Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… Using data science to help people write Using machine learning models to generate text, images, and other creative objects is, as they say, a bit of a hot topic right now. There are examples of models like this in action all across the internet and across different fields and disciplines. Today, we discuss one of those fields in more depth: marketing. In particular, the Klaviyo data science team recently released...

Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… Writing code for computers and people No matter what sort of data science work you do, it’s fairly inevitable that you’ll have to write code to accomplish your goals. For substantial projects, it’s also fairly inevitable that you’ll have to work with other people to see them to completion. As anyone who’s dived into a legacy code base can tell you, writing code that other people (and yourself in the future) can...

Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… What are data privacy and security? Data privacy and security are huge and hugely important topics — in all likelihood, you already know a little about them if you’re reading this intro. But they are both crucial to any good data science work, and this month we explore the fundamentals of both topics: why data privacy and security are necessary to deliver the value you promise your customers, who they matter the...

Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… Customer-focused research This month, we focus on research — but specifically research that’s aimed at your customers, delivering the sort of insight they would try to glean by running experiments and analysis using their own data. In particular, we dive into two different case studies drawn from the recent topics explored by the Klaviyo data science team. You’ll hear about: Why customer-focused research can be...

Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… 2021 Year in Review Once again, as the new year starts, we begin by recapping the old. Instead of diving deep into a specific topic, I asked 7 members of the Klaviyo data science team to give their personal highlight for 2021 as a year in data science. You’ll hear about fascinating data science topics, including: How companies used domain knowledge to hyper-charge their ranking algorithms Powerful estimating...

Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… Customer research: your secret weapon You can study as much mathematical theory, invent as sophisticated a machine learning model, or write as clean production-ready code as you want — if you don’t make sure you’re solving the right problems to begin with, all that effort could be for nothing. It’s not a topic you learn about in most data science coursework, but understanding your end customer is a crucial part of...

Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… Fuel for the Creative Fire It’s no secret: being creative is hard. Creativity requires time and energy, at the bare minimum, and lacking creativity can spiral into writer’s block and other such conditions. That may be okay if you’re just sending out a tweet here or there — but what if your core user base consists of people who need to be creative, day in and day out? The Creative team at Klaviyo recently tackled...

Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… Slow Problems, Quick Solutions We’ve devoted quite a bit of time on this podcast to robust, carefully tuned, and vetted-in-a-thousand-ways solutions. This episode, we venture beyond the land of neatly trimmed hedges and into the unknown, where scrappy solutions may be the only ones that are feasible — or even possible. And we’ll hear about settings where a quick calculation on a napkin can be the difference between...

Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… Solving difficult problems with data science This month, we talk with Shane Suazo, the founder of Plytrix Analytics, about using data science to drive efficient business growth. Shane and Plytrix work with Vital Proteins, and we dive deep into their story and highlight the places where using specific — and powerful — data science techniques helped accelerate a growth opportunity into a growth story. You’ll hear...

Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… (More) required reading for data science A question we frequently get asked is: what books should I read to be a better data scientist/machine learning engineer? This may not surprise you, but there isn’t just one answer — in fact, we spent an entire episode talking about three ways to level up your data science knowledge and skills. This month, we’re back with three more: One of the foremost foundational texts...

Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… Getting real value from data science This week, we talk with Ben Knox from Super Coffee and Gina Perrelli from Lunar Solar Group about using data science to motivate the growth of a business. No hypothetical business cases this week — Super Coffee is a real business with a real growth story, and we’re here to showcase the ways that they have partnered with Lunar Solar Group and used inquisitive problem-solving...

Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… Making your product experiments count We’ve talked about quite a few aspects of data science on this podcast, but one that’s perhaps conspicuously absent so far is running experiments on your product. It’s no secret that experiments provide extraordinarily high-quality data to help you make decisions, but it’s also no secret that you only get good experimental results if you run good experiments. You’ll hear about...

Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… Recruiting for a data science team Most of us reading this writeup have probably had at least one interaction with a recruiter. Most of us reading this writeup probably don’t have a deep knowledge of recruiting — what recruiters do, how they help teams scale, and what the other 90% of the iceberg you don’t see as a candidate consists of. Recruiters are on the front lines of attracting talent and making sure that a...

Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… Required reading for data science A question we frequently get asked is: what books should I read to be a better data scientist/machine learning engineer? This may not surprise you, but there isn’t just one answer — depending on the skills you have, your knowledge base, the point of your career that you’re in, and many other factors, there are many books you could read that will help you learn more. This month, we...

Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… Understanding your Customer Lifetime Value This is a math-heavier episode than usual — we’re going to dive into probabilistic distributions and talk about systems of estimators. Even if that’s not your background, though, you should still find this episode useful. That discussion is all based in something crucial to real-life businesses around the world: customer lifetime value, or CLV. What exactly does CLV tell...

Benchmarks: what are they and why? You’ve probably heard of benchmarks. You’ve probably even used them. But what exactly are benchmarks, how are they useful, and how can you go about building a system to make benchmarks in your own industry? You’ll hear about all that and more, including: How to use benchmarks to make informed decisions about improving your business Why the humble stoplight served as a key insight for making complex math understandable How to assess your personal levels...

Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… 2020 Year in Review We have a bit of a different episode this month. Instead of diving deep into a specific topic, I asked 14 members of the Klaviyo data science team to give their personal highlight for 2020 as a year in data science. You’ll hear about a bunch of fascinating data science topics, including: Using machine learning to take a quantum leap in drug discovery Discovering methods from much older years...

Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… Engineering Challenges in Data Science All data science work at scale rests on a solid foundation of engineering. We discuss how to establish that foundation — from what goes into software engineering to begin with to the specifics of how to prepare for big seasonal events like Black Friday and Cyber Monday. You’ll hear from software engineers on the team about: Why building software is a lot like running a bar ...

Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… Seasonality in e-commerce As the calendar changes, so do the right steps to take for your e-commerce business. We wade into the waters of seasonal changes in behavior, data, and logistics, and we take a deeper look at how to navigate them. You’ll hear from data scientists and product analytics about: The fact that gardening is sometimes more powerful than the biggest holiday of the year Why you should stop...

Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… Recommender systems: how do they work? We get recommendations for all sorts of things today: routes to take when we drive, places to eat, books to read, petitions to sign, and of course, things to buy. We take a deeper look at the task of making the data science and software systems that dispense useful recommendations at scale, with a special focus on recommending ecommerce products. You’ll hear from data...

Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… What makes a report good? Data-centric teams likely take it as a given that good reporting is a key to living a happy life, but what exactly makes a report good? We dive into the topic of reporting and discuss ways to make a report exceed expectations. You’ll hear from data scientists and product designers about: Why bad reports may be worse than no reports Why good reports may be more like the movie Inception...

In this episode, we take a deep dive into a recent feature the team built, signup form A/B testing, to give you a taste of what it’s like to build software for data science. You’ll hear from data scientists, product designers, and software engineers. We discuss: The reason multi-arm bandits are called multi-arm bandits How to distill a two-minute explanation into a single word The way people think about randomness, and what that means when you’re designing a feature that involves...

In this episode, we discuss how our careers in data science began, lessons we’ve learned along the way, and mistakes we’ve made and learned from. You can expect to hear: When we stopped wanting to be astronauts and started wanting to be data scientists Advice we’d give to anyone just starting in the field Advice we’d give to anyone currently at the helm of a dinosaur-based movie franchise Resources We mention a few books and other resources in the course of this episode. Check them out...

We’re excited to unveil the first episode of the Klaviyo Data Science podcast! This podcast is intended for all audiences who love data science--veterans and newcomers alike, from any field, we’re all here to learn and grow our data science skills. We’re jumping right into the action with this episode. This is a deep dive into research in action. We’ll learn about what’s happening in the world of ecommerce in the wake of COVID-19, and more importantly how we figured out what’s happening....