By now, many leading banks and credit card providers have already invested in basic credit card analytics, such as value, behavior and needs/lifestyle segmentation, churn prediction, and credit risk analysis. Is this the end of road for customer insights in the field? Hardly so – this article summarizes five relatively niche ways of using credit card data, allowing banks and credit card providers to take things one step further towards separating themselves from their competitors by getting even more value out of the rich POS data at hand…
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Credit card transactions are one of the richest sources of data for customer analytics in the financial services field; yet, relative to the wealth of insights they hold, one of the most commonly under-utilized sources of information as well. Most credit card providers today apply only the traditional data mining models on this data, such as value, behavior and needs/lifestyle segmentation, churn prediction and credit risk models, considering credit cards as merely another banking product.
In order to maximize the benefits, credit card providers need to start changing their views regarding transactional credit card data, and start looking at it more from a retailer’s perspective. Tapping into the location, product, and competitive intelligence aspects of credit card data opens new revenue sources for both the providers and the merchants.
The answer to “why” can be summarized in two simple ways – the first – more revenues, the second – more revenues. This increase in revenues can come from:
- Direct Financial Benefits
Based on a recent report by the Wall Street Journal, as well as both companies’ own statements, Visa and MasterCard are both working on their plans to start selling reports and insights based on credit card data, to support companies in better targeting customers. It is already known that some banks already sell reports and dashboards to their merchants based on POS and customer data. Most haven’t taken the natural next step, the step of acting as a direct marketing agency to target and reach out to customers based on their credit card spend profile.
- Indirect Financial Benefits
Any insights provided to a merchant on opportunities for more sales means even more revenues passing through credit cards and POS systems, which means increased transaction volumes and commissions for the credit card providers. Sharing better intelligence with the merchants is a win-win scenario for both parties.
We recommend five methods for increasing the value generated from credit cards data:
1. Targeted Merchant Ads for Google Dollars: Credit card providers, with access to billions of transactions by millions of customers, are the shopping equivalent of search engines in terms of targeted advertising opportunities. Just as Google Ads provides the ability for companies to target customers based on the keywords they type in, credit card providers can do something similar – provide access to credit card holders based on what they actually purchase. A real world example by Citibank is an example of this – the company puts advertisements by various merchants (e.g. “Free Ground Shipping on Sony TVs from Sonystyle.com,”) right under the relevant online credit card statement lines (e.g. beneath a transaction with Sirius Satellite Radio, categorized as “cable, satellite, pay TV/radio service”).
2. Real Time Competitive Intelligence for Merchants: Another attractive offering for merchants (for which the credit card providers are uniquely positioned) is the providing of real-time monitoring and reporting of competitor activities. Based on the volume of transactions of specific competitor brands and products, merchants can be provided with the sales trends and breakdown of their key competitors, across all product lines, distributors and locations. On top of that, based on the value of transactions, it is possible to provide a real-time alert mechanism on changes in prices and discounts applied by each competitor (e.g. notifying Bosch when the unit price of a specific Siemens refrigerator model becomes cheaper, based on POS transactions).
3. Cross Brand Partnership Opportunities for Merchants: Similar to real time competitive intelligence, credit card companies are in a unique position to provide intelligence on partnership opportunities for merchants, having visibility over customers’ preferences across brands and industries. Based on the analysis of customers’ purchasing patterns across different stores, it is possible to identify which brands have the highest correlation (due to their complementary nature or similar positioning). For example, a specific TV brand could realize that its customers also quite often also purchase a specific furniture brand (TV stand), and come up with a joint value proposition / bundle that would increase sales for both parties. Only with a credit card provider’s data is it possible to identify such opportunities, in virtually limitless combinations (i.e. including all possible brands and stores, which accept credit cards).
4. Tapping into Location Based Marketing: Location based marketing has become one of the key activities in telecommunications, based on the GPS position of customers on a cellular network (such as sending an SMS to a customer when he/she is near a specific store or mall). Credit card companies need to act on the fact that they can match such targeted marketing opportunities for merchants, based on the location of their POS transactions. Instead of focusing on only the products customers purchase with their credit cards, and begin focusing on where customers buy these products from, it becomes possible to provide location-based marketing opportunities to merchants. A mobile operator can only provide information in regards to the general vicinity of a given customer (i.e. that a given customer is traveling close to a women’s accessories store), whereas the credit card provider can hone in on the location (by seeing just actually where a purchase was made in that area). When location meets POS data, the opportunities become endless.
5. Sneak Peak into Competitor Customers: A more direct way of using the credit card data for banks’ own benefits is the valuation and segmentation of competitor credit cards, which are swiped through their own POS machines in some cases. Based on the ‘off-net’ transactions happening on a bank’s POS network, it is possible to identify and understand quite a bit about the credit card holders of competitor banks – i.e. which ones are relatively high spenders, what behaviors which ones exhibit, what their preferences are, etc. This gives an unmatched opportunity to target them right before / after their purchase at the point of sales, with the most relevant value proposition. For example, a competitor customer who has been identified to be spending over $500 on clothes per month from specific brands through these ‘off-net’ transactions can be offered a 10% special discount on his/her favorite brand in the next transaction, in case he/she applies for a new credit card with one’s own bank. And all this communication can go through the POS slip, which means very limited marketing costs for targeted customer acquisition.
Of course, management of customer privacy and merchant confidentiality is a key success element in most of these opportunities, calling for process and policy design in addition to customer analytics activities for them (as well as a thorough understanding of what regulations allow and don’t allow in a given market).
Given that the infrastructural elements are in place, companies could quickly turn these opportunities into actions, making pilots possible for each of them in a matter of days. Once each opportunity is tested on pilot groups of customers and merchants, the ones that could be translated into significant returns can easily be deployed across the whole base. Once these five opportunities are incorporated into day-to-day credit card business, next, companies should pursue new opportunities, mainly combining intelligence from credit card with other banking products’, creating benefits for both ends.
To learn more about credit card analytics and how to operationalize the above, please contact us at email@example.com.