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Shopify
7 posts about Shopify. Every summary links to the original.
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Helix: The internal tool powering our Shopify app's native migration (2026) - Shopify
Shopify’s internal tool Helix powers the native migration of its Shopify app, which has over 300 screens. The company previously rebuilt the Shop app in just 12 weeks using similar methods. Helix is a set of tools and skills that help LLMs migrate features and screens from the React Native app while following a highly opinionated architecture. Unlike most tools that gather information, create specs, and implement everything at once, Helix aims for consistent, high-quality, and maintainable results. The approach is now being applied to the larger Shopify App after its success with Shop.
Announcing Fin for Ecommerce: Fin’s next role as a Customer Agent
Fin for Ecommerce is a new Customer Agent role for Shopify merchants, combining shopping assistance with ecommerce support before and after purchase. It helps shoppers discover products through conversational questions, live browsing context, catalog retrieval, comparisons, complementary recommendations, cart updates, and checkout guidance, while handling returns, refunds, exchanges, order changes, tracking, and shipping questions in the same conversation. The system uses Fin Apex 1.0 with an ecommerce retrieval engine and connects to Shopify to sync products, variants, content, order data, inventory, and APIs. Merchants can add Messenger and set Fin live in minutes without manual training; Shopify API integrations also let Fin use Procedures for complex requests, with drafts based on account data and company policies for review. The announcement positions Fin as a single Agent spanning discovery, purchase, and post-purchase support, with named ecommerce brands already using it.
Fin Product Updates: February recap
February updates for Fin address constraints in complex automation, voice quality, Shopify deployment, and helpdesk operations. Procedures can be drafted from existing source material, edited in natural language with hooks for live data, business logic, and deterministic code, then tested step by step in simulations using conversation data and defined criteria. Voice changes add pronunciation rules, 11 new voices, and automatic background-noise reduction, while Shopify setup connects a store, installs Messenger without code, and deploys Fin in under two minutes. Helpdesk additions include 11 call metrics and automatic public-holiday office hours; the post says 19 improvements shipped in 2026, and concludes that all featured updates are live and available now.
Intercom is now a Shopify Plus Technology Partner
Intercom announces that it is now a certified Shopify Plus Partner on the Technology Track. The program recognizes technology providers whose product quality, service, performance, privacy, and support meet advanced requirements for Shopify Plus merchants. Intercom says its integration is vetted and optimized, and describes recent additions including Data Connector templates for Fin, multi-store support, inbox order actions, EU workspace support, and updated data mapping and custom fields. The announcement also lists planned expanded Fin Tasks, Model Context Protocol support, and smarter product search powered by Shopify data, positioning these capabilities as ways to resolve ecommerce support requests faster and personalize conversations at scale as merchants prepare for peak season and rising customer expectations.
From support to sales: Turn ecommerce conversations into customers with Fin
Online retailers often struggle to answer delivery, returns, discount, and product questions quickly, especially during peak shopping periods, when delays can frustrate shoppers and contribute to abandoned carts. Intercom’s Fin is presented as an LLM-powered AI agent that uses existing knowledge content and real-time data to resolve queries, personalize support, and assist with sales activities such as upselling, cart recovery, and targeted promotions. It can handle order tracking, refunds, exchanges, product availability, and support in more than 45 languages, while integrating with Shopify and Stripe for actions including order changes and refunds. Reported examples include GoodBuy Gear’s 50% resolution rate and engagement in over 20% of interactions, plus Nuuly’s 11% reduction in subscriber support contact rates after implementation. Fin is positioned as a way to scale 24/7 multichannel support and connect service interactions with conversion and loyalty goals.
Preparing Shopify for Black Friday and Cyber Monday
Shopify’s Production Engineering team prepares its platform and 600,000+ merchants for Black Friday and Cyber Monday traffic without interrupting service. Preparation combines controlled fault injection “game days,” synthetic load tests, and staged freezes: a feature freeze begins several weeks ahead, followed by a code freeze allowing only critical fixes during the event. The tests probe dependencies such as shipping providers and payment gateways, including latency, fallback behavior, and responses to datastore failures. After the 2018 weekend, Shopify reported nearly 11,000 orders per minute, around 100,000 requests per second for extended periods, and overall metrics about 1.8 times 2017 levels. The account concludes that fault injection, load testing, and disaster role-play improved readiness, while third-party downtime remains Shopify’s responsibility to merchants and buyers.
How Shopify Merchants can Measure Retention
Shopify addresses customer retention for merchants operating non-contractual businesses, where churn is not directly observable. Common rules that label customers inactive after N days create arbitrary binary states, so the post proposes probabilistic modeling with the BG/NBD (Beta Geometric / Negative Binomial Distribution) model. It represents each customer with a purchase rate and churn probability, estimates their population distributions, and uses age, recency, and repeat-purchase frequency as sufficient statistics. Shopify fits a modified implementation in lifetimes using Apache Spark DataFrames, subsampling up to 50k customers per shop for performance, and produces activity probabilities and expected future purchases for more than 500 million historical merchant customers. The model is interpretable and supports customer ranking and targeted campaigns, but it handles seasonality poorly and does not easily incorporate additional variables such as country or products purchased.
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