Database Reference
In-Depth Information
Furthermore, email data is powerful, because as a communications channel
it generates more revenue per recipient than social channels. That's why
companies are always asking you for your email address, not your Twitter
handle. A business can have a more personal conversation with you and
generate more revenue from a customer via than inbox than a waterfall of ads,
gifs, and the latest fear-mongering news.
Not only is the depth of this data powerful, but MailChimp is so large, that its
breadth and network effects become an asset. 60% of our business is interna-
tional. We send to three billion unique email addresses, making the network
of recipients of MailChimp's email about 10 times larger than Twitter's user
base. So it's really cool to think about and see in aggregate what people are
interested in and how they engage with the content. And not only that, this
is a dynamic data set, as some newsletters are daily, weekly, biweekly, or even
monthly. This means it's an evolving and growing data set. It's fun and really
cool to work with it.
Gutierrez:
What is it like working the MailChimp team?
Foreman:
I like the people at MailChimp because we're a very diverse group
of people, and we're very choosy about who gets to come in. MailChimp is
known not just as a solid, technically advanced product, which it is, but it's also
known as a really beautiful product. People have really paid attention to the
user experience and design within the application. So it looks beautiful, it feels
intuitive, and it's a very pleasant experience for folks to use. Because of all of
that, we've really spent a lot of time as a company bringing in the people that
can continue to make this happen.
Whether it's customer support, or knowledge-base, or the ops team, or the
dev team, or the creatives, or UX—the people at MailChimp are excellent
at what they do and very collaborative to boot. That makes MailChimp an
excellent place to be challenged. One day I might have an internal client who's
a graphic designer and the next day I'll be working with an anti-abuse officer.
All located in the same office in Atlanta. So I have to stay on my toes and keep
the internal customer in mind; a designer is going to understand and interact
with data products and research in a fundamentally different way than a devel-
oper, so I have to keep my ears open and my communication skills—verbal
and written—sharp.
When you talk to a designer, the way that they think about a problem and
the tools they employ to solve that problem are going to be very different
from, say, a data scientist or very different from a dev ops person. Those dif-
fering perspectives are healthy. There's a—perhaps apocryphal—operations
research story about an operations research [OR] person who was hired to
fix an elevator-scheduling problem. The OR person initially thinks that they
should build a model to solve the rush-hour traffic problem at this elevator
bank. Instead, they end up solving it by putting mirrors in the elevator so that
