Database Reference
In-Depth Information
Foreman typifies the data scientist who culls the latest data science techniques to
best serve his end users' needs. His prioritization of the end user informs his concep-
tion of his role as a translator between customers and the data science team and his
counterintuitive observation that overreliance on KPIs can harm the end-user experi-
ence. Foreman's thoughtfulness in selecting tools, his desire to help other data scien-
tists be successful, and his constant end-user orientation characterize his interview.
Sebastian Gutierrez:
Tell me about where you work.
John Foreman:
I work for MailChimp.com, which is a web application that
allows businesses to have email conversations with their customers. We help
about seven million customers send over ten billion emails a month, which to
me is very exciting. Whether large or small, nonprofit or for profit, businesses
choose us for the excellent user experience we provide for creating and
sending marketing email. Our application is exceptionally powerful yet simple
while still being playful and fun.
From a business point of view, it's great to help people connect with their
audience. From a data science point of view, it's exciting because we get back
all sorts of data about who was emailed, which people opened the email,
which people clicked on links, which links were clicked, which people went
to which websites, and then what they did on your own website. All of that
engagement creates this really fascinating set of data that we can then turn
around and use to create even more value for our customers.
Gutierrez:
Why is this data interesting?
Foreman:
If you think about a Facebook “like” in terms of following a page,
it's not entirely clear why you “liked” that page or company, as that's a very
public-facing action. The things you engage with on Facebook are very public.
They're partly for you, but they're also partly aspirational. They're actions for
the people watching you. Same with Twitter. Your actions on Twitter are also
aspirational. They're for the people looking at you.
However, it's the complete opposite with your email subscriptions, because
you're doing it for you. No one sees your email subscriptions except for you.
These are the newsletters you want to receive because you're actually inter-
ested in getting the content in your inbox, which is very different from the
notion of having the information be in a stream that you check in on every
now and then. So it's really fascinating to have this data because it represents
all of the subscriptions that you really wanted, as well as how you actually
interacted with them. For me personally, I get newsletters from places like my
church, my local pool, nonprofits I've engaged with in the past, and organiza-
tions like my local craft brewery store. So this data is a representation of a
wide range of interests that are more personal and a lot more interesting than
a “like,” “favorite,” or “follow.”
