Customer Spending Data: Capturing Deep Customer Insights
Customer spending data is one of the most impactful drivers of personalization a brand can leverage in their loyalty offerings. With a phone number or email entry at the point of sale, brands capture what their customers spend at their stores in real-time.
The challenge with today’s loyalty programs, however, is that for the most part, they are all the same - discounts in-store and select partners, and most of them can’t be used outside their store (commonly referred to as closed-looped). So the question becomes, how can brands gain access to additional spending data, inside and outside of their stores? What’s next for loyalty programs? And what is needed for innovation?
A possible route for innovation is by better understanding customers' spending habits when they are not spending outside a brand's four (virtual) walls.
This is where embedded finance technology comes into play. By offering financial services programs like open-looped debit, credit, and prepaid card programs through embedded fintech, companies can get real-time transaction-level spending data.
3 Examples: How To Use Spending Data From Outside Your Store
At first thought, the practical use behind “open-loop customer spending data” might not be obvious, but here are a few basic examples that make the value come to life.
1. Steering customer purchases back to your store
A big box retailer may uncover that a large percentage of their customers are using a more specialized retailer focused on sporting goods. The big box retailer could then develop a competing product offering for their sporting goods products that deliver rewards or cash-back that drives customers back into their store for those same types of products.
A quick service restaurant sees a customer segment that frequently purchases at a competitor for breakfast, and creates a special offering for those customers to choose them for breakfast.
2. Financial services product development
A telecommunications provider may uncover a large demographic that frequently deposits money into an investing app. The telco could take that data and decide to integrate customized investment features into their financial services app and keep customers in their app while providing a more robust offer for their customers.
A discount retailer offers a debit card program for their underbanked customer demographic and gets insights into customer deposit activity. With embedded finance technology, the discount retailer can use deposit history as a metric to determine a particular customer’s creditworthiness and can look to offer them credit items like credit cards or loans.
3. Spending pattern insights
A grocery retailer may uncover general spending cycles within a segment of customers - certain pockets of time within the week or month that customers do the majority of their spending. The grocery retailer could use that data to launch bundled offers and promotional campaigns designed to cater to when customers are most likely to buy.
Different Types of Spending Data
Brands who have previously worked with a bank partner on a card program offering are familiar with customer spending data, but in most cases, the spending data is lagged and aggregated. In contrast, embedded finance technology gives you access to raw, transactional data. For example, let’s look at the data that an open-looped card program yields.
Customer transaction data for open-looped card programs:
- Time and Date of Transaction
- Origin Bank
- Transaction Type: Parent Transaction, ACH, Check, Refund
- Transaction Currency Amount and Status
- Payment Method
- Merchant Name and ID
- Currency Exchange Rate
Steering customers back in-store from a competitor is simply using the merchant ID data point. Layering in additional data points like transaction amount and number of transactions over a period of time provide insight into a segment of customers that frequently spend at a competitor.
Similarly, for financial services product development, analyzing deposits into investment apps through the merchant ID data can give insight into the number of customers potentially interested in investment technology in-app, and how much they would deposit over a certain time period.
Finally, spending patterns insights includes time and date that yields insights into when customers focus their spending.
Beyond Data: The Value of Embedded Finance Technology
So, you have the details of how customer spending data can influence your loyalty program, product development, and customer engagement strategies, but that’s just one part of the value chain.
Embedded finance technology creates new channels of revenue and builds stronger ties with your customers.
Before searching and getting the wrong answers from Google, get our complete handbook on embedded finance.
Whether you're looking for new ways to innovate and drive new revenue, focused on loyalty programs, improving customer experiences, or just learning more about embedded finance technology, this handbook is for you.
You’ll learn:
- How innovation is driving embedded finance
- The shift in consumer spending habits
- What to offer in your financial services program
- Launching a new financial product to your customers
Download the Embedded Finance Handbook Now
