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THE IMPORTANCE OF DATA IN THE EVOLVING PAYMENTS ECOSYSTEM<br />
PCM: Tell us a bit more about yourself (background<br />
and what led you to payments & Netflix<br />
specifically)?<br />
Kristen: I have been with Netflix since 2015, having<br />
joined just in time to help Netflix bring its internet<br />
television network to more than 130 new countries<br />
around the world. The timing could not have been better<br />
- it has been a remarkable challenge solving the puzzle<br />
of how to bring local payments to many new markets.<br />
As Netflix’s creative teams works to bring great stories<br />
from all over the world to people all over the world,<br />
the Global Payments team works to ensure potential<br />
members have a way to pay for their subscription.<br />
Prior to Netflix, I spent 8 years at PayPal where some of<br />
my notable projects included building the payment risk<br />
management infrastructure across EMEA and driving<br />
the migration from national direct debit schemes to<br />
SEPA Direct Debit. I also spent several years in tech<br />
consulting and payments / financial services regulatory<br />
innovation in both the United States and in Europe.<br />
PCM: How important is data analytics when<br />
selecting a payments partner?<br />
Kristen: At Netflix, we generally prioritize a partner’s<br />
data capabilities over all other qualities, including<br />
cost. What is most critical for us is having a partner<br />
who provides key data elements during a transaction.<br />
Typically, Netflix creates its own analytical tools using<br />
external payment events data from partners merged<br />
with other internal data elements, so it is important to<br />
receive reliable and rich partner data to make our tools<br />
and analyses as robust as possible.<br />
Our Global Payments team relies primarily on our<br />
internal data analytics and tools, and our strongest<br />
payment partners are nimble with their own data and<br />
can provide additional insights in a timely manner.<br />
Within a few clicks in our internal tools, we can analyze<br />
payments data at the country-, issuing bank- and even<br />
BIN-level, and when partners can match our agility, it<br />
allows us to move quickly and efficiently in building new<br />
optimizations. Combined with being able to understand<br />
our business objectives, data analytics capabilities are<br />
the driving factor behind our decision to partner.<br />
PCM: What role does data play in your organisation<br />
when it comes to payments and how has it affected<br />
your organisation?<br />
Kristen: Netflix is a famously data-driven company,<br />
and payments is no exception. Data enters every<br />
discussion: measuring business performance,<br />
identifying opportunities or anomalies, designing and<br />
analyzing experiments, or making strategic decisions.<br />
There is no payments optimization where approval or<br />
conversion rates are not discussed — everything we do<br />
is measured.<br />
PCM: What role does data play in your organisation<br />
when it comes to payments and how has it affected<br />
your organisation?<br />
Kristen: Netflix is a famously data-driven company,<br />
and payments is no exception. Data enters every<br />
discussion: measuring business performance,<br />
identifying opportunities or anomalies, designing and<br />
analyzing experiments, or making strategic decisions.<br />
There is no payments optimization where approval or<br />
conversion rates are not discussed — everything we do<br />
is measured.<br />
For testing new payment methods or optimizations, we<br />
prefer to run randomized A/B tests before rolling out<br />
changes. These tests may last a few days, weeks or<br />
months depending on the type of change being made,<br />
and to account for patterns in usage and traffic. Our<br />
100 million strong member base allows us to obtain a<br />
sample size relatively quickly, and this allows for rapid<br />
iteration and multiple system experiments to be run<br />
sequentially for optimization.<br />
We monitor these tests across many performance<br />
metrics to evaluate whether to productize a feature.<br />
Data-driven decision making complements Netflix’s<br />
company culture well. We trust our employees to do<br />
what they think is best for Netflix, and we realize this<br />
by ensuring they have the power to make informed<br />
decisions. In turn, this freedom generates a sense of<br />
responsibility and self-discipline that we believe brings<br />
better results for Netflix.<br />
A recent post in our Tech blog summed it up well:<br />
when you have highly talented individuals who have<br />
lots of great ideas, it’s important to have a framework<br />
where any new idea can be developed and tested. This<br />
ensures that intuition alone does not drive decisions.<br />
PCM: Taking a look at the payments landscape,<br />
what developments do you see in the future when<br />
it comes to data?<br />
Kristen: I expect to see analytics becoming more of<br />
a strategic product offering by innovative emerging<br />
payment companies. Some processing partners<br />
already offer very in-depth insight tools, which enables<br />
them to invest in data-driven optimizations,<br />
executed in real-time with a simple<br />
user interface that merchants<br />
can control themselves. We<br />
see more vendors moving in<br />
this direction as merchants<br />
shop around for the best<br />
approval rates.<br />
14<br />
PAYMENT COLLECTIVE
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