Mozart Investor Interview – Karine Hsu

For our inaugural investor interview, we have Karine Hsu, one of Mozart Data’s first angel investors and co-founder of SLOPE Agency. We caught up with her to talk about investment strategy, her experience as both a founder and an investor, and why she chose to invest in Mozart Data.

Mozart Data: Tell us a little bit about your professional background and your current work at SLOPE Agency.

Karine Hsu: I started my career at Affirm. I was on the Analytics team so I was building out dashboards and working cross-functionally across Data Engineering, Product, and many other teams across the company to better understand the business trends we were seeing from our data. At Affirm, we worked with many fast-growing Ecommerce companies like Peloton, Casper, and more, and naturally, was inspired to start my own venture-backed D2C fashion brand. I ended up starting and selling my own D2C fashion brand that went through YC in 2017, where I began to realize how many analytics needs there were.

In 2019, I started SLOPE, a marketing and design agency that works with Ecommerce and tech startups. There aren’t very many agencies that specialize in working with startups, nor are there many that combine both marketing and design together under one roof. We want to be the agency startups go to for both brand and marketing work.

Mozart Data: What did your path to becoming an angel investor look like, and what are the areas you like to invest in?

Karine Hsu: I really started investing about two years ago. I was a Managing Partner of Dorm Room Fund when I was at Harvard, so I’ve been investing in student startups for a while. I found myself really gravitating towards three areas in particular — FinTech, real estate tech, and venture. The three companies I wanted to join coming out of school were Opendoor, AngelList, and Affirm. I think I’m good at identifying big, hairy spaces with hard problems like the ones those 3 companies were tackling.

At Affirm, I noticed that Ecommerce was a burgeoning area that I hadn’t considered before. I became interested in it, and made my first investment in MarketerHire, which works with Ecommerce companies to connect them with freelance marketers. I have a good amount of experience with FinTech, Ecommerce, and brands, so as an angel, I like to invest in companies that are in those fields.

I also love data and have recently started to invest in that space. I studied statistics in college and have worked on analytics teams in the past. Although I haven’t been on a data team in a few years, I am still very interested in it and regularly talk to people about how they use data at their companies.

Mozart Data: What do you look for in a team when investing?

Karine Hsu: A question I ask myself when evaluating a founding team is “Why are you starting a company?” I’ve had experience starting companies, and it’s a difficult undertaking, so I like to understand why the founders want to establish the company in the first place. The business and team can pivot a little bit or even a lot, but at the end of the day, the motivations behind why the founders started the company really drive it forward.

I also look at founder/market fit. There are definitely founders that can trudge through markets and problems that they’ve never had experience with, but those are pretty special people and not all that common. I think it’s always good for founders to have a solid understanding of the market they are starting their company in.

Mozart Data: What led you to invest in Mozart Data?

Karine Hsu: I met Pete (Mozart Data CEO) while working for Affirm, and when I found out he was working on a new company focused on the next evolution of data tools, it was a no brainer investment for me. People say data is the new oil, but if you don’t know where to get your data or how to interpret it, it isn’t really valuable. Companies can also end up reading too much into their data when you really shouldn’t be looking at every permutation. I think Mozart helps companies understand what data is actually the most important.

There are so many data tools out there, and no founder wants to go through the evaluation process for all of them. They just want someone to decide for them. Mozart is this quick and easy way to set up your data infrastructure without having to go through that decision process. I find that super compelling. I also think that Mozart’s focus on pulling data pipelines and data warehouses together first is really smart. Data visualization is actually a really hard problem so it would be difficult to focus on that as well in the beginning.

Pete’s experience in the data world is also kind of unparalleled, and he has a myriad of relationships and people around him to help jumpstart Mozart.

Mozart Data: How has your experience as a founder shaped the ways you add value to the companies you invest in?

Karine Hsu: I think the mental health side of being a founder is one of the most difficult parts. Being a founder can be very draining, both physically and mentally, and I like to make sure that the founders get the emotional support they need.

Within Ecommerce, FinTech, brands, and data, these areas where I’ve had more relevant working experience, I like to connect companies that I know will create mutually beneficial partnerships.

Mozart Data: What trends have you seen recently in the investing and data worlds? Any predictions for the future?

Karine Hsu: Quarantine has definitely accelerated investing as it’s been easier to chat and connect virtually over Zoom. You can see that with all the recent IPO announcements. There was also this big data movement back between 2015 and 2017, but I hadn’t seen much going on there until recently. I’ve noticed a lot of data companies popping up that are focused on security, as well as ones that are efficiency tools for data analysts. I think you’ll see a lot more of those types of data companies in the near future.

Thanks again to Karine for chatting with us for our first investor interview! Be sure to check our blog for more investor interviews throughout the year.


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