# Ecommerce Published articles for Ecommerce. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## When scanners miss the attack: how Cloudflare Client-Side Security protects storefronts DevFeed: [When scanners miss the attack: how Cloudflare Client-Side Security protects storefronts]() Original publisher: [Read original article]() Author: Denzil Correa Published: 2026-09-16T20:06:17Z Content type: article Language: en Sources: [Cloudflare Blog]() Topics: [Cloudflare](), [Machine Learning, Security Attacks](), [Security](), [JavaScript]() Tags: [ai](), [application-security](), [attacks](), [client-side-security](), [cloudflare](), [cybersecurity](), [developer-platform](), [developers](), [ecommerce](), [javascript](), [machine-learning](), [malicious-javascript](), [page-shield](), [security](), [security-research](), [virustotal](), [workers-ai]() ### AI overview Cloudflare describes how its Client-Side Security machine learning model detected four malicious JavaScript operations involving eight payloads in live storefront traffic. The post says humans verified the findings after automated detection, while most payloads were absent from VirusTotal and received no malicious verdict from URLScan. ### Source excerpt A modern storefront can look healthy while malicious JavaScript quietly siphons revenue, hijacks clicks, or rewrites analytics. See how Cloudflare's machine learning models surface evasive client-side attacks for analyst investigation. ## From alert to resolution: Manage incidents with Bits Chat in Slack DevFeed: [From alert to resolution: Manage incidents with Bits Chat in Slack]() Original publisher: [Read original article]() Author: Nancy Zhu; Evan Marcantonio; Nicole Parisi; Chris Miller Published: 2026-09-16T00:00:00Z Content type: tutorial Language: en Sources: [Datadog | The Monitor blog]() Topics: [incident](), [Slack](), [Artificial Intelligence](), [telemetry](), [Code](), [Pull Request]() Tags: [ai](), [also](), [bits-ai](), [code](), [collaboration](), [ecommerce](), [incident](), [monitor](), [root-cause-analysis](), [slack](), [telemetry]() ### AI overview This tutorial explains how Bits Chat in Slack can support incident response by investigating alerts, analyzing telemetry, coordinating responders, generating a pull request for a fix, and tracking follow-up work within the incident channel. ### Source excerpt Use Bits Chat in Slack to investigate incidents, collaborate with responders, make code fixes, and capture follow-up work where your team communicates. ## B2B Medical & Pharma UX Benchmark: 3,400+ Performance Scores and 2,600+ Best Practice Examples DevFeed: [B2B Medical & Pharma UX Benchmark: 3,400+ Performance Scores and 2,600+ Best Practice Examples]() Original publisher: [Read original article]() Author: Anders Nielsen Published: 2026-09-15T09:30:00Z Content type: article Language: en Sources: [Baymard Institute]() Topics: [User experience (UX)](), [Testing](), [web applications](), [Mobile]() Tags: [b2b](), [benchmark](), [desktop](), [ecommerce](), [mobile](), [performance](), [research](), [testing](), [ux]() ### AI overview Baymard reports on a UX benchmark covering 10 B2B Medical & Pharma ecommerce sites, assessed across more than 400 research-based UX parameters. The sites ranged from poor to mediocre overall, with recurring issues in product information, pricing, search, and collaborative cart workflows. ### Source excerpt (Note: Unfortunately, e-mail and RSS don't support advanced layouts and features. If the graphics in this article look strange, you may want to read the article in your web browser.) At Baymard, we've just released a new UX benchmark with 10 "B2B Medical & Pharma" UX case studies. This follows from our large-scale user testing and adds to our existing ecommerce UX benchmark. In this article, we give you a snapshot of the overall UX performance. 10 B2B Medical & Pharma UX Case Studies and the Overall Performance AbCam mediocre B2B Medical & Pharma 40 page designs: desktop, mobile Waters mediocre B2B Medical & Pharma 38 page designs: desktop, mobile Allegro Medical mediocre B2B Medical & Pharma 41 page designs: desktop, mobile Medline mediocre B2B Medical & Pharma 25 page designs: desktop, mobile Cole-Parmer mediocre B2B Medical & Pharma 50 page designs: desktop, mobile Mckesson poor B2B Medical & Pharma 22 page designs: desktop, mobile Thermo Fisher poor B2B Medical & Pharma 42 page designs: desktop, mobile Henry Schein poor B2B Medical & Pharma 38 page designs: desktop, mobile Bound Tree Medical poor B2B Medical & Pharma 41 page designs: desktop, mobile Sigma Aldrich poor B2B Medical & Pharma 41 page designs: desktop, mobile YourSite.com? Want to know how your site performs? Get Premium access to review your own site or have it audited by Baymard researchers. These are the 10 in-depth B2B Medical & Pharma UX case studies. The 10 sites have been manually assessed across 400+ research-based UX parameters relevant to B2B Medical & Pharma, resulting in 3,400+ weighted UX performance scores and 2,600+ best practice examples from these desktop and mobile sites. Each of the 3,400+ UX performance scores from the 10 B2B Medical & Pharma case studies is summarized in the interactive scatterplot below -- showing you how they perform collectively and individually: {{ scatterplot-graph: size=big + habitat=public + base-sites=collection:medical-pharma + view-structure-id=gemini-st ## How to Design Gifting Features People Actually Use: Evidence from 58 Apps DevFeed: [How to Design Gifting Features People Actually Use: Evidence from 58 Apps]() Original publisher: [Read original article]() Author: Anamol Rajbhandari Published: 2026-09-14T13:58:38Z Content type: article Language: en Sources: [freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More]() Topics: [App](), [SQL]() Tags: [apps](), [article](), [design](), [developer](), [ecommerce](), [research](), [sql](), [ux]() ### AI overview The article examines whether gifting features are worth building into consumer apps. Drawing on research across 58 apps, it identifies gifting scenarios, the triggers that prompt people to send gifts, and the costs and design work involved in implementing them. ### Source excerpt American shoppers spent about $29 billion on gift cards over the 2025 holiday season, and 43 percent of them bought at least one. This put gift cards at the top of what people said they wanted accordi ## Telco UX Benchmark: 3,100+ Performance Scores and 2,400+ Best Practice Examples DevFeed: [Telco UX Benchmark: 3,100+ Performance Scores and 2,400+ Best Practice Examples]() Original publisher: [Read original article]() Author: Anders Nielsen Published: 2026-09-01T08:45:00Z Content type: article Language: en Sources: [Baymard Institute]() Topics: [web applications](), [GUI]() Tags: [article](), [benchmark](), [case-studies](), [comparison](), [ecommerce](), [mobile](), [performance](), [research](), [testing](), [ux](), [web]() ### AI overview Baymard presents a Telco UX benchmark based on seven case studies, manually assessed across more than 500 research-based parameters. The benchmark reports poor overall UX performance and highlights unclear plan and specification labels, weak comparison tools, missing contract and device terms, and incomplete warranty, returns, shipping, delivery, and discount information. ### Source excerpt (Note: Unfortunately, e-mail and RSS don't support advanced layouts and features. If the graphics in this article look strange, you may want to read the article in your web browser.) At Baymard, we've just released a new UX benchmark with 7 "Telco" UX case studies. This follows from our large-scale user testing on Telco UX and adds to our existing ecommerce UX benchmark. In this article, we give you a snapshot of the overall UX performance. 7 Telco UX Case Studies and the Overall Performance AT&T mediocre Telco 51 page designs: desktop, mobile Xfinity poor Telco 47 page designs: desktop, mobile Lebara poor Telco 45 page designs: desktop, mobile Orange poor Telco 56 page designs: desktop, mobile Vodafone UK poor Telco 49 page designs: desktop, mobile Bell poor Telco 44 page designs: desktop, mobile Verizon poor Telco 49 page designs: desktop, mobile YourSite.com? Want to know how your site performs? Get Premium access to review your own site or have it audited by Baymard researchers. These are the 7 in-depth Telco UX case studies. The 7 Telco sites have been manually assessed across 500+ research-based UX parameters relevant to Telco providers, resulting in 3,100+ weighted UX performance scores and 2,400+ best practice examples from these desktop and mobile sites. Each of the 3,100+ UX performance scores from the 7 Telco case studies is summarized in the interactive scatterplot below -- showing you how they perform collectively and individually: {{ scatterplot-graph: size=big + habitat=public + base-sites=collection:telco + view-structure-id=gemini-st_47eezi8l }} The overall UX performance of the Telco sites is "poor," with only 1 site in the "mediocre" range. Here are some of the overarching UX issues. On the benchmarked sites, proprietary plan names and technical specifications were presented as labels without explanation. No site explained its industry-specific filters or provided inline help for technical specifications within comparison features, and plan feature ## The Hidden Cost of Bad UX: How Much Revenue Are You Leaving on the Table? DevFeed: [The Hidden Cost of Bad UX: How Much Revenue Are You Leaving on the Table?]() Original publisher: [Read original article]() Author: Christian Holst Published: 2026-08-19T08:12:00Z Content type: article Language: en Sources: [Baymard Institute]() Topics: [User experience (UX)](), [Usability](), [web applications](), [coding]() Tags: [article](), [best-practices](), [business](), [checkout](), [cost](), [design](), [ecommerce](), [insights](), [leadership](), [metrics](), [product](), [research](), [revenue](), [usability](), [ux]() ### AI overview Baymard presents an Opportunity Sizing Calculator that estimates the revenue recoverable from reducing ecommerce UX friction. It translates user research and usability improvements across areas such as checkout, navigation, and product pages into projections that can support roadmap prioritization, budget decisions, and executive buy-in. ### Source excerpt (Note: Unfortunately, e-mail and RSS don't support advanced layouts and features. If the graphics in this article look strange, you may want to read the article in your web browser.) How much revenue is your site losing each month because of unnecessary UX friction? If you are like most ecommerce leaders or UX managers, you know that friction points across checkout, product pages, and navigation cause shoppers to abandon. Yet, when competing for roadmap resources or budget approvals, UX research is often categorized as an internal software or subscription expense rather than a top-line revenue driver. Without concrete financial estimates to back up your design priorities, critical usability improvements often get pushed aside. To help you translate UX friction into clear commercial impact, Baymard has developed an Opportunity Sizing Calculator. This tool converts Baymard's actionable user research into quantifiable projections, showing you the exact revenue you can unlock by systematically applying proven UX best practices to your site. Moving from Opinions to Research-Backed Forecasting Prioritizing a product roadmap often turns into a debate of subjective opinions, where the loudest voice in the room or the most senior person's viewpoint takes priority. UX designers and product managers must frequently advocate for critical usability fixes against competing internal requests, relying on qualitative arguments that struggle to secure executive support. Baymard's Opportunity Sizing Calculator bridges the gap between design priorities and executive decision-making, helping you secure buy-in. This means you're better able to: Connect specific usability insights directly to top-line revenue Build an unshakeable business case for leadership Give directors and VPs clear line-of-sight into the ROI of resolving site friction Get your personalized opportunity metrics: Book a short call with our team and find out how much revenue you could recover with better UX. Book a demo ## 10 ecommerce website examples: Build a better storefront DevFeed: [10 ecommerce website examples: Build a better storefront]() Original publisher: [Read original article]() Author: Webflow Team Published: 2026-08-18T00:00:00Z Content type: tutorial Language: en Sources: [Webflow Blog]() Topics: [Website](), [AI search]() Tags: [ai](), [build](), [design](), [ecommerce](), [examples](), [navigation](), [product]() ### AI overview A guide to 10 ecommerce website examples, explaining how product organization, navigation, visuals, copy, brand storytelling, practical details, and supporting information can improve online shopping experiences and build trust. ### Source excerpt Explore 10 ecommerce website examples that offer practical design lessons to help you improve product pages, navigation, and visuals for your online store. ## Food Delivery & Takeout UX Benchmark: 3,100+ Performance Scores and 1,900+ Best Practice Examples DevFeed: [Food Delivery & Takeout UX Benchmark: 3,100+ Performance Scores and 1,900+ Best Practice Examples]() Original publisher: [Read original article]() Author: Anders Nielsen Published: 2026-08-13T08:01:00Z Content type: article Language: en Sources: [Baymard Institute]() Topics: [Benchmark](), [User experience (UX)](), [App](), [web applications]() Tags: [apps](), [article](), [benchmark](), [case-studies](), [customer](), [ecommerce](), [insights](), [mobile](), [performance](), [research](), [retail](), [user-testing](), [ux]() ### AI overview Baymard presents a Food Delivery & Takeout UX benchmark based on eight mobile sites and apps assessed across more than 390 research-based UX parameters. The benchmark reports over 3,100 weighted performance scores and 1,900 best-practice examples, with overall experiences ranging from poor to mediocre. Key weaknesses include repeat ordering, dietary and customization support, category filters, navigation, fulfillment timing, and tipping details. ### Source excerpt (Note: Unfortunately, e-mail and RSS don't support advanced layouts and features. If the graphics in this article look strange, you may want to read the article in your web browser.) At Baymard, we've just released a new UX benchmark with 8 "Food Delivery & Takeout" UX case studies. This follows our large-scale user testing on Food Delivery & Takeout UX and adds to our existing ecommerce UX benchmark. In this article, we give you a snapshot of the overall UX performance. 8 Food Delivery & Takeout UX Case Studies and the Overall Performance Just Eat mediocre Food Delivery & Takeout 49 page designs: mobile, app KFC mediocre Food Delivery & Takeout 48 page designs: mobile, app Uber Eats mediocre Food Delivery & Takeout 54 page designs: mobile, app Domino's Pizza poor Food Delivery & Takeout 34 page designs: mobile, app DoorDash poor Food Delivery & Takeout 48 page designs: mobile, app McDonald's poor Food Delivery & Takeout 39 page designs: mobile, app Deliveroo poor Food Delivery & Takeout 53 page designs: mobile, app Burger King broken Food Delivery & Takeout 41 page designs: mobile, app YourSite.com? Want to know how your site performs? Get Premium access to review your own site or have it audited by Baymard researchers. These are the 8 in-depth Food Delivery & Takeout UX case studies. The 8 mobile sites and apps have been manually assessed across 390+ research-based UX parameters relevant to Food Delivery & Takeout, resulting in 3,100+ weighted UX performance scores and 1,900+ best practice examples from these mobile sites and apps. Each of the 3,100+ UX performance scores from the 8 case studies is summarized in the interactive scatterplot below -- showing you how they perform collectively and individually: {{ scatterplot-graph: size=big + habitat=public + base-sites=collection:online-food-delivery + view-structure-id=gemini-st_l9jw5tjp }} The overall UX performance of the Food Delivery & Takeout sites and apps ranges from "poor" to "mediocre". What is missing is a ## Ecommerce Quantitative UX: 3 High-Level Trends & Takeaways from 20+ Charts DevFeed: [Ecommerce Quantitative UX: 3 High-Level Trends & Takeaways from 20+ Charts]() Original publisher: [Read original article]() Author: Anja Feibel Meerwald Published: 2026-08-04T08:21:00Z Content type: article Language: en Sources: [Baymard Institute]() Topics: [User experience (UX)](), [User Experience](), [data]() Tags: [article](), [checkout](), [data](), [ecommerce](), [research](), [time](), [ux]() ### AI overview Baymard presents quantitative UX findings from a survey of 1,083 US online shoppers, covering more than 20 ecommerce insights. The article highlights declining online return frequency, retailer-specific email frequency as a leading cause of newsletter unsubscribes, and the rising priority of loyalty programs in online account expectations. ### Source excerpt (Note: Unfortunately, e-mail and RSS don't support advanced layouts and features. If the graphics in this article look strange, you may want to read the article in your web browser.) Key Stats & Takeaways 20+ new insights on general ecommerce shopper habits and preferences 1,083 US online shoppers surveyed in this quantitative UX study General ecommerce shopping habits remain consistent overall, but a few noteworthy shifts stand out this year, from declining return frequencies to changing newsletter preferences At Baymard, we've released updated Quantitative Insights into the habits and preferences of online shoppers across key ecommerce stages. These insights are survey-based data visualizations that complement and deepen our large-scale UX research findings. The 20+ insights cover the online shopping experience across a wide range of topics: product discovery, cross-sell preferences, sale-seeking behaviors, checkout friction, return behaviors, account feature expectations, and newsletter management. Ecommerce shoppers make decisions with deeply ingrained expectations regarding transparency, flexibility, and convenience, standards that continually evolve as the online shopping landscape evolves. While the vast majority of our foundational data remains highly stable year after year, tracking this data over time reveals a few subtle, critical shifts in reported consumer habits. Over the last 3 years, consumer habits show clear directional changes in how frequently shoppers make online returns for their past purchases. Further down the funnel, they frequently leverage accounts to manage post-purchase utility, carefully balancing their participation in brand incentive structures with their tolerance for direct retailer outreach. Each of these evolving dynamics plays out at a different stage of the user experience, highlighting exactly where optimization priorities should be re-evaluated. In this article, we'll highlight 3 high-level findings that reflect the most notab ## Internet Service Providers UX Benchmark: 1,700+ Performance Scores and 1,100+ Best Practice Examples DevFeed: [Internet Service Providers UX Benchmark: 1,700+ Performance Scores and 1,100+ Best Practice Examples]() Original publisher: [Read original article]() Author: Anders Nielsen Published: 2026-07-28T05:27:00Z Content type: article Language: en Sources: [Baymard Institute]() Topics: [Benchmark](), [User experience (UX)](), [User Experience](), [web applications]() Tags: [article](), [benchmark](), [case-studies](), [ecommerce](), [performance](), [research](), [user-testing](), [ux]() ### AI overview Baymard presents a UX benchmark covering seven Internet Service Provider websites. Based on large-scale user testing, the benchmark reports 1,700+ weighted UX performance scores and 1,100+ best-practice examples. Overall performance is described as mediocre, with recurring problems in plan comparison and application flows, including dense layouts, unclear pricing, weak guidance, and form friction. ### Source excerpt (Note: Unfortunately, e-mail and RSS don't support advanced layouts and features. If the graphics in this article look strange, you may want to read the article in your web browser.) At Baymard, we've just released a new UX benchmark with 7 "Internet Service Providers (ISP)" UX case studies. This follows from our large-scale user testing and adds to our existing ecommerce UX benchmark. In this article, we give you a snapshot of the overall UX performance. 7 Internet Service Providers UX Case Studies and the Overall Performance BT mediocre Internet Service Providers 26 page designs: desktop, mobile Telekom mediocre Internet Service Providers 35 page designs: desktop, mobile Frontier mediocre Internet Service Providers 25 page designs: desktop, mobile COX mediocre Internet Service Providers 24 page designs: desktop, mobile CenturyLink mediocre Internet Service Providers 25 page designs: desktop, mobile Viasat mediocre Internet Service Providers 32 page designs: desktop, mobile Spectrum mediocre Internet Service Providers 15 page designs: desktop, mobile YourSite.com? Want to know how your site performs? Get Premium access to review your own site or have it audited by Baymard researchers. These are the 7 in-depth ISP UX case studies. The 7 ISP sites have been manually assessed across 280+ research-based UX parameters relevant to Internet Service Providers, resulting in 1,700+ weighted UX performance scores and 1,100+ best practice examples from these desktop and mobile sites. Each of the 1,700+ UX performance scores from the 7 ISP case studies is summarized in the interactive scatterplot below -- showing you how they perform collectively and individually: {{ scatterplot-graph: size=big + habitat=public + base-sites=collection:internet-service-providers + view-structure-id=gemini-st_9en1b7zd }} The overall UX performance of the ISP sites is "mediocre," with 1 site just on the border of "poor". ISP sites typically offer a narrow set of services, but these services come wi ## Introducing the ChatGPT for small business program DevFeed: [Introducing the ChatGPT for small business program]() Original publisher: [Read original article]() Published: 2026-07-21T17:00:00Z Content type: article Language: en Sources: [OpenAI News]() Topics: [ChatGPT](), [Artificial Intelligence](), [OpenAI](), [OpenAI Academy](), [Prompt Engineering](), [Shopify](), [Slack]() Tags: [accounting](), [agents](), [ai](), [ai-adoption](), [business](), [chatgpt](), [content](), [customer-stories](), [ecommerce](), [events](), [guides](), [openai](), [openai-academy](), [partner](), [partners](), [product](), [resources](), [shopify](), [skills](), [small-business](), [work]() ### AI overview OpenAI launches the ChatGPT for small businesses program, offering training, AI academies, practical guides, workflows, and partner resources to help small businesses become more productive and scale. ### Source excerpt OpenAI launches the ChatGPT for Small Businesses program, helping entrepreneurs build AI skills, automate work, and grow with ChatGPT Work. ## How to improve website performance: Best practices for faster sites DevFeed: [How to improve website performance: Best practices for faster sites]() Original publisher: [Read original article]() Author: Webflow Team Published: 2026-07-10T00:00:00Z Content type: tutorial Language: en Sources: [Webflow Blog]() Topics: [Web](), [User experience (UX)](), [Optimization](), [Caching](), [Compression](), [Search engine optimization (SEO)](), [Google]() Tags: [best-practices](), [browser](), [caching](), [code](), [compression](), [conversion](), [core-web-vitals](), [development](), [ecommerce](), [how-to](), [optimization](), [performance](), [seo](), [ux](), [web]() ### AI overview This article explains why website performance matters for user experience, customer satisfaction, bounce rates, conversions, and search rankings. It introduces performance metrics and seven optimization methods, including code minification, browser caching, and compression, while also covering common mistakes. ### Source excerpt Learn why a fast-loading website is so crucial for UX, and pick up seven common strategies for improving website performance as you grow your site. ## Wix vs. Shopify: Which is better for building your online store? DevFeed: [Wix vs. Shopify: Which is better for building your online store?]() Original publisher: [Read original article]() Author: Webflow Team Published: 2026-07-05T00:00:00Z Content type: comparison Language: en Sources: [Webflow Blog]() Topics: [Shopify](), [Back end]() Tags: [business](), [development](), [ecommerce](), [how-to](), [platform](), [pricing](), [shopify]() ### AI overview A comparison of Wix and Shopify for building and managing an online store, covering ease of use, ecommerce workflows, features, and pricing considerations. ### Source excerpt Learn the differences between Wix and Shopify, where each excels and falls short, and how to choose the best ecommerce platform for your business. ## Apparel & Accessories Quantitative UX: 3 High-Level Takeaways from 40+ Charts DevFeed: [Apparel & Accessories Quantitative UX: 3 High-Level Takeaways from 40+ Charts]() Original publisher: [Read original article]() Author: Niel Gan Published: 2026-06-12T08:02:00Z Content type: article Language: en Sources: [Baymard Institute]() Topics: [User experience (UX)](), [data](), [benchmarking]() Tags: [article](), [benchmarking](), [customer](), [data](), [ecommerce](), [online-shopping](), [research](), [reviews](), [shopping](), [survey](), [ux]() ### AI overview This quantitative UX study examines apparel and accessories shoppers' habits and preferences using survey data from 1,922 US online shoppers. It presents more than 40 insights on topics including sizing and fit confidence, product-page evaluation, reviews, returns, loyalty programs, and delivery expectations. The article highlights uncertainty throughout the shopping journey, including mismatches between shoppers' self-reported sizes and industry definitions, infrequent shopping as a barrier to loyalty enrollment, and reviews serving as a proxy for fit evaluation. ### Source excerpt (Note: Unfortunately, e-mail and RSS don't support advanced layouts and features. If the graphics in this article look strange, you may want to read the article in your web browser.) Key Stats & Takeaways 40+ new insights on Apparel & Accessories shopper habits and preferences 1,922 US online shoppers surveyed in this quantitative UX study Apparel and accessories shoppers face uncertainty at every stage of their journey, from how their self-identification corresponds to retailer categories to how they evaluate fit on the product page We've released new Quantitative Insights into people who shop on "Apparel & Accessories" sites, adding to our growing body of data on the habits and preferences of online shoppers across key ecommerce categories. These insights are survey-based data visualizations that complement and deepen our large-scale UX research findings and benchmarking of the Apparel & Accessories industry. The 40+ insights cover the Apparel & Accessories online shopping experience across a wide range of topics: online trip drivers, size and fit confidence, product page evaluation, reviews usage, returns, loyalty programs, and delivery expectations. Apparel and accessories shoppers make decisions with incomplete information at every stage of their online journey. They can't feel a fabric, try out a fit, or know whether a size label will translate to their body. Beyond that, they may not know whether the items they buy will ultimately feel "worth it" to them, or whether they'll shop frequently enough to make a rewards program worth joining. Each of these uncertainties plays out at a different stage of the journey, and each has distinct implications for how Apparel & Accessories sites should be designed. In this article, we'll highlight 3 high-level findings that reflect how apparel and accessories shoppers navigate that uncertainty: Shoppers' self-reported size categories often diverge from industry definitions Infrequent shopping, not program design, is the top ## Whatnot's Product Culture and the Changing Role of Product Managers DevFeed: [Whatnot's Product Culture and the Changing Role of Product Managers]() Original publisher: [Read original article]() Author: Whatnot Engineering Published: 2026-05-14T16:01:00Z Content type: opinion Language: en Sources: [Whatnot Engineering]() Topics: [Job](), [Software]() Tags: [ai](), [ecommerce](), [industry](), [job](), [leadership](), [people](), [product-management](), [software](), [software-engineering]() ### AI overview Tom Verilli discusses Whatnot's deliberate product culture and argues that the product manager role has become diluted by organizational scale, hiring growth, and management incentives. He suggests that succeeding in an AI-driven industry depends on doing the right product work rather than relying on tools alone. ### Source excerpt Tom Verilli | Chief Product Officer In the last two years, 31,832 people applied to be a Product Manager at Whatnot. We hired one. You're twice as likely to hit a hole in one as you are to get a job by simply applying. That's not a process failure. I've been building products -- and product teams -- for over a decade, and one of the biggest factors in deciding to come to Whatnot ~3 years ago was the very deliberate product culture. No one knows what it means to be a PM in the world of AI, but everything I see says the industry is moving towards us and how we build here -- because no tool will make you useful if you aren't doing the right job. First: we have to acknowledge that the average PM is deeply average. The product function emerged in response to scale -- engineering teams got too big for CEOs or GMs to manage directly, so a business <> tech conduit was needed. Over time, we lazily generalized the role to "every time you hire an Engineering Manager, you hire a PM". But where an Eng Director managed 30-40 people through their EMs, a PM Director just managed five. Incentives govern the world, so those directors' jobs became "justify growing my eng partners headcount" so they could, in turn, grow theirs to become a VP. Slowly, the role of junior PMs shifted from "CEOs of the product" to "babysitters of buttons" and product-minded engineers to infantilized order takers. Then COVID hit, and the industry hired a mind-boggling 500,000 new software engineers in just four years, and ~80,000 new PMs were minted to match. That's 80,000 PMs buried within gargantuan teams at FAANG, far from any customer, 50 layers from the zoom where it happens, taught paint-by-number PM'ing at a product school, in an era of unearned engagement growth where seemingly anything worked. The likelihood of someone emerging from that with great product instincts, experience, and grit actually feels less likely than hitting a hole in one. Second: we made our best, worse. When your job is supervising ## We replaced Redis with MySQL for inventory reservations--and it scaled DevFeed: [We replaced Redis with MySQL for inventory reservations--and it scaled]() Original publisher: [Read original article]() Author: Emilie Noel Published: 2026-05-12T16:51:53Z Content type: article Language: en Sources: [Shopify Engineering](), [Shopify Engineering - Shopify Engineering]() Topics: [MySQL](), [Redis](), [Database](), [Shopify](), [Transactions]() Tags: [database](), [ecommerce](), [mysql](), [payment-processing](), [performance](), [redis](), [scale](), [shopify](), [transactions]() ### AI overview Shopify explains how it replaced Redis with MySQL for inventory reservations during checkout. Using one row per inventory unit, SKIP LOCKED, composite primary keys, and connection visibility, the rebuilt system met high-throughput and consistency requirements during peak Black Friday 2025 traffic. ### Source excerpt How we used SKIP LOCKED, composite primary keys, and connection visibility to hit our scale targets. ## Rill and ClickHouse: real-time operational BI for a metered world DevFeed: [Rill and ClickHouse: real-time operational BI for a metered world]() Original publisher: [Read original article]() Author: ClickHouse Published: 2026-04-01T17:42:05Z Content type: article Language: en Sources: [ClickHouse Blog]() Topics: [clickhouse](), [real-time](), [DLT](), [dashboards](), [data](), [Amazon Web Services](), [Cloud](), [stripe]() Tags: [analytics](), [aws](), [clickhouse](), [cloud](), [data](), [datasets](), [ecommerce](), [events](), [fintech](), [google](), [observability](), [real-time](), [scale](), [snap](), [streaming](), [stripe](), [systems]() ### AI overview Rill uses ClickHouse to power real-time operational BI for more than 100 billion daily events. Its declarative ingestion, high-performance aggregation, and metrics-first BI workflow brings cloud costs, payments, and product usage together for analysis against live data. ### Source excerpt Rill uses ClickHouse to power real-time operational BI for 100B+ daily events, enabling instant exploration and conversational analytics directly against live datasets through a declarative, BI-as-code workflow. ## Adding Payments to Astro Sites: Static Meets Dynamic DevFeed: [Adding Payments to Astro Sites: Static Meets Dynamic]() Original publisher: [Read original article]() Author: Ayush Agarwal Published: 2026-03-27T00:00:00Z Content type: tutorial Language: en Sources: [Dodo Payments Blog]() Topics: [Astro](), [Web Development]() Tags: [astro](), [checkout](), [developer-tools](), [digital-products](), [ecommerce](), [how-to](), [payment-processing](), [payments](), [webhooks]() ### AI overview This guide explains how to add payment processing to Astro websites while preserving their static-first performance model. It covers payment links, checkout, webhooks, and server-side integrations for selling digital products and supporting ecommerce use cases. ### Source excerpt How to add payment processing to Astro websites. Integrate checkout, handle webhooks, and sell products from static-first sites with Dodo Payments. ## How Whatnot's Taxonomy Keeps Pace with a Marketplace That Won't Sit Still DevFeed: [How Whatnot's Taxonomy Keeps Pace with a Marketplace That Won't Sit Still]() Original publisher: [Read original article]() Author: Whatnot Engineering Published: 2026-03-25T14:22:19Z Content type: article Language: en Sources: [Whatnot Engineering]() Topics: [recommendations](), [bug](), [real-time]() Tags: [2025](), [ai](), [bug](), [ecommerce](), [machine-learning](), [onboarding](), [platform](), [real-time](), [recommendation-system](), [recommendations](), [taxonomy]() ### AI overview Whatnot describes how it redesigned its marketplace taxonomy to change more rapidly across countries and discovery surfaces. The article explains why onboarding, browse, search, and recommendations need different taxonomy treatments, using supply-aware onboarding and the Labubu category as examples. ### Source excerpt Marcus Gee | Discovery The hottest trends don't happen over months, but start suddenly. At Whatnot, our best sellers update their strategies in real time to stay in step with the market. Connecting buyers and sellers in this fast-changing landscape is one of the most important problems Whatnot solves, but in 2025, it was a major challenge. In this post, we're going to walk through how we overhauled the taxonomy system to evolve more rapidly, so our team could help new communities grow. There is No Single Taxonomy Whatnot supports over 200 categories across seven countries, and that number increases weekly. Our taxonomy is a platform primitive that underpins nearly every discovery experience. It shapes onboarding (what categories new users see), browse (how they navigate), search (how results are ranked), and recommendations (what their feed looks like). A bug in taxonomy doesn't break one feature; it degrades the entire discovery surface. That makes every change high-stakes. Here's what we learned the hard way: maintaining a single taxonomy doesn't work. A single taxonomy can't optimally serve onboarding, browse, and search at the same time, because these surfaces have different goals. Let's look at two examples to understand why: When new users join Whatnot, they choose categories they're interested in. That choice shapes the first feed they see. If a user selects a niche category with limited supply, their initial experience may feel sparse or low quality. For this reason, onboarding taxonomies are country-specific and supply-aware. We fold categories into broader parents, reorder them, or exclude them based on local marketplace density. Categories play a critical role in connecting enthusiasts and sellers. When Labubu surged in 2025, it was subcategorized under Toys, and new users struggled to find relevant shows. When we elevated Labubu to the first page of onboarding (a similar treatment given to other big categories like Pokémon Cards), it reduced this frictio ## Shopify Merchant of Record: What Shopify Handles vs What You Still Own DevFeed: [Shopify Merchant of Record: What Shopify Handles vs What You Still Own]() Original publisher: [Read original article]() Author: Ayush Agarwal Published: 2026-03-25T00:00:00Z Content type: tutorial Language: en Sources: [Dodo Payments Blog]() Topics: [Shopify](), [Tooling]() Tags: [checkout](), [compliance](), [digital-products](), [ecommerce](), [merchant-of-record](), [payments](), [shopify](), [tax]() ### AI overview This guide explains that Shopify is generally not the merchant of record in standard setups. Shopify provides commerce, checkout, payment, and integration infrastructure, while merchants typically retain tax and legal seller responsibilities. The article also explains why these responsibilities are more complex for globally sold digital products and when a dedicated Merchant of Record provider may be useful. ### Source excerpt A detailed guide to Shopify Merchant of Record decisions for digital products, including Shopify's actual role, where liability stays with merchants, and how Dodo Payments complements Shopify. ## Digital River Alternatives: 7 Better Options for SaaS in 2026 DevFeed: [Digital River Alternatives: 7 Better Options for SaaS in 2026]() Original publisher: [Read original article]() Author: Ayush Agarwal Published: 2026-03-25T00:00:00Z Content type: comparison Language: en Sources: [Dodo Payments Blog]() Topics: [Software as a service](), [migration](), [Software](), [stripe]() Tags: [2026](), [alternatives](), [billing](), [compare](), [complexity](), [compliance](), [cost](), [cross-border](), [digital](), [ecommerce](), [financial](), [global](), [global-payments](), [guide](), [legal](), [merchant-of-record](), [migration](), [payments](), [pricing](), [providers](), [saas]() ### AI overview A comparison guide to seven alternatives to Digital River after it shut down its Merchant of Record business in January 2025. It covers operating replacements, pricing, Merchant of Record coverage, and migration considerations for SaaS and digital-product teams. ### Source excerpt Digital River shut down its Merchant of Record business in January 2025. Compare seven operating replacements with verified pricing, MoR coverage, and migration guidance for SaaS and digital product teams. ## Wayfair boosts catalog accuracy and support speed with OpenAI DevFeed: [Wayfair boosts catalog accuracy and support speed with OpenAI]() Original publisher: [Read original article]() Published: 2026-03-11T00:00:00Z Content type: article Language: en Sources: [OpenAI News]() Topics: [OpenAI](), [AI Models](), [AI Development](), [Data Quality](), [ChatGPT](), [Generative AI]() Tags: [agent](), [ai](), [ai-models](), [chatgpt](), [data](), [data-quality](), [ecommerce](), [openai](), [production]() ### AI overview Wayfair integrates OpenAI models into supplier support and product catalog workflows, automating ticket handling and improving the accuracy of product attributes across millions of items. A single tag-agnostic system replaces costly bespoke models and supports production-scale operations. ### Source excerpt Wayfair uses OpenAI models to improve ecommerce support and product catalog accuracy, automating ticket triage and enhancing millions of product attributes at scale. ## Best Payment Methods for SaaS in 2026 DevFeed: [Best Payment Methods for SaaS in 2026]() Original publisher: [Read original article]() Author: Joshua D'Costa Published: 2026-01-13T00:00:00Z Content type: article Language: en Sources: [Dodo Payments Blog]() Topics: [Software as a service](), [Mobile]() Tags: [2026](), [apple](), [bank](), [card](), [checkout](), [compliance](), [conversion](), [ecommerce](), [google](), [mobile](), [payment](), [payments](), [saas](), [subscriptions](), [tokenization]() ### AI overview This article reviews major payment methods for SaaS businesses in 2026, including cards, digital wallets, buy now, pay later, cryptocurrency, and cash on delivery. It explains how the methods work and outlines their advantages and drawbacks, including fees, settlement delays, PCI compliance, and chargeback risk. ### Source excerpt See the top payment methods SaaS customers prefer in 2026 with pros, cons, regional coverage, and selection tips to improve checkout conversion rates. ## Building with Laravel for Ecommerce. The Artisan of the Day Is Gulzar Ahmed. DevFeed: [Building with Laravel for Ecommerce. The Artisan of the Day Is Gulzar Ahmed.]() Original publisher: [Read original article]() Author: Ana Tavares Published: 2025-12-12T15:23:44Z Content type: article Language: en Sources: [Laravel Blog]() Topics: [Laravel](), [PHP](), [Microservices](), [Architecture & Design](), [Open Source](), [Artificial Intelligence]() Tags: [ai](), [architecture](), [ecommerce](), [laravel](), [leadership](), [microservices](), [open-source](), [php](), [pull-request]() ### AI overview A profile of Gulzar Ahmed, CTO of Hyperzod, who builds large-scale quick-commerce systems with Laravel. The article covers Hyperzod's Laravel-based microservices, AI-related products, technical leadership, mentoring, and contribution to the Laravel community. ### Source excerpt Gulzar Ahmed, CTO of Hyperzod, builds large-scale quick commerce systems using Laravel, and mentors devs while contributing to the community and open source. [Next page]()