Analysing SaaS Trial to Subscriber Conversions - Part 2 - Comparing Groups with Stratified Analysis
Introduction # You can read the Series Introduction here In the previous post, we saw how a Survival curve can be reframed as a Conversion Momentum Curve (CMC), giving us a way to esitmate when (counting in days from the start of a free trial period) we will reach conversion rate milestone of e.g. 5%, 10%, or 15% of free trial users. This is useful information because anything we can do to shorten the free trial period for our SaaS product offsets our fixed operating costs with new revenue.
Analysing SaaS Trial to Subscriber Conversions - Part 1 - Going Beyond the Binary Outcomes with Survival Analytics
Series Introduction # This is part one of a series on using Survival Analysis techniques for Product Management. Survival models excel at analyzing time-dependent events where timing matters as much as the outcome itself. Unlike time series analysis that tracks metrics evolving over time (and requires data collected at regular time intervals), survival analysis is event-based and asks a different question: when will something happen, and what influences that timing?
Educational Attainment in England - A Deeper Dive
Introduction # On the 25th July 2023, the UK Office for National Statistics produced a wonderful piece of data journalism with open access to their dataset measuring educational attainment across England. The article’s title “Why do children and young people in smaller towns do better academically than those in larger towns?” hides a bold claim in the form of a question. I like to assume that their research question(s) did not start from such a knowledge claim but rather the title emerged from the themes they discovered during their investigation.
Tech Stock Stories - The Pandemic Winners
As we breath a collective sigh of relief that the COVID-19 pandemic is behind us, it’s interesting to think about the winners and losers of this unique period of living memory. Judging by the stock performance of US tech giants, I’d say their shareholders did rather well while the rest of the world switched to remote work and spent all our time indoors. Please enjoy my Tableau Viz below, which is a candle chart of the stock performance of US tech giants during the pre- and post-pandemic period. We can see the month average highs, lows, opens and closes, and you can pick the company of interest from the drop down list on the right.
What is Analytics Engineering?
The well-known roles of the data team are Data Analyst/Scientist and Data Engineer. Yet, in recent years, there has been a growing demand for data-driven decision making to be distributed throughout the organisation, with a traditional data team at risk of becoming a bottle neck as the growing need for insights and analytics cannot be fully met. With this increased demand has come the emergence of a new role - the Analytics Engineer - for the typical data team to better encompass these evolving responsibilities, and specialist technologies. This evolution has led to a paradigm shift in data processes from Extract-Transform-Load (ETL) to Extract-Load-Transform (ETL), which facilitates a more self-service oriented Business Intelligence (BI) operating model where data analysts and data scientists can be more embedded with domain teams.