Welcome to Issue 13 of my Data Analytics Journal newsletter, where I write about data analysis, data science, and business intelligence.
✨ In today’s newsletter:
Congratulations to the first recipient of the $1 million AAAI Squirrel AI Award.
Introducing product-led growth, a methodology where user acquisition, conversion, and retention are driven primarily by the product itself.
Navigating the impact of COVID-19 on analytics teams and projects.
SaaS Growth Metric One-Pager guide for data analysts - keep it close and reread as needed.
Open internship positions.
Let’s get started!
📚 Weekend Longread
There are many frameworks for developing products. They follow either a sales-driven or marketing-driven approach. Today I wanted to share an article from The Product-Led Growth Collective introducing a product-driven approach.
“Product-led growth (PLG) is a business methodology in which user acquisition, expansion, conversion, and retention are all driven primarily by the product itself. It creates company-wide alignment across teams—from engineering to sales and marketing—around the product as the largest source of sustainable, scalable business growth.”
In other words, the product-led approach is based on a free trial revenue model that allows users to experience the product without going through the sales/marketing layer. If you want to convert users into paying customers, your product must demonstrate the value within a short period of time. Read more to learn more about product-led companies and a go-to-market strategy.
🔥 What’s new this week
COVID-19 puts double pressure on team leaders and managers who have to support and protect their team during these challenging times, and, at the same time, ensure the full potential of AI and ML at their company is maximized. Research from McKinsey & Company highlights why companies with a heavy focus on ML technology are affected the most, and what leaders can do to keep their models and teams afloat.
Curious how much data scientists earn for developing ML algorithms? Here are statistics of industry job offers in AI at FAANG.
Congratulations to Regina Barzilay, a professor at the Massachusetts Institute of Technology for becoming the first recipient of the $1 million AAAI Squirrel AI Award (it’s like a Nobel Prize, but way cooler). She received the recognition for outstanding work developing ML algorithms for detecting cancer and designing new drugs.
I wanted to share some of her thoughts on AI from the recent interview:
There are so many patients, with so much accumulated data. How come we’re not using it?... I started using NLP to access it…
From this NLP work I then moved into predicting patient risk from mammograms, using image recognition to predict if you would get cancer or not—how your disease is likely to progress.
Why has AI not yet had much impact on COVID-19?
The main reason AI hasn’t been more useful is not the lack of technology but the lack of data.
AI doesn’t yet have the acceptance of society. I hope that this award, and the attention that comes with it, helps to change people’s minds and lets them see the opportunities—and pushes the AI community to take the next steps.
🏆 Nailed It
Be prepared for your next interview
Earlier in my career, I used to be intimidated by SaaS analytics (and still am). Analyzing and calculating KPIs for B2B or B2C is more straightforward. It is easy to define and group metrics by buckets:
Revenue - sales, profit, margin
Growth - MAU, retention, engagement
Marketing - acquisition, CPC, referrals
It’s not easy for SaaS. For SaaS business models, your user growth is heavily embedded in revenue. And, your revenue is all predictive analytics. And, your marketing becomes an important driving force merged into most of your KPIs. You have to be very careful and more precise in estimations and annual projections.
I do believe data analysts in SaaS age faster.
This week I published my second One-Pager - SaaS Growth Metrics. It covers the most important SaaS KPIs you will be working with:
MRR - new MRR, churned MRR, net new MRR
Churn - customer and revenue churn
CAC, months to recover CAC
I also provided some estimations to give you an idea of how to determine your product health and covered some analysis specifics for churn, LTV, and MRR.
Each of those KPIs must be adapted to the company product or service and might have its own variations. However, the basics and concepts stay the same and will guide you to the light.
One-Pager is a short brief guide covering only the essential information you need - formulas, concepts, red flags, and must-know terminology.
🎓 Level Up
Certifications, internships, schools, and courses.
Open internship for a Data Analyst - American Chemical Society is currently seeking an Intern for the Summer of 2021 with SQL, R, or Python knowledge.
Open internship for ML Engineer- The Broad Institute of MIT and Harvard is looking for 6-month grad + undergrad interns. They work on building open source tools and models to work on cutting-edge cardiovascular science, in conjunction with ML scientists, engineers, and top clinical & genetic researchers. If you are interested to apply, respond to this email or contact me at firstname.lastname@example.org with your resume, and I’ll put you in touch with a recruiter.
🍸 Drink and Mingle
Upcoming free events, meetups, talk, webinars
Oct 7, At Internet: Data Model Strategy – Align Analytics with Your Business
Oct 7, Anaconda: Securing Open-Source Data Science in the Enterprise
Oct 7, Provectus: MLOps and Reproducible ML on AWS
Oct 8, Galvanize: Intro to SQL and RDBMS
Oct 13, PyLadies: Monitoring your Python Apps with Prometheus & Grafana
Oct 14, Tableau: Mitigating Bias in Analytics
Oct 20, Neo4J: NODES 2020 Neo4j Online Developer Expo and Summit
Oct 28, Anaconda: Working with Data in the Cloud
Thanks for reading everyone. Until next Wednesday!