Klaviyo Data Science Podcas‪t‬ Michael Lawson

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 of spice intake

Mentioned this episode
Some more reading or viewing that we mention in this episode:


2020 in review using benchmarks: https://www.klaviyo.com/blog/ecommerce-benchmarks-2020-email-marketing
The benchmarks feature announcement video, featuring the one and only Data Science Santa: https://youtu.be/Ge5zvOQVLDc?t=298
The Klaviyo benchmarks feature page: https://www.klaviyo.com/features/benchmarks
The Klaviyo benchmarks announcement post: https://www.klaviyo.com/blog/benchmarks-ecommerce-performance

About Klaviyo
Klaviyo helps growth-focused ecommerce brands drive more sales with super-targeted, highly relevant email, Facebook, and Instagram marketing. Interested? We’re always looking for great people to join our team.

Contact me
The best place to reach the podcast is by messaging me on Twitter: https://twitter.com/lawson_m_t.

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 that are still relevant for the problems of today
How 2020 provided some new opportunities — and some sobering real-world stress tests — for data science

Full Episode Notes

See https://medium.com/klaviyo-data-science/klaviyo-data-science-podcast-ep-8-2020-a-data-science-year-in-review-88be9b534183.

Contact Me

Contact me on twitter: @lawson_m_t

Corrections
This podcast was recorded in January 2021, before Abigail Thorn publicly came out as transgender. It currently refers to her by her former name, but will soon be edited. Congrats to Abigail!

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
How to make things be — or at least seem — real-time
How a tiny leak can crash a whole system

Full show notes available at https://medium.com/@michael-lawson-96765/klaviyo-data-science-podcast-ep-7-laying-a-stable-engineering-foundation-ba6462aa0db.

Contact us: @lawson_m_t on Twitter.

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 worrying and love the error bars
How to immortalize yourself as a data science meme

Full show notes are available at https://medium.com/@michael-lawson-96765/klaviyo-data-science-podcast-ep-6-navigating-seasonality-in-e-commerce-1bac11b8bf13.

Contact us: @lawson_m_t on Twitter.

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 scientists and engineers about:


The best (and worst) recommendations we’ve ever gotten
How the recommendation systems you take for granted actually work under the hood
Why dining room tables are basically the same thing as people’s favorite colors

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 than you think
How to design reports with your target audience in mind