# measuring Published articles for measuring. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## The Causality Gap: Measuring the True Impact of Voluntary Adoption in Digital Marketplaces DevFeed: [The Causality Gap: Measuring the True Impact of Voluntary Adoption in Digital Marketplaces]() Original publisher: [Read original article]() Author: Lin Jia Published: 2026-05-22T08:05:43Z Content type: article Language: en Sources: [Booking.com Data Science]() Topics: [A/B Testing](), [doubleml](), [Data Science](), [Tool]() Tags: [a-b-testing](), [causal-inference](), [causal-machine-learning](), [causality](), [data-science](), [doubleml](), [e-commerce](), [experimentation](), [featured](), [measuring]() ### AI overview This article explains why standard A/B tests can mismeasure features that require voluntary adoption in digital marketplaces. It presents Randomized Encouragement Design combined with Double Machine Learning as a way to estimate both causal impact among adopters and overall rollout impact. ### Source excerpt by Lin Jia, Kexin Fei The Content of this post has been presented at Pydata Amsterdam 2026 and the slides can be found here TL; DR Whenever a feature requires voluntary adoption, standard A/B testing breaks: low adoption flattens the topline, and self-selection makes adopters incomparable to non-adopters. Combining Randomized Encouragement Design (RED) with Double Machine Learning (DoubleML) recovers two answers -- the causal lift for adopters and the rollout's overall impact. When they diverge, the gap turns an ambiguous topline into a sharp product decision -- build a better product, or build a better adoption funnel. 1. The Opt-In Barrier Across Demand and Supply Across the tech industry, many platform features rely on voluntary adoption. A customer chooses whether to claim a promotional discount. A traveller opts into a loyalty program. An e-commerce seller enables a smart-pricing tool. In every case, the platform cannot force adoption -- and the feature's true impact becomes hard to measure, on both demand and supply. At Booking.com this challenge spans both sides of the marketplace -- travellers choosing to log in, partners choosing to adopt new features. Unlike a search-ranking change that applies to 100% of traffic, opt-in features create a "trilemma" for Product Data Science: Voluntary Adoption (the "Opt-In" Barrier): Users must actively enable the feature. A standard A/B test cannot separate the product's effect from the motivation that drove users to adopt it. Extreme Heterogeneity: Travellers range from once-a-year holidaymakers to travel agencies booking thousands of nights; partners range from single-apartment hosts to hotel chains. This variance is noise on both sides. Finite Sample Sizes: Opt-in features target a finite sub-segment, so we cannot simply "run the test longer" to gain power. When these stack up, a flat topline can hide a strong product behind a weak adoption funnel. Genuinely strong features get killed, and resources flow into the wrong int ## Reduce latency and speed up your Temporal Workflows DevFeed: [Reduce latency and speed up your Temporal Workflows]() Original publisher: [Read original article]() Author: Joshua Smith Published: 2025-02-12T00:00:00Z Content type: tutorial Language: en Sources: [Temporal Blog]() Topics: [Latency](), [reliability](), [systems](), [Cloud](), [Network](), [Server](), [Transactions]() Tags: [cloud](), [durability](), [e-commerce](), [latency](), [measuring](), [optimizing](), [payment](), [problems](), [reduce](), [speed](), [system](), [techniques](), [temporal-concepts](), [workflows]() ### AI overview This tutorial explains how to reduce latency in Temporal workflows used by interactive applications while preserving durability and reliability. It identifies workflow startup, task scheduling, network calls, and activity execution as contributors to response time. ### Source excerpt Latency can be a challenge when responsiveness matters. The good news is, there are ways to make your workflows snappier without sacrificing durability. ## Measuring and analyzing the KotlinJS bundle size - Gustavo Fão Valvassori DevFeed: [Measuring and analyzing the KotlinJS bundle size - Gustavo Fão Valvassori]() Original publisher: [Read original article]() Published: 2024-02-16T00:00:00Z Content type: tutorial Language: en Sources: [Touchlab | Enterprise Mobile Innovation & Development]() Topics: [kotlinjs](), [Webpack](), [JavaScript](), [Web Development]() Tags: [analyze](), [article](), [devtools](), [gradle](), [gradle-plugin](), [javascript](), [kotlin-js](), [kotlinjs](), [lighthouse](), [measuring](), [performance]() ### AI overview This tutorial explains how KotlinJS projects are compiled into JavaScript and bundled with Webpack. It presents two ways to measure and analyze bundle size: examining source maps with SourceMapExplorer or Chrome Lighthouse, and using WebpackBundleAnalyzer. ### Source excerpt Smaller JavaScript bundle size helps improve a website's loading speed and performance. In this article, we present two different ways of analyzing and measuring KotlinJS bundle size. ## Visualizing your AAARRP priorities as a way to manage up in your DevRel team DevFeed: [Visualizing your AAARRP priorities as a way to manage up in your DevRel team]() Original publisher: [Read original article]() Author: Julien Published: 2023-12-12T09:46:10Z Content type: article Language: en Sources: [Thoughts, stories and ideas.]() Topics: [devrel](), [developer-relations](), [Framework]() Tags: [developer-relations](), [development](), [devrel](), [framework](), [management](), [measuring](), [strategy]() ### AI overview The article describes using the AAARRRP framework to visualize a Developer Relations team's strategy, explain activity priorities to internal stakeholders, and focus discussions on impact. It presents context from a small B2B DevRel team whose work emphasizes code, content, community, documentation, and samples. ### Source excerpt In this article, I'm describing how we used the AAARRRP framework to visually describe our DevRel team's strategy and clarify the reason for our day to day activities to our internal stakeholders, and more focus on impact instead. ## Measuring cost of spawning Goroutines DevFeed: [Measuring cost of spawning Goroutines]() Original publisher: [Read original article]() Published: 2023-09-17T00:00:00Z Content type: article Language: en Sources: [Gaurav Sarma's Blog]() Topics: [Concurrency](), [Benchmark](), [Go Language](), [Concurrent Programming]() Tags: [benchmark](), [concurrency](), [go](), [goroutines](), [measuring]() ### AI overview This article revisits a Go benchmark measuring goroutine-spawning patterns. The corrected experiment separates channel synchronization costs from goroutine creation and finds that the original conclusion favoring preallocated worker pools was imprecise. ### Source excerpt > 2026 update. The original version of this post compared three concurrency shapes by timing fixed batches of 1M / 10M / 100M / 1B operations and concluded "always pre-allocate... ## Why We Need to Stop Measuring (Developer) Productivity -- Part 1 DevFeed: [Why We Need to Stop Measuring (Developer) Productivity -- Part 1]() Original publisher: [Read original article]() Author: tobi@techunicorn.builders (Tobias Mende) Published: 2023-09-16T04:00:00Z Content type: opinion Language: en Sources: [Tobias Mende]() Topics: [code productivity](), [developer-productivity]() Tags: [collaboration](), [command-and-control](), [communication](), [culture-developer-productivity-leadership-metrics-engineering-excellence](), [developer](), [developer-productivity](), [leadership](), [measuring](), [productivity](), [trust]() ### AI overview This opinion argues that productivity metrics are difficult and potentially harmful when used as targets, especially under command-and-control leadership. It advocates leadership based more on trust, communication, and collaboration, and introduces concerns about measuring sales and engineering productivity. ### Source excerpt Why We Need to Stop Measuring (Developer) Productivity -- Part 1 Leaders are obsessed with productivity metrics. This is at least true for leaders who learned to lead in the last century. The ones that follow a command-and-control or carrots-and-sticks leadership approach. They need to measure each department individually to make the right decisions top-down. ## September 2023 - Bookmarks DevFeed: [September 2023 - Bookmarks]() Original publisher: [Read original article]() Published: 2023-08-31T22:00:00Z Content type: article Language: en Sources: [Domenico Luciani]() Topics: [code productivity](), [coding]() Tags: [coding](), [developer](), [developer-productivity](), [interview](), [links](), [measuring]() ### AI overview A September 2023 bookmark collection featuring 11 links, including resources about measuring developer productivity and passing a coding interview. ### Source excerpt Bookmarks for September 2023: 11 links - Measuring developer productivity? A respon...; How to pass a coding interview with me - R..., and more. ## Measuring Developer Experience - A Balanced Approach DevFeed: [Measuring Developer Experience - A Balanced Approach]() Original publisher: [Read original article]() Author: tobi@techunicorn.builders (Tobias Mende) Published: 2023-08-05T06:00:00Z Content type: tutorial Language: en Sources: [Tobias Mende]() Topics: [Developer experience](), [code productivity](), [developer-productivity](), [retrospectives]() Tags: [culture-developer-experience-developer-productivity-metrics-engineering-excellence](), [developer-experience](), [measuring](), [metrics](), [retrospectives](), [survey]() ### AI overview The article presents a balanced way to measure developer experience by combining quantitative and qualitative methods. It discusses surveys, eNPS, retrospectives, developer productivity metrics, turnover rates, and feedback channels, while noting that individual measures have limitations. ### Source excerpt Measuring Developer Experience - A Balanced Approach Developer Experience is one of the most essential factors for high-performing teams and organizations. Thus, the obvious question is how to measure, assess and understand the status quo within your organization and team. ## Ways to Decrease Performance: Velocity Tracking DevFeed: [Ways to Decrease Performance: Velocity Tracking]() Original publisher: [Read original article]() Author: tobi@techunicorn.builders (Tobias Mende) Published: 2023-07-15T06:00:00Z Content type: opinion Language: en Sources: [Tobias Mende]() Topics: [Agile](), [Software Engineering]() Tags: [agile](), [article](), [critical](), [measuring](), [metrics-practices-ways-to-decrease-performance-developer-productivity-engineering-excellence](), [performance](), [practices](), [story-points](), [teams](), [velocity]() ### AI overview This opinion article examines velocity tracking and estimation in Agile software teams. It explains how teams use story points, velocity trends, and burndown charts, then begins discussing how these practices can harm performance, including the limitations of human estimation. ### Source excerpt Ways to Decrease Performance: Velocity Tracking This is the first article of my series, "Ways to Decrease Performance", which intends to trigger critical reflection on common "Agile" practices, that is, practices that I see many "agile" teams doing. ## Measuring the Impact of Font Grade on Text Readability DevFeed: [Measuring the Impact of Font Grade on Text Readability]() Original publisher: [Read original article]() Published: 2022-05-11T09:00:00Z Content type: article Language: en Sources: [Material.io - Material Design]() Topics: [Font]() Tags: [measuring](), [readability](), [text]() ### AI overview This article examines how font grade affects text readability. ### Source excerpt Measuring the impact font grade has on text readability ## Incrementally measuring my internet speed with Prometheus DevFeed: [Incrementally measuring my internet speed with Prometheus]() Original publisher: [Read original article]() Author: Carlos Alexandro Becker Published: 2021-07-29T00:00:00Z Content type: tutorial Language: en Sources: [Carlos Becker]() Topics: [Prometheus](), [Internet](), [Grafana](), [Time Series](), [dashboards](), [k3s](), [Terraform](), [Helm charts]() Tags: [cache](), [dashboard](), [grafana](), [helm-charts](), [internet](), [k3s](), [measuring](), [metrics](), [modem](), [prometheus](), [providers](), [terraform](), [time-series]() ### AI overview A tutorial on measuring home internet speed every 30 minutes with a custom Prometheus exporter, storing the results in a time-series database, and visualizing them in Grafana. ### Source excerpt I live in Brazil, and, if you're not familiar, internet usually sucks here. ## How Engagement Systems Use Data to Provoke Political Outrage DevFeed: [How Engagement Systems Use Data to Provoke Political Outrage]() Original publisher: [Read original article]() Author: Adam Published: 2020-10-31T00:00:00Z Content type: opinion Language: en Sources: [Shostack & Friends Blog]() Topics: [data](), [systems]() Tags: [engagement](), [manipulation](), [measuring](), [optimizing](), [social-media]() ### AI overview The article argues that news and social media websites use data to measure and optimize engagement, showing users content tailored to provoke them. It recommends recognizing these tactics and reflecting on emotional reactions to reduce their influence. ### Source excerpt With three days to the US election, the outrage machines are running on all cylinders. It'll be easier to stay happy if you remember to notice them. ## Measuring ROI for DMARC DevFeed: [Measuring ROI for DMARC]() Original publisher: [Read original article]() Author: Adam Published: 2018-10-16T00:00:00Z Content type: article Language: en Sources: [Shostack & Friends Blog]() Topics: [email](), [Deployment]() Tags: [analysis](), [deployment](), [email](), [measuring](), [protection](), [report]() ### AI overview The article shares work by Shostack + Associates and the Cyentia Institute for the Global Cyber Alliance, including new threat models and statistical analysis for email. It reports that 1,046 domains using GCA's DMARC tools were estimated to save $19 million to $66 million in 2018 by limiting business email compromise, with further savings expected while DMARC remains deployed. ### Source excerpt I'm pleased to be able to share work that Shostack + Associates and the Cyentia Institute have been doing for the Global Cyber Alliance. ## A/B Split Testing with Nginx & Craft CMS DevFeed: [A/B Split Testing with Nginx & Craft CMS]() Original publisher: [Read original article]() Author: andrew@nystudio107.com (Andrew Welch) Published: 2017-05-10T18:52:00Z Content type: tutorial Language: en Sources: [nystudio107 | Articles on modern web development.]() Topics: [A/B Testing](), [nginx](), [Content Management System](), [Testing]() Tags: [a-b-testing](), [analytics](), [browser](), [chrome](), [cms](), [craft](), [developer-tools](), [doing](), [effectiveness](), [here-s](), [insights](), [measuring](), [nginx](), [pages](), [split](), [testing](), [useful]() ### AI overview This tutorial explains how to implement A/B split testing with Nginx and Craft CMS. It describes serving different page variants based on visitor information, persisting the assigned variant in a 24-hour cookie, and sending test data to Google Analytics as a custom dimension. ### Source excerpt Doing A/B split testing can be very useful in measuring the effectiveness of your pages; here's how to do it with Nginx & Craft CMS