Meet Pasquale Prosperati, a mentor for Springboard’s Data Analytics Career Track.
One of Pasquale Prosperati’s favorite things about being a data analyst is that the work rarely feels repetitive. No two problems are alike, and most projects can be approached from different angles. That’s also why he loves being a mentor because it gives him the opportunity to help students from technical and non-technical backgrounds tackle a range of data analytics problems.
“Every single one of my mentees is a different human,” said Prosperati. “I get to explore this person’s world and learn more about what they do, where they come from.”
Having lived in five countries—including Singapore, Germany, Switzerland, New Zealand, and the US—Prosperati enjoys learning about different cultures and understanding how people think.
Now, he’s an e-commerce analytics manager at the Lego Group, where he collects and analyzes data on e-commerce sales of Lego products throughout the entire Asia Pacific region. Initially, he studied media and communications because he was interested in a career in advertising working on the creative side, but then he “fell into” data analytics while working on a university project for his Master’s degree where he had to gather and analyze his own data.
Tell me about your role at the LEGO Group. What is e-commerce analytics?
In the last few years, especially with the pandemic, sales have shifted more and more towards online versus offline. So Lego has expanded the teams who deal with online sales. Obviously, data is a big part of that. I joined Lego as the first person on the e-commerce analytics team, so it’s basically just me at this point. I work with all the data coming in from the online retailers in the Asia Pacific region.
What types of data do you look at specifically? What are some of the most important metrics in your industry?
The toy industry is very sales-driven, obviously, so the main metric is sales. When it comes to online sales, we look at other metrics like traffic, page views, conversion rates. Which products did better than others? On some retail pages we do advertising, so the question becomes, “How much did we spend and what was the return on investment?” I also deal with a lot of inventory data, which is new to me.
Retailers are starting to provide us with more sophisticated data so we can actually look at detailed shopper behavior in terms of retention, repeat buying, and which products they buy together. We also try to understand who the buyers are. Is it kids buying Legos? Is it adults buying Legos for their kids or for themselves? This helps us understand consumer needs and adapt accordingly.
Are there any surprising things that you’ve learned about Lego consumers?
A lot of Lego consumers are adults. Obviously, we have a lot of themes and products that are more geared towards kids and then some that are in between. People are very intense about Lego. didn’t realize how much people love Lego and you can see that in the data as well.
How did you come to work at Lego? What is it like to work for a brand that is so loved and has such a long history?
I’ve been spoiled. I worked at Spotify before and that is another brand that I loved. When you love the brand you don’t just put in your eight hours a day and be done with it; you really care about the product.
When everyone is so passionate about the product that you’re creating and selling, it’s just a different work atmosphere. Obviously, there are some downsides as well. Since the Lego brand is so big and established, trying to make changes on a small team isn’t easy. It’s like trying to get a big ship that has been going in the same direction for hundreds of years to change course.
I bet people get excited when they hear that you work at Lego.
Yeah. When I mention that I work at Lego people pull out their phones and show me photos of their Lego sets and builds, and I’m like, “Okay. I didn’t know you had a Lego room. That is interesting.”
What made you realize you wanted to pursue a career in data analytics?
I completed a Master’s degree in media and communications and in one of our class projects we had to gather and analyze our own data. I found that part of it to be super fun. After university I worked for a market research company and I became more and more curious about the data. Then I went from project-managing the data analysis team to actually doing my own analysis.
What is the most interesting project you’ve worked on in your career so far?
I’ve worked on a lot of super interesting projects. At Spotify I worked on the artist and fan development team to host exclusive events to bring fans and artists together. I provided support on the data side to answer questions like, how do we identify a fan based on their streaming habits? Who is the artist’s top fan? How do we reach out to them? My team consisted mostly of artist relations people who would work with the artists to create the events while my job was to find the audience for it.
On the day of the event I would see thousands of fans standing in line who were once just data points to me but now they’re actual people who have come to see an exclusive concert with their favorite artist.
Were the top fans selected based on their listening habits?
Yeah. It’s not just about the quantity of streams but the depth of the catalog. How many different albums did you listen to from that artist? Did you listen on the radio or your own playlist which has other songs from that artist? Sometimes I would email someone whom I had identified as a fan and they would write back and say “I’ve never heard of this artist.” Obviously, the data wasn’t perfect.
Let’s talk a bit about your experience with Springboard. What do you like most about being a mentor?
I’m an introvert so it’s wild to me that I spend almost 10 hours a week talking to people from completely different parts of the world who come from all sorts of backgrounds. It’s exciting to meet people who are on the journey towards becoming a data professional and being able to help them along.
What is something that you’ve learned from your mentees?
Every mentee is a different human, which is fascinating. Some of my mentees have never heard of Lego. People come from all different walks of life. You get to explore this person’s world and learn more about what they do, where they come from. At the end of the day, they all want to work with data and build their careers, but you have to learn to approach each person differently.
I see that you’ve worked in a number of different countries. What are some of the main advantages of having an international career?
Before the pandemic, one of the main advantages was being able to travel to surrounding countries. I’ve traveled all of Europe, the Caribbean, South America, Southeast Asia. In terms of the work, you get to understand different cultures. How do people work in other parts of the world? Why do they work this way? What is their way of thinking? As an analytics professional, I work with stakeholders from different backgrounds and I have to understand them. I can’t just be like, “Here’s the data. You figure it out.”
How has being a mentor helped with your own career development?
Sometimes, when you work in one profession for a long time, you become set in your ways and you start doing certain things on autopilot. Mentoring others has allowed me to take a step back and see things with fresh eyes. For example, one of my mentees might be working with pharmaceutical data, while another is interested in stock market data, and I have to help them brainstorm ways to approach the analysis. That has helped me become more mindful of what I’m doing.
You’ve worked in a variety of industries throughout your career. Would you recommend working in one specific industry for a long time to hone your domain knowledge, or is it better to work in a variety of industries?
I think it comes down to your personality type. I’ve always preferred variety but I also envy people who can just focus on one thing. I play guitar in a band but I don’t think I could have made it as a musician because I couldn’t have focused on just playing music. I still have so many other interests.
Is it easy to move from one industry to another without having experience in that industry?
Yes and no. During job interviews employers will ask about your experience in the industry, so you have to explain how you’ll add value. Maybe you’re a fast learner or you love learning how to work with different types of datasets. As long as your fundamental data analysis skills are strong, you should be able to figure it out. When I started at Lego, I knew very little about supply chains and inventory management, so there are certain things you just have to learn on the job.
What is your advice to someone from a non-technical background who is interested in becoming a data analyst?
People often think that having a non-technical background is a bad thing. I always tell them that their background is useful because they’re bringing domain knowledge. You can always learn the data analysis tools and techniques on top of that. The subject matter expertise is what sets you apart. No one wants to hire a data analyst who only knows how to run code but not how to apply data insights to the real world.
Want to become a mentor? Apply here!
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