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Predicting the past: how big was the internet?
Ordinarily, data scientists spend a lot of time trying to predict the future. Time‑series prediction, recommendations, even next‑token‑prediction…they’ve all broadly got the same flavor. Recently, however, I came across a problem with a distinctly different taste, and I’d like to share it with you today: predicting the past. Surely predicting the past is pretty easy, right?…
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The WooCommerce Plugin Playbook: What Successful Stores Install, and When
Most plugin advice online is opinion‑dressed‑as‑fact: a list of “top 10 must‑have WooCommerce plugins,” usually written by someone selling one of them. We looked at hundreds of WooCommerce merchants who started a store in the past 12 months, and found a clear four‑phase pattern. At the same four points in their growth, stores reach for…
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From Support to Data Science and Analytics: My Journey at Automattic
“Is it possible to transform a role in customer support into a data science career?” This question, which once seemed like a distant dream, became my career blueprint at Automattic. This post describes the journey to a data wrangler in a tale of continuous evolution, learning, and adaptation.
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Hack Project: Creating a tool to translate customer feedback into product insights
Explore Automattic’s hack project in our latest post, where we developed a tool for analyzing Tumblr user feedback. Learn about our challenges with AI, creating insightful dashboards, and the impactful outcomes. Our collaborative effort not only enhanced product development but also earned us the top spot in our Hack Week Awards!
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How to Organize a Data Book Club at Work
Why a Book Club? Automattic has a creed that informs everything we do. And the very first part of the creed is “I will never stop learning”. The first and most important line of the creed means that you’re never finished. There is always more to learn. Your list of unread books is always going to…
