers or bundles of them, thus broadening the scope of accessibility to a wider investment community seeking precise insights to drive strategic decisions.

Insights from Specialized Workshops on Consumer Transaction Data

Highlighting Key Consumer Data Trends

In a late 2020 specialized workshop, industry leaders shared robust data analytics methods and insights within the consumer transaction arena. These discussions covered the nuances of credit and debit card transaction datasets and the importance of data consistency in understanding consumer behavior over time.

Thomas Combes, by exhibiting data from a comprehensive quality report, underscored the significance of panel steadiness, which considers the variations in transaction volume by card type. He emphasized how vendors might apply specific filters to data, ensuring that business strategies are based on reliable and steady datasets.

Experiences of Seasoned Experts

David Schwartz, with his considerable expertise in data acquisition, touched upon the evolving landscape of consumer transaction data. He brought to light the challenges in harnessing this data, yet mentioned how advances in technology and vendor compliance are rendering it more accessible. Although competitive edge—alpha—might be diluted, it remains embedded within this type of data. For dominant industry players, leveraging transaction data is no less than a crucial competitive necessity, or as Schwartz termed it, “table stakes.”

Leveraging Data for In-Depth Market Analysis

Furthermore, Daniel McCarthy dived into the strategic applications of this data through his Customer-Based Corporate Valuation (CBCV) model. By analyzing consumer loyalty and churn rates with transaction data, companies can gauge the long-term value of their customers. His approach signifies a vanguard for revenue prediction based on consumer actions, providing a framework for year-over-year evaluations and market research.

These workshops grant invaluable collaboration opportunities among professionals, with shared practical applications of consumer transaction data spanning from product development to consumer trend assessment.

Table: Key Points from Workshops

In essence, these expert-led workshops provide a broad view of the sub-categories and their applications, equipping businesses to make data-driven decisions in product development and business strategy based on consumer transactions in sectors like restaurants and beyond. For more information on how to participate and/or attend these expert workshops, please reach out to dallan.ryan@eaglealpha.com.

Analytical Insights: Understanding Consumer Market Dynamics

Through the lens of transactional data, it becomes evident that consumer behavior patterns afford crucial insights into company performance. A key study demonstrated the strategic play by McDonald’s, leveraging data from email receipts to carve out a larger market share in the increasingly competitive breakfast delivery market post-COVID-19’s arrival, collaborating with platforms like Uber Eats and DoorDash.

Market Expansion: McDonald’s expansion in breakfast delivery service
Partnerships: Collaborations with delivery services
Outcome: Growth in market share during the pandemic’s peak

Strategists and investors turn to such illustrative cases to interpret intra-quarter business trends. For instance, this approach enables a granular look at Disney+ subscriber growth, guiding both analysts and hedge funds in making informed projections. Precise transaction data not only pinpoints customer retention rates, such as those observed with Netflix—where a significant majority maintain their subscription after a year—but also provides a window into market shifts.

Subscriber Patterns: Disney+ growth trends
Customer Loyalty: One-year retention rates for Netflix
Data Source: Credit and debit card transactions

These data-driven narratives, invaluable to Bloomberg Terminal and Bloomberg Second Measure users, offer a forward-looking perspective for investors during volatile economic times like the COVID-19 pandemic.

As per the infographic in the first paragraph, there has been an increase in consumer transaction data providers coming to market and it is now possible to get quality consumer transaction data outside of the US. For example, there are consumer transaction data providers, like Fable Data, that offer pan-European consumer transaction data. Fable Data began delivering consumer transaction data from the UK but now offer data across many European regions and as you can see below, have steadily grown their panel over time, covering over 2400 tickers now.

Figure 2: Fable Data’s Storefront of Eagle Alpha Explorer Platform. (Click on the image to explore Fable Data’s coverage and Data Structure.)

The ability to analyze comparative cohort analysis, customer overlap, and churn illuminates pathways for strategic decision-making and intra-quarter insights that are critical in today’s market landscape.

Legal Aspects of Handling Consumer Transaction Information

In managing consumer transaction information, compliance with privacy laws including the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) is imperative. These regulations mandate strict guidelines on how personally identifiable information (PII) and sensitive transaction details not yet public, referred to as material non-public information (MNPI), are handled and protected.

For professionals engaged with such data, here are key legal points to consider:

PII Protection: Safeguarding individual identifiers necessitates robust security and restricted data access protocols.
MNPI Concerns: Transparency around non-public financial information is critical to avoid insider trading implications.
Data Origin Tracking: Documenting the lineage of data is crucial for authenticity and compliance purposes.

Concluding Insights

In the realm of asset management, leveraging consumer transaction data has emerged as an invaluable strategy to gain insights into revenues of businesses with direct interaction with end-users, like retail outlets and dining establishments. This data offers a glimpse into buying patterns, providing indicators for both short-term trading decisions and long-term company valuations.

Implementation Considerations
- Legal Compliance: Immutable compliance with legal frameworks is paramount.
- Data Acquisition Costs: Notwithstanding the expense, the benefits justify the investment for many firms.
Usage Across Industries
- Utilized for generating signals for trade strategies.
- Informs long-term analysis for sustained investment planning.

Should you seek further guidance, don’t hesitate to reach out through the provided communication channels.