The payment processor market is extremely competitive. Companies for the likes of PayPal, Adyen, and Stripe are currently lowering their margins in a detrimental “race to the bottom”. This severely impacts their profitability, which is why payment processing companies are now seeking for new revenue streams.
At the same time, they realized that they have access to large amounts of data, which holds tremendous value, because it relates to real users who make real transactions. That said, rather than sell the high-quality data at their disposal, payment service providers wish to monetize it by offering new, data-driven services for their business customers. Most important of all, it would act as the much needed differentiator in the saturated market.
In this article, we’re going to explore how payment service providers can build new revenue streams thanks to data clean rooms. But first, let’s take a look at some of the challenges they’re currently facing.
Payment Service Providers face some challenges…
Payment providers are currently looking at the following operational and market challenges.
Drop in transaction fees
Nowadays, payment service providers’ revenue is strictly related to the income of merchants using their payment gateway and processing solutions. Up until recently, the future looked bright, with the total transaction value having grown at an average growth rate of 14% just between 2017 and 2019 alone.
The pandemic brought on an even more significant spike resulting from online shopping and has pushed even more businesses into integrating with an online payment provider. That said, the rise in online purchasing demand also gave birth to multiple new payment service providers, whom large processors now had to share the market with. This, on top of the economic crisis which impacted their merchants’ profitability, has forced payment service providers to gradually lower their transaction fees – as of now, the sole revenue generator.
Limited differentiation options
Payment service providers have, thus far, been the innovators in the finance field. They never feared technological advancements and had the resources to create completely new service categories. Their inception has also enabled the fast development of the e-commerce industry.
For example, all the way back in 2013, PayPal acquired Braintree, which automated online payments for companies and merchants for $800 million. This way, they gained access to Braintree’s merchant account, billing, and credit card storage modules, as well as their PCI compliance and international and mobile payment solutions. This strategic decision has helped PayPal maintain its market position and outpace competitors on the market in the past decade.
But the situation, i.e., ability to develop new solutions has changed since. Innovation is no longer a trait of payment provider giants only. Due to significant venture capital investments in the payment processing market in the last couple of years, entering the industry is now attainable to other contenders.
Since merchants primarily choose payment providers based on the competitiveness of their prices, in order to thrive, companies in the sector need to diversify their revenue streams to maintain high profitability.
As mentioned earlier, many payment service providers are now recognizing the value of their transactional data. They realize that data monetization can become an extension of their core service and add value into their merchants’ personalization efforts. Here’s where the most innovative players in the industry are choosing to create services based on user profiles with data clean rooms (DCRs). We discuss how they can work for payment providers and merchants in the next section.
Creating new services with data clean rooms
Data clean rooms represent an environment where two or more parties can exchange and share data, including customer information (to an extent permitted by law and the T&C’s approved by the end customer). If a company has consent for their clients to use and share their data and applies relevant Privacy Enhancing Technologies, they can use DCRs to create comprehensive user profiles, which can hold information on price sensitivity, favorite product categories, and tens of other characteristics.
While most DCRs only allow parties to work on historical data, the most advanced solutions like Trusted Twin allow for real-time recommendations and insights.
If implemented according to legal requirements (and executed properly from an operational perspective), DCRs can be used in the following use cases:
Option 1: Building high-intent buyer audiences
Knowing what a customer has purchased previously is a powerful tool. Payment processors create audiences for merchants, which merchants can target with closely personalized offers.
A great analogy for how a data clean room can work in this area is Shopify Audiences. It collects data from merchants and data from its own payment service, Shopify Pay, and creates a collaborative profile that lets merchants learn more about each person’s shopping behavior, history, preferences, and others. It then creates a unique ‘audience’ for each merchant that can be used to target high-intent leads. Shopify Audiences also suggests campaigns the merchant could use to target the relevant group on Meta and Google.
This leads to the next option.
Option 2: Hyper-personalization
Collaborative profiles for end customers are rich in data and can be used to increase conversion rates on ecommerce websites by offering hyper-personalization such as:
- suggesting a product that fits the customer,
- identifying if a customer is shopping for discounts,
- offering a flash promo to complete the transaction immediately, etc.
For example, if a prospect looking for a pair of shoes visits an online store, they can get a recommendation of a product in the preferred color, price range, etc. This is possible as the store gets access to a user profile built from data collected from multiple other stores.
From the end customer’s perspective, this can lead to a better overall customer experience, while from the merchant’s perspective it improves conversion.
Option 3: Launching a “lookup service”
Let’s assume that a customer wants to take out a microloan to take their family on a holiday trip and settle it in installments or fully within 30 days.
To provide such a service in real-time the microlender needs to check customer data in real time across multiple sources, one of which are payment service providers. If the payment provider has set up customer profiles in a way to collaborate on data with others, then it’s very easy to access such data. The payment provider can then receive a fee for each access to the profile. Based on this information, the microlender can decide in real time whether they should grant the microloan or not.
Making the most of data while staying compliant
In the age of significant data regulation changes and the simultaneous depreciation of third-party cookies, using customer data compliantly for purposes other than those strictly related to the payment service can be difficult. While, in the financial sector, this primarily relates to banking, payment service providers aren’t free of obligations either. If they wish to create an ecosystem where they can collaborate with merchants on customer data, they need to ensure compliance with region-specific privacy regulations including GDPR.
Trusted Twin is a real-time data clean room that enables on-the-fly data collaboration among different parties while maintaining compliance with data privacy regulations.
As a result, merchants can exchange and assemble supplementary knowledge and insights to provision real-time recommendations to their clients. It is capable of providing recommendations in mere milliseconds per request once it’s at full scale.
It goes without saying that data collaboration provides actionable insights for merchants and payment service providers alike.
Acting to connect the right merchants with the right customers means more transactions take place, which leads to more commission. It also supports payment providers in their effort to maintain higher merchant retention and liberates them from the pressure of further dropping their transaction fees.
With a data clean room, merchants will need payment service providers for more purposes than solely transaction processing. Over time, this unique positioning can help payment providers win over more merchants and strengthen their partnership through adding value with data.
Initiating a data clean room gives payment processors the opportunity to monetize their data, increase profits, and it specifically provides the ability to stand out from competing solutions.
If you are a payment provider, learn how you can create a collaboration ecosystem for your merchants with Trusted Twin.