If you've ever been handed a ticket that says "make the store faster" or "checkout is losing people, fix it," you already know the problem with eCommerce projects: the feature list is huge, it's rarely fully documented anywhere, and half of it is invisible until it breaks in production during a sale.
At https://softwin.io/ we build and audit eCommerce platforms across Shopify, WooCommerce, Magento/Adobe Commerce, and custom headless stacks. This post is the checklist we actually work from — framed for engineers and technical leads, not just PMs — covering the features, integrations, and architecture calls that separate a store that converts from one that just renders in a browser.
What "eCommerce features" means at the architecture level
An eCommerce site is a distributed system disguised as a website: catalog service, search index, cart/session state, payment gateway integration, inventory sync, and an analytics pipeline, all wired to a front end that has to render fast on a $150 Android phone on 4G. "Features" in this context are really system requirements — each one maps to a measurable business metric (conversion rate, AOV, cart abandonment, organic traffic), which means each one is also a legitimate line item for scoping and estimation.
The list below isn't exhaustive, but it's the baseline we check against on every engagement.
Why engineering leads should care about the business numbers
A few figures worth keeping in your back pocket when a feature gets deprioritized in sprint planning:
- A 1-second increase in load time has a measurable, well-documented negative effect on conversion rate — this makes performance work directly attributable to revenue, not just a Lighthouse score.
- The majority of storefront traffic in 2026 is mobile, so mobile performance budgets should be the primary target, not an afterthought optimized after desktop ships.
- Cart abandonment averages around 70% across the industry, and a large share is attributable to implementation choices: late shipping-cost disclosure, forced account creation, checkout step count.
Framing performance and UX work in these terms tends to get it prioritized a lot faster than "best practice" alone.
The checklist
[ ] Performance: sub-2s LCP, optimized/responsive images, CDN, caching layer
[ ] Mobile-first responsive design (not just "responsive")
[ ] Search: autocomplete, typo tolerance, faceted filtering, AI/NLP search
[ ] Checkout: guest checkout, saved payment methods, Apple/Google Pay, BNPL
[ ] PCI-DSS compliant payment processing (tokenized, never store raw card data)
[ ] Product pages: high-res media, video/360°, AR preview, verified reviews
[ ] SEO: clean URLs, schema.org structured data, per-product meta, sitemap
[ ] Personalization: recommendation engine, dynamic merchandising
[ ] Omnichannel: marketplace + social commerce integrations (API-driven)
[ ] Real-time inventory sync (webhooks/event-driven, not polling)
[ ] Analytics: GA4, funnel tracking, abandoned cart events
[ ] Accessibility: WCAG 2.2 AA baseline
[ ] Legal: GDPR/CCPA data handling, cookie consent, clear policies
[ ] Composable/headless-ready architecture for future scale
A quick rundown of the ones that most often get cut, and why they shouldn't be:
Performance and Core Web Vitals — LCP, CLS, and INP aren't just Lighthouse vanity metrics; they're SEO ranking inputs and conversion inputs simultaneously. Budget for image optimization pipelines, a CDN, and caching at the edge before you budget for anything visual.
Search — self-hosted search (basic SQL LIKE queries) breaks down fast past a few hundred SKUs. A dedicated search index (Algolia, Elasticsearch/OpenSearch, Typesense) with typo tolerance and faceting is close to mandatory once catalog size grows, and increasingly customers expect natural-language query support on top of it.
Structured data — schema.org Product, Offer, and AggregateRating markup, implemented per-product and validated (not just present), is what unlocks rich results in search. It's cheap to implement and routinely skipped.
Real-time inventory — polling-based sync creates exactly the "in stock" lie that kills trust. Event-driven sync (webhooks from your inventory/ERP system) is the correct pattern here, not a nightly batch job.
Composable/headless readiness — you don't need a full headless build on day one. But keeping the front end decoupled from catalog and checkout logic via APIs from the start avoids a painful rebuild later if you need a second storefront, a mobile app, or multi-region support.
https://softwin.io/'s practical take
Across our audits, the recurring finding isn't a missing feature — it's sequencing and prioritization. Teams ship visual polish and start paid acquisition before checkout friction, Core Web Vitals, and structured data are solid, so every acquisition dollar runs through a leaky funnel.
Our standard first pass on any engagement: Core Web Vitals audit, checkout step count and drop-off analysis, structured data coverage check, and a mobile usability pass — in that order, before any redesign work starts. On architecture: for catalogs under a few thousand SKUs, a well-configured platform build (Shopify/WooCommerce) usually beats a custom headless stack on time-to-market and total cost. Past that scale, or with real omnichannel/multi-region requirements, composable architecture starts paying for itself in flexibility and integration speed.
Common mistakes we still see
- Building headless/composable commerce for a catalog that doesn't need it yet — premature architecture optimization.
- Polling-based instead of event-driven inventory sync, causing stale stock data.
- Skipping structured data validation — markup present but broken, so it never renders as a rich result.
- Shipping analytics as a "phase 2" item, losing the first month of real user behavior data permanently.
- Treating accessibility as a post-launch fix instead of a build-time requirement.
- Storing or logging raw payment data instead of using a tokenized processor — a compliance and security risk that's entirely avoidable.
FAQ
Do I need every item on this checklist before launch?
No — treat performance, mobile experience, secure checkout, and core SEO as launch blockers. Personalization, AR previews, and deep omnichannel integration can ship post-launch once demand is validated.
Platform (Shopify/WooCommerce) vs. custom/headless — how do we decide?
Catalog size, integration complexity, and growth trajectory drive this. Platforms minimize time-to-market; custom/headless pays off once you need architectural flexibility platforms can't give you. A short technical audit usually resolves this faster than debate.
How long does a build like this take?
A platform-based store covering the core checklist: roughly 6–10 weeks. Custom or headless builds with deep integrations: typically 3–6 months, depending on scope.
What should get fixed first on an existing store?
Page speed and checkout friction — they affect every visitor on every device on every visit, making them the highest-leverage fixes available.
Is structured data really worth the engineering time?
Yes — it's a one-time implementation cost with a compounding SEO return, and it's one of the most commonly skipped items on this whole list.
Wrapping up
None of this is exotic engineering — it's disciplined prioritization of fundamentals (performance, checkout, search, structured data) before investing in the more visible, more exciting features. That ordering is what actually moves conversion and revenue numbers.
If you're scoping a new store or debugging why an existing one underperforms, SoftWin runs technical eCommerce audits and builds against exactly this checklist — feel free to reach out.
Curious how others here scope this: what's the one eCommerce feature you've seen most consistently under-budgeted in sprint planning? Drop it in the comments.
