Shopify Store Creation

I found a way to triple eCommerce revenue without writing hundreds of articles. Instead, by focusing on these big needle-movers (which most brands skip)... We grew a client’s monthly traffic by 115%... and monthly revenue 198% in just 9 months. Here's how: (full eCommerce SEO crash course)👇 #1: Personalize and Streamline the Shopping Experience • Add product recommendations based on user behavior • Show “complete the look” bundles • Enable cart-saving and wishlists • Simplify checkout with guest options, pre-filled forms, one-click purchase, and collapsible stages #2: Leverage Seasonal Search Trends Ask ChatGPT: “Suggest seasonal keywords for [your niche].” Validate demand in Google Trends. Build content 2 months before interest spikes. This allows you to pre-position for surges in buyer intent. #3 Micro-Moments Strategy There are 4 key decision-making moments in the buyer’s journey. "I want to know" content (researching): • Blog posts answering product questions • FAQ pages about product care/maintenance • Explainer videos showing product features "I want to go" content (for physical stores): • About page with clear location info • Contact page with embedded map • Updated Google Business Profile with photos and reviews "I want to do" content (learning how to use): • How-to guides for using your products • Assembly instructions with clear visuals • Video tutorials showing product in action • Downloadable user manuals "I want to buy" content (ready for purchase): • Product descriptions that highlight benefits • Category pages that compare similar products • Customer reviews and testimonials • Clear pricing and availability info #4 Faceted Navigation Strategy Faceted nav lets users filter by size, color, price, etc. But done wrong, it’ll bloat your index with duplicate URLs. Here’s how to implement it properly: • Use buttons or <input>—not <a href> • Add canonical tags on filtered pages → point to main category page • For high-potential filtered URLs (e.g. “blue running shoes”), create internal links to them • Use AJAX so filters don’t generate new URLs • Remove noindex/nofollow/robots.txt blocks for URLs you want indexed WordPress? Use WP Grid Builder. WooCommerce? Follow the official SEO filtering guide. Shopify? Enable Storefront Filtering. #5 Schema Markup Strategy Schema helps Google understand your content and display rich results. When your listing takes up more real estate and draws the eye, users are more likely to click. Use these two schema types: • Product Schema: includes ratings, reviews, price, availability • BreadcrumbList Schema: helps Google understand your site structure Use ChatGPT to generate your schema fast, then validate it on validator(.)schema(.)org before uploading. Our client’s result after implementing this strategy? • Organic traffic: +115% (12.8K to 27.6K sessions) • Monthly revenue: +198% ($10.2K to $30.6K) • Keywords in top 10: +36% (2,005 to 2,737)

92% of people don’t buy the first time they see a product. Not because they don’t want it. But because they aren't confident to buy it (yet). They think: – Is this the right product for me? – What if I need to return it? – Can I trust this brand? Answers to which they struggle to find. In this post, I’m breaking down 8 content, image, and UX changes that help shoppers say “yes” faster (without lowering your price or offering a bigger discount). 1. Keep the product name, price above the product image. This allows you to add a "1-line description" prominently. Also makes the add to cart CTA "appear" closer since shoppers usually scroll till the image. 2. Add badges on your product image. It's certifications, press icons, bestseller. This reassures shoppers that this is a quality product. And gives them the confidence to keep scrolling down. 3. Show a sneak peek of the next product. This makes the image gallery more intuitive to use, overall increasing your engagement rates. 4. Show thumbnails of the other images. Especially applicable if they have model images, educational content. It makes the shopper know in an instance "why" they should see these images. 5. Add key service USPs just below your add to cart CTA. This addresses common questions people have. How fast I get did? Can I return it? Does it delivery to my location? 6. Upsell at the right place. People usually buy towels in packs. For face, hand, body. That's why it made sense for it to be before the accordions for this brand. See my other posts to find where to upsell for other industries. 7. Add a short description intro before the accordions. This gets people reading and interested in the product. Overall improving CTR on the accordions. 8. Add accordions. These are collapsed drop downs with key product information. Help them answer common questions like how to use, quality, materials, how it's made. Try these and let me know how it impacts your website. P.S. Want to know what % of users interact with your images? Find out from a tool like Clarity (which is free), or Crazyegg/Hotjar (paid alternatives). From the heat maps report. If you'd want to learn how to take out insights from user behavior. Check out my CRO guide. Comment 'Guide' and I'll send you the link to get it.

OpenAI dropped something big: retailers can now embed AI shopping agents into their Shopify stores - in just a few clicks. Through a new integration between the Storefront Managed Compute Platform (MCP) (Shopify’s tool for powering custom storefront features) and the OpenAI Responses API (controls how AI agents understand and respond to users), building a shopping assistant no longer requires authentication, custom code, or complex setup. By adding a store URL to the OpenAI Playground (an easy-to-use web interface for testing and deploying AI agents), a fully functional assistant can be deployed almost instantly. Once live, the AI assistant is capable of: - Searching the store’s live product catalog - Adding selected items to a shopper’s cart - Generating checkout links in real time The interaction is seamless. A shopper might type, “I’m looking for a lightweight men’s button-up shirt for a vacation,” and the agent responds with curated options. Upon selection, the item is added to cart - autonomously and without delay. The launch marks more than a product update - it’s a strategic step toward agentic commerce, where AI doesn't just inform but acts on behalf of the shopper. While OpenAI provides the intelligence and interface, Shopify is laying the groundwork for retailers to operationalize it at scale through tools like the Storefront Managed Compute Platform (MCP). And it’s not alone. - Perplexity offers one-click purchasing via Buy with Pro and is onboarding merchants through a free product data program. - Google is enhancing Search and Bard with shopping intelligence, making results more shoppable — though still not fully agentic. - Amazon is using generative AI in listings, reviews, and its Rufus assistant to improve discovery and streamline decisions. - Startups like Cocoon and Cartwheel are building white-label AI agents for brands, turning chat into personalized storefronts. We are clearly moving from search engines to shopping agents. Opinions: my own, Video source: Shopify Developers 𝐒𝐮𝐛𝐬𝐜𝐫𝐢𝐛𝐞 𝐭𝐨 𝐦𝐲 𝐧𝐞𝐰𝐬𝐥𝐞𝐭𝐭𝐞𝐫: https://lnkd.in/dkqhnxdg

The 3-second rule: That's how long you have to grab a customer's attention online. Here's how to ensure your B2C startup's website drives interest: Your website is your 24/7 salesperson. But for many B2C startups, it's more like a shy intern. They end up with:   🏪 A cluttered shop front that overwhelms visitors   🧭 Unclear pathways to important information   🤔 Missed opportunities to showcase credibility The solution: Reframe your homepage as an engaging, informative storefront. Think of it as a one-page showcase with clear pathways to products and information. Here's how to structure it: 1. ABOVE THE FOLD     ↳ Value prop headline (under 10 words)     Example: "Feel confident with your skincare routine"     ↳ 25-word max product description     Example: "Our AI-powered app analyses your skin and recommends personalised, ethically-sourced products delivered straight to your door."     ↳ Inspirational intro video (optional)     ↳ CTA to 'Why Us' page TIP: This section gets the most attention. Make it emotionally appealing and mobile-friendly! 2. JUST UNDER THE FOLD     ↳ Social proof (customer reviews, ratings, press coverage, influencer endorsements)     ↳ CTA to product showcases or customer stories WHY: Build trust quickly with real experiences and third-party validation. 3. FURTHER DOWN THE PAGE     ↳ 3 lead benefits (not features!)     ↳ Bring product to life - showcase popular items or categories     ↳ CTA to product page REMEMBER: Benefits solve customer problems. Features are just tools. 4. WRAP UP     ↳ Final CTA (e.g., 'Start Shopping' or 'Join Our Community') PRO TIP: Make this CTA stand out on all devices! This blueprint helps your homepage quickly answer:     ↳ What do you offer?     ↳ Who is it for?     ↳ Why should customers care? Key components to include:     🎯 Clear, emotionally resonant value proposition  🧭 Intuitive navigation to 'Why Us' and product pages     💡 Benefits led and visually appealing product showcases    🤝 Diverse customer testimonials, ratings, and press mentions   Follow this plan for an improved user experience and a boost in conversions. Remember, your 'Why Us' page is crucial for building credibility and emotional connections with consumers. What's your biggest challenge in designing a B2C homepage? Ask me anything in the comments 👇

A real-world dilemma many e-commerce brands face: Modernize or stick with what works. Sometimes when businesses scale, their websites feel the strain. Increased product categories, complex merchandising, and evolving customer expectations often leave leaders asking: Should we redesign the site? The challenge: A business experiencing significant growth approached us about their Shopify site. While functional, the site wasn’t evolving with the business. The founder said, “I’m just tired of how it looks.” The frustration was valid. But we dug deeper and found: → The site’s core functionality worked well. → Customers were converting. → Synthetic “site speed” metrics were misleading—real user performance was solid. The problem wasn’t broken UX/UI—it was stagnation and the natural weariness that comes with running the same site for years. The options: 1️⃣ Full Overhaul: Start fresh with a complete UX/UI rebuild. 2️⃣ Strategic Iteration: Focus on backend improvements, design tweaks, and A/B testing to boost performance without disrupting what works. Our advice? A clean slate might look shiny, but incremental changes often deliver better ROI with less risk. So this is what we did: → Conducted a technical audit to identify opportunities for scalability and efficiency. → Implemented Shopify metafields and product hierarchy updates for smoother operations. → Addressed the emotional disconnect by refreshing key visual elements without a full redesign. The result? A site that aligned with the business’s growth while keeping what worked—and the founder didn’t need to throw everything out to feel proud of their website again. The takeaway: Redesigns aren’t always the answer. Sometimes, your site doesn’t need to look new—it just needs to work better. Focus on functionality, scalability, and incremental improvements before opting for a full overhaul.

Most product listings fail before they go live. Here’s how Shopify fixed it—for millions of merchants—using one small AI model: Everyone wants their products to rank high in search. But messy listings kill visibility. Wrong tags, unclear descriptions, missing categories. Shoppers scroll right past. Shopify faced this at scale. Millions of merchants. Billions of product images. Over 10,000 potential categories. Manual tagging wasn’t cutting it. Closed AI models were too expensive to run daily at that volume. So they built their own solution. A fine-tuned, open-source LLaVA model powered by Llama 2 7B. It analyzes product images, suggests categories, creates metadata, and even flags violations—all in real time. It now processes tens of billions of tokens daily across 100 GPUs. Merchants get smarter listings. Shoppers get better search results. No expensive fees. No bloated infrastructure. The entire product catalog updates faster, more accurately, and with zero added effort. Want listings that actually work? Start by fixing your metadata. Or let the right AI do it for you.

The last few weeks have been intense. I’ve been deep-diving into how AI and LLMs can transform the way we interact with Shopify data—not just for automation, but for smarter decision-making. So I built something small MVP. A chatbot that pulls real-time product, customer, and order data from Shopify, pushes it to vector DBs like Chroma, Pinecone, Milvus, and makes it searchable with OpenAI embeddings. You ask: “Where is my order?” → It checks login and gives you a contextual reply. You say: “Show me a red t-shirt under $30” → It fetches product data semantically. It’s not just for customer support—imagine CXOs chatting with their business data to get instant answers like: “What’s the best-selling product in California last month?” I wrote a deep-dive blog on how I built it, with all the tech breakdowns: - Shopify API - OpenAI embeddings - Vector DB - LLM orchestration Would love to hear your thoughts on similar use cases or how you’re approaching AI in eCommerce. #Shopify #AI #LLM #OpenAI #eCommerce #CustomerSupport #TechForBusiness #GenerativeAI #CRO #CXO

Fantastic overview from Shopify explaining how they use vision-language models for product classification. Shopify's product classification system serves as the basis for search ranking and related-product recommendations, so identifying nuance among related products is important. Shopify states that its first system used logistic regression and TF-IDF (a bag-of-words technique that scores words for importance based on frequency across a corpus and a document). This approach lacked classification depth since it was unimodal: it only used a product's description (text) as an input. Shopify determined that its classification system needed to capture more granular product details while adhering to its internal taxonomy, which spans 10,000 product categories. Using a large multimodal model for product classification enables the learning of more intricate relationships across modalities (image + text simultaneously) while also providing zero-shot classification capabilities. To build this system, Shopify implemented FP8 quantization (floating point precision reduction) to reduce memory footprint during inference, on-demand batching with NVIDIA Dynamