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Hi there, hope you're having a great Friday!
This is Colm and Simon from CommerceGurus, with a handpicked weekly roundup of eCommerce articles.
Most eCommerce teams assume their site search is “good enough” - until customers start leaving.
The moment they can’t find something, they jump straight to the search bar and type whatever feels natural to them.
The problem is, many search systems still expect exact matches. If your product is labeled “athletic footwear” but your customer searches for “running shoes,” you’ve just created friction.
If your naming, categories, and tags don’t match how real customers think, your products effectively become invisible.
The fix isn’t a one-time upgrade, but an ongoing process: look at what people are searching for, identify where they get zero results, and adjust your language to match theirs.
Our own Ajax Search module in CommerceKit includes a report on which searches get zero results - ideal for this research.
When search works well, it feels effortless and keeps shoppers moving toward purchase.
Read The Site-Search Paradox: Why The Big Box Always Wins
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In this guide, Julia Callicrate explains how AI is becoming a new “front door” for eCommerce, with tools like ChatGPT, Gemini, and AI search changing how people discover products.
We discussed this important topic also in our recent article: The Invisible Storefront: The Shift from SEO to AEO in eCommerce
Instead of browsing search results, shoppers are now asking questions in natural language - and AI systems recommend products directly. Visibility is no longer just about SEO rankings, but about whether your products can be understood and surfaced by AI.
The key point is that product data quality is now critical.
AI systems rely on structured, detailed information - things like clear specs, attributes, pricing, and use cases - to decide what to recommend. Stores that provide complete, factual, and well-structured product data will have a big advantage, while gaps in data can mean being skipped entirely.
Her advice is to start simple: audit your product data, rewrite descriptions to answer real customer questions, and test how your products appear in AI tools.
The encouraging part is that these improvements don’t just help with AI, they also make your store better for real shoppers, improving clarity, trust, and conversions at the same time.
Learn How to Prepare your Store for AI-driven Commerce
The Nielsen Norman Group has looked at how popups affect usability and why they’re often frustrating for users.
Many sites display them immediately when a page loads, blocking the content people actually came to see.
This creates an interruption that slows users down and forces them to dismiss the popup before continuing, which can damage the overall browsing experience.
That said, the article acknowledges why they remain so popular - popups can significantly increase conversions for things like email signups, discounts, and promotions, especially in eCommerce.
The key is balance. Instead of interrupting visitors right away, NNGroup recommends showing value first and triggering popups later in the session or after a specific action.
Done thoughtfully, popups can still drive conversions without hurting the user experience.
Read Popups: 10 Problematic Trends and Alternatives
TypeVibe is a lightweight AI tool that helps you quickly find font pairings and typography styles based on the kind of project you’re working on.
You simply describe what you’re building, and it suggests font combinations - then shows how they actually look across real design layouts like landing pages, posters, or dashboards.
Instead of guessing or spending hours testing fonts, it gives you a fast starting point and lets you explore different visual directions in context.
It’s a simple but useful tool for designers and developers who want to make better typography decisions without overthinking it.
Take a Look at Type Vibe
Una Kravets has shared a quick demo of the CSS contrast-color() function, which automatically returns either black or white text depending on which provides better contrast against a given background color.
For example, contrast-color(purple) would return white because it’s more readable against purple.
The idea is to make accessibility easier: instead of manually choosing text colors for every background, the browser can automatically pick the most legible option based on contrast.
Check out the contrast-color() Demo Example
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Have a great week and best of luck with your projects!
Simon and Colm from CommerceGurus
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