The importance of data in the evolving payments ecosystem


In this month’s Payment Collective we interviewed Kristen Morrow-Greven, who is the Director of Payment EMEA at Netflix. She points out how data & analytics are creating value for organizatons and and customers alike. Moreover, Kristen shares some of her thoughts on the future of the payments landscape.


PCM: Tell us a bit more about yourself (background and what lead you to Payments & the Netflix specifically)?

Kristen: I have been with Netflix since 2015, having joined just in time to help Netflix bring its internet television network to more than 130 new countries around the world. The timing could not have been better - it has been a remarkable challenge solving the puzzle of how to bring local payments to many new markets. As Netflix’s creative teams work to bring great stories from all over the world to people all over the world, the Global Payments team works to ensure potential members have a way to pay for their subscription. Prior to Netflix, I spent 8 years at PayPal where some of my notable projects included building the payment risk management infrastructure across EMEA and driving the migration from national direct debit schemes to SEPA Direct Debit. I also spent several years in tech consulting and payments / financial services regulatory innovation in both the United States and in Europe.


PCM: How important is data analytics when selecting a payments partner?

Kristen: At Netflix, we generally prioritize a partner’s data capabilities over all other qualities, including cost. What is most critical for us is having a partner who provides key data elements during a transaction. Typically, Netflix creates its own analytical tools using external payment events data from partners merged with other internal data elements, so it is important to receive reliable and rich partner data to make our tools and analyses as robust as possible. Our Global Payments team relies primarily on our internal data analytics and tools, and our strongest payment partners are nimble with their own data and can provide additional insights in a timely manner. Within a few clicks in our internal tools, we can analyze payments data at the country-, issuing bank- and even BIN-level, and when partners can match our agility, it allows us to move quickly and efficiently in building new optimizations. Combined with being able to understand our business objectives, data analytics capabilities are the driving factor behind our decision to partner.


PCM: What role does data play in your organisation when it comes to payments and how has it affected your organisation?

Kristen: Netflix is a famously data-driven company, and payments is no exception. Data enters every discussion: measuring business performance, identifying opportunities or anomalies, designing and analyzing experiments, or making strategic decisions. There is no payments optimization where approval or conversion rates are not discussed — everything we do is measured. For testing new payment methods or optimizations, we prefer to run randomized A/B tests before rolling out changes. These tests may last a few days, weeks or months depending on the type of change being made, and to account for patterns in usage and traffic. Our 100 million strong member base allows us to obtain a sample size relatively quickly, and this allows for rapid iteration and multiple system experiments to be run sequentially for optimization. We monitor these tests across many performance metrics to evaluate whether to productize a feature. Data-driven decision making complements Netflix’s company culture well. We trust our employees to do what they think is best for Netflix, and we realize this by ensuring they have the power to make informed decisions. In turn, this freedom generates a sense of responsibility and self-discipline that we believe brings better results for Netflix. A recent post in our Tech blog summed it up well: when you have highly talented individuals who have lots of great ideas, it’s important to have a framework where any new idea can be developed and tested. This ensures that intuition alone does not drive decisions.


PCM: Taking a look at the payments landscape, what developments do you see in the future when it comes to data?

Kristen: I expect to see analytics becoming more of a strategic product offering by innovative emerging payment companies. Some processing partners already offer very in-depth insight tools, which enables them to invest in data-driven optimizations, executed in real-time with a simple user interface that merchants can control themselves. We see more vendors moving in this direction as merchants shop around for the best approval rates. Similarly, Netflix is testing ways to integrate data science into our payment engine. We have offline methods for optimizing payment processing and identifying fraud, but we want to move the bulk of these processes online to drive more impact. Additionally, we are focusing on enhancing our machine learning tools which can apply intelligent logic to support transaction routing and market-specific retry logic in real-time with the goal of improving our approval rates. As the industry becomes more data-driven, I hope to see more data sharing for collective benefit across the ecosystem. Payments-savvy merchants have already realized benefits from transparency with other merchants. If partners would share data from acquirers, networks, and issuers with merchants, the customer experience will benefit the most.


PCM: How will these developments affect your payment operations?

Kristen: As Netflix continues its global expansion, payment tools will likely get more complicated to support our growing network of processing partners and payment methods. As the number of different processing routes and configurations for a payment transaction increases, so will the amount of data and number of ways an event can improve or fail. It becomes ever more important to stay on top of critical metrics and ensure that we are constantly monitoring and testing for optimal performance. Additionally, expanding and integrating machine learning to our payments platform will bring us new opportunities to find and interpret patterns for optimization. As machine learning sends our vast amount of data through complex algorithms, it reframes our data which requires us to interpret the business impact and to find actionable insights for improving member acquisition and retention.


PCM: From a merchant PoV, what needs do you see coming up in terms of payments in the near future and what are you excited about most?

Kristen: In recent years, the global payments ecosystem has been evolving rapidly, with the emergence of startups that are finding new ways to enable consumers to pay and incumbents racing to evolve their business models so as not to become irrelevant. As a merchant, we stand to benefit from the vast amount of financial products being offered in the payments space, and I am excited to see how this develops further, particularly in emerging markets. Furthermore, I see innovative approaches in detecting and authenticating fraud for e-commerce payments. Card network tools like CVV and AVS are dated and ineffective compared to behavioral analytics, device ID, and other tools. Merchants like us embrace the idea of moving fraud detection to the background of the customer experience, but we need collaborative efforts between banks, regulators, and like-minded merchants in order to affect change.


About Kristen Morrow-Greven

Director of Payments EMEA at Netflix

With 10+ years in payments and e-commerce, Kristen is an experienced strategist who focuses on customer-centric and results-oriented solutions. At Netflix, one of the largest recurring billing merchants in the world, she is primarily responsible for expanding the offering of consumer payment methods to help with member acquisition globally and implementing front- and back-end optimizations for better performance.


About Netflix

Netflix is the world’s leading internet television network with 104 million members in over 190 countries enjoying more than 125 million hours of TV shows and movies per day, including original series, documentaries and feature films. Members can watch as much as they want, anytime, anywhere, on nearly any Internet-connected screen.