The hottest Analytics Substack posts right now

And their main takeaways
Category
Top Technology Topics
benn.substack • 1271 implied HN points • 19 Jan 24
  1. The modern data stack ecosystem is shifting as interest in generative AI takes over.
  2. The hype surrounding data tools can lead to rapid product development but also instability and distraction.
  3. Startups can find success by focusing on rebuilding existing ideas in a more deliberate and stable manner.
escape the algorithm • 579 implied HN points • 06 Feb 24
  1. Substack's network effects might be exaggerated: Data shows that most new subscribers come from sources other than Substack.
  2. Subscriber growth on Substack may not solely be due to Substack's technology: Many readers find newsletters due to recommendations from other writers or external sources.
  3. The power of a newsletter audience lies more in the people than the platform: Leaving Substack might not drastically impact growth as much as anticipated.
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Purple Insider • 294 implied HN points • 29 Jan 24
  1. Sunday's games were strange for Vikings fans to watch from a unique perspective.
  2. Building a championship team can involve having an all-time great quarterback, hitting on many draft picks, or building a strong supporting cast around an affordable quarterback.
  3. Success in the NFL requires making bold decisions and it's challenging to win even with a great team.
The Small Business Corner • 39 implied HN points • 06 May 24
  1. Craft a targeted marketing plan to save time and effort by focusing on potential customers with a detailed strategy that aligns with your business goals.
  2. Create engaging content that resonates with your audience, providing value and building trust over time to attract and convert followers into customers.
  3. Utilize social media platforms to connect with your target audience cost-effectively, engaging with users, choosing the right platforms, and leveraging analytics for success.
Gradient Flow • 139 implied HN points • 08 Feb 24
  1. AMD's hardware offers performance and efficiency gains for AI tasks, with specialized optimizations making them well-suited for training and inference in advanced AI scenarios.
  2. AMD has invested in mature and optimized open-source software like the ROCm stack, providing a critical foundation for maximizing the performance of their hardware in real-world AI applications.
  3. Market trends are aligning favorably for AMD, with shorter lead times improving chip availability, notable endorsements from industry leaders, and growing momentum indicating a strong position in the AI silicon landscape.
Data Analysis Journal • 373 implied HN points • 25 Oct 23
  1. Learning data is more accessible and better now than in the past years.
  2. For transitioning into data engineering, focus on SQL, programming, data warehouse, and data pipelines.
  3. Analysts should focus on understanding the business problem, building maintainable systems, and following a data analytics process.
The Better Letter • 196 implied HN points • 08 Dec 23
  1. Baseball's analytics revolution owes its existence to a smart security guard creating statistical analysis accessible and interesting.
  2. The success of 'Moneyball' accelerated the statistical disruption in baseball and led to the widespread use of advanced statistical measures in MLB.
  3. The Bill James approach transformed baseball analysis to be more objective, relevant, and useful, impacting team strategies and decision-making.
Data Analysis Journal • 452 implied HN points • 26 Jul 23
  1. The author reflects on three years of writing a newsletter about analytics, thanking supporters and subscribers.
  2. The author's newsletter aims to document their journey, bridge the gap between academics and industry, and encourage classic data analysis.
  3. The author shares insights on their writing strategy, the power of being small and independent, and future plans for the newsletter.
Topsoil • 511 implied HN points • 30 Jun 23
  1. Data in agriculture is essential for advancements like Generative AI, automation, and precision agriculture.
  2. Challenges in farm digitization include issues like connectivity, interoperability, data quality, trust, and incentives.
  3. Farmers derive value from data through decision-making, enabling technologies, sharing with advisors, compliance, and future income opportunities.
Web3 for Analytics Engineers • 1 HN point • 13 Jun 24
  1. Web3 is a decentralized internet on blockchain tech, aiming for user ownership and benefits for many people.
  2. Blockchain technology, at the core of Web3, offers immutability, decentralization, transparency, and cryptographic security.
