February Recap: The Rising Demand for Analysts
Exploring the latest trends in data science, product analytics, and market shifts.
Welcome to my Data Analytics Journal, where I write about data science and analytics. This month, paid subscribers learned about:
How to Create Decks That Don’t Suck - A guide to make strong presentation decks. Best practices and common mistakes analysts make.
How to Analyze Onboarding Flows - A deep dive into analyzing and reporting onboarding flows. Methods, frameworks, and examples of tracking complex user journeys.
Why Your Activation Analysis Is Wrong - And How to Fix It - How to identify the a-ha moment, different ways to calculate it, and what to do when you’re not getting a clear signal.
Today, I am back with a recap of key analytics updates from February, including recent analyses and industry reports, new tutorials, and anything important that shapes our work in data and analytics.
But first, a quick announcement - I am hiring a few positions to start ASAP:
BigQuery Data Engineer or Analyst - I need help setting up a BigQuery sandbox and spinning up a database with a batch load. Requirements: expertise in BigQuery and advanced SQL. If you have done this before, please reach out.
Senior Data Analyst - I am looking for a B2C transactional analytics expert to consult with me, review my approach to integrating different product personas into ecosystem KPIs, and help make reporting more digestible. Compensation: $350/hour. If you have done this before and are interested in consulting, please fill out this form.
Co-writer: I have a few upcoming trips and need help managing the newsletter while I’m away. Requirements: experience in blogging and analytics. This newsletter is written by an analyst for analysts, so fluency in data analytics is essential. If interested, please fill out this form.
🔊 Advocating for analytics
Remember my prediction that demand for analysts would rise this year? Well, guess what the latest data science job market report confirms - Data analyst roles are increasing by 25% MoM:
With AI acceleration, today, it’s as easy as ever to create an app or a SaaS. 2025 is expected to bring stiff competition for downloads, high mobile store rankings, market share, and, most importantly - customers. Success ultimately depends on understanding customer behavior and product usage. The demand for analysts will remain high.
📊 February highlights
Booking.com celebrated 20 years of experimentation
Can you imagine the wealth of their experimentation data and all the things they can do with it?
A new YouTube channel on product and analytics - The Beautiful Mess
John Cutler, the author of The Beautiful Mess is now on YouTube:
I admire John and have been following him since he led product at Amplitude. Happy to see he’s started a channel!
Amplitude introduced Guides and Surveys to support in-product engagements.
An interesting trend to watch is how Amplitude has repositioned itself from a product analytics tool to the Amplitude Platform, offering not only analytics, what we know it for, but also development and data management tools, including Experimentation, Targeting, Session Replay, Feature Management, Data Governance, and Guides and Surveys. From Spencer, Amplitude CEO:
“...This makes the Amplitude platform even stronger. If your growth team wants to offer different guides to different users at different times, Amplitude's cohorting makes it easy. If your marketing team wants to test new versions of in-product announcements to determine which are most effective, Amplitude's experimentation capabilities make it possible. If your product team wants to see whether user feedback matches what customers are doing in the app, Amplitude Session Replay lets you do this. With Amplitude, 1+1=11.”
This upsell strategy is great, but I hope it doesn’t come at the expense of providing the decent analytics tool we truly need.
2025 App Marketer Survey
Sensor Tower + AppsFlyer recently surveyed over 700 mobile marketers across various apps. They shared a report covers marketing industry health, campaign performance in 2024 and 2025, revenue growth trends, and more.
Key takeaways:
Time spent in apps is rising across nearly all major markets. According to Sensor Tower data, users globally spent 4.2 trillion hours in apps in 2024 - an average of 500 hours per person.
Most respondents agree that the past year was better for the mobile marketing industry than 2025:
KPIs are becoming more aggressive.
The push for new users becomes more competitive. Companies are under pressure to deliver consistent revenue growth.
Budgets are expanding to support ambitious KPIs. In 2025, companies spend more on campaigns than they did in 2024.
Three years in, many marketers are still struggling to see success with SKAN 😂.
Ad networks or self-attributing networks remain top priorities for mobile user acquisition.
And this one is my favorite: Mobile marketing teams are collaborating more closely with data and analytics teams:
“We asked survey respondents how their teams have changed in the last twelve months. Unsurprisingly, over half of respondents cite working more with data, analytics, and BI teams. 34 percent also mentioned that they or their team needed to acquire new technical skills 43 percent reported more work with product teams.”
Once again, this points to the growing demand for analysts.
⚙️Know your craft
Metric Trees for Digital Analysts - A great take from Timo on why metrics truly matter.
Quasi-experiments in ads measurement - The Bolt Data Science team shared steps for setting up counterfactual (predictive) experiments. This is a follow-up to their earlier piece, Mastering incrementality in ads: an introductory guide.
Estimating Incremental Lift in Customer Value - The PayPal Data Science team published a walkthrough of measuring the impact of user actions and product adoption at PayPal.
Revenue Automation Series: Building Revenue Data Pipeline - How Yelp developed a revenue data pipeline to support real-time revenue reporting and financial forecasting.
A non-beginner Data Engineering Roadmap — 2025 Edition from Ernani Castro. A skills and technologies roadmap for data engineers looking to level up.
RF matrix — Frequency dimension from Paul Levchuk - How to use frequency of usage as a proxy for user monetary value. Is Frequency a more important factor than Recency?
Why Pivot Tables Never Die from RillData - An exploration of how pivot tables continue to evolve and why they remain the key in BI.
Get KPIs Right! And, Metrics + Influencing Variables - Another great piece from Avinash Kaushik on Data Pukes. Sorry… Reports, dashboards.
🎓 Tutorials
SQL NOIR is one of the best SQL tutorials I have seen. A fun game designed to teach SQL. You run queries to track down the lead and solve the case.
21 Ways to Visualize Time in Tableau - I love this dashboard by Angela Drucioc, an analyst from France, which features 21 unique ways to visualize time series data. From bar charts to heat maps, area charts to calendars. Awesome.
📚 Weekend Longread
Microsoft shared a white paper on how they enable running ~100 A/B tests annually:
“At Microsoft, we run ~100k A/B tests annually using our internal Experimentation Platform ExP. To achieve this scale, we evolved ExP over the years, and one investment that truly enabled us to democratize decision making and make A/B testing effective across diverse organizations was to make ExP extensible. In this paper we describe how we enabled individual teams of experts across the company to contribute new extensions to ExP, the value this brings to the end users of the platform, and the impact that it has on the ExP team and practitioners building Experimentation Platforms.”
❤️ Favorite publications this month
The Data Leader’s Guide to Crucial Conversations from SeattleDataGuy.
The myth of measuring “data team ROI” from Barry McCardel. Hex
If spreadsheets are eternal, are BI tools transitory? From Jacob Matson, MotherDuck
Aligning Finance and Product for Success from Mostly metrics.
✈️ Upcoming events in March
March 6, Stanford: Women in Data-Driven Discovery (WiD3)
March 6, Sunnyvale: International Women’s Day Summit
March 7, Zell am See, Austria: Combining a Data Conference with Alpine Fun
March 12, San Francisco: Amplitude Wizard Bar - Live Office Hours + Meetup
March 13, Utrecht, Netherlands: Collaboration in product teams
March 18: San Fransisco: Low-Key Data Happy Hour
March 19, London: Experimentation London Meetup
March 26, Toronto: CDAO Canada 2025 - Deep Learning AI and ML Summit
March 28, Charlottesville: Women in Data Science (WiDS) 2025
It’s been a dark month if you’ve been following the news. If even possible, let’s try to smile more.
Thanks for reading, everyone!
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