  3. Web3 analytics introduces opportunities like decentralized data storage, on-chain data analysis, smart contract analytics, DeFi analytics, and NFT analytics.
timo's substack • 157 implied HN points • 27 Nov 23
  1. The concept of a Customer Data Platform (CDP) is evolving with a focus on defining its functionality more clearly.
  2. There is a trend towards composable CDP solutions, allowing for flexibility but also potential complexity.
  3. The key value of a CDP lies in activation - using customer data to create targeted audiences for more efficient marketing strategies.
Department of Product • 393 implied HN points • 22 Jun 23
  1. Some tech companies are experimenting with higher-priced subscription tiers to offer new features to exclusive users.
  2. Revenue generation is a key focus for many product teams, leading to new pricing strategies.
  3. Pricing experiments like launching super premium subscriptions are worth monitoring for trends in the industry.
davidj.substack • 47 implied HN points • 23 Feb 24
  1. Real-time data streaming from databases like MySQL to data warehouses such as Snowflake can significantly reduce analytics latency, making data processing faster and more efficient.
  2. Streamkap offers a cost-effective solution for streaming ETL, promising to be both faster and more affordable than traditional methods like Fivetran, providing a valuable option for data professionals.
  3. Implementing Streamkap in data architectures can lead to substantial improvements, such as reducing data update lag to under 5 minutes and delivering real-time analytics value for customers, showcasing the impact of cutting-edge data technology.
timo's substack • 314 implied HN points • 05 Jun 23
  1. Product analytics tools like Amplitude, Mixpanel, and Heap are evolving to offer new features like marketing attribution and user experience analytics.
  2. New players in the market like Kubit are focusing on providing product analytics directly on cloud data warehouses.
  3. The future of analytics is moving towards event analytics, opening up new possibilities and challenges for businesses.
Data Analysis Journal • 235 implied HN points • 28 Jun 23
  1. Embracing accelerated testing in the modern data analysis landscape is essential for success.
  2. The current traditional academic workflow for A/B testing may not be suitable for the evolving landscape of experimentation.
  3. To thrive in the era of rapid feature flagging and A/B testing, teams need to adapt by automating statistical checks, simplifying documentation, and eliminating bias.
Huddle Up • 22 implied HN points • 08 Mar 24
  1. The NFL is developing optical tracking technology to replace the traditional 'chain gang' for measuring first-down yardage.
  2. The NFL has been using RFID chips in footballs and players' gear for tracking player movements and collecting Next Gen stats.
  3. Introducing additional video review technology in the NFL could complicate the game over time and may not necessarily be a positive change.
Sarah's Newsletter • 359 implied HN points • 27 Oct 22
  1. Analytics should be a first-class citizen in crafting product launches to avoid wasted time and ensure measurable success.
  2. Utilize detailed agreements like Product Requirements Documents (PRD) and Analytics Requirements Documents (ARD) to align teams, outline goals, data criteria, assumptions, and finalize expectations.
  3. Involving analytics early in the product evolution lifecycle is crucial for gathering and analyzing data effectively, helping in decision-making, and ensuring alignment across technical and business teams.
timo's substack • 176 implied HN points • 12 Mar 23
  1. Focus on retention rate, especially first-week retention for free users, as a key metric for product analytics
  2. Retention analytics require solid user identification to track if users are returning and engaging with your product
  3. Measure retention with cohorts to understand performance over time, highlighting improvements or decreases in user retention
Jakob Nielsen on UX • 15 implied HN points • 13 Mar 24
  1. In A/B testing, the average uplift from design changes is small, about 0.15%, with 54% of cases showing improvements of 0.5%.
  2. Only 19% of experiments result in statistically significant gains, with an average lift of 1.0% across those cases.
  3. As companies mature in UX, gains from design experimentation may decrease over time due to the nature of tested designs and the diminishing low-hanging fruit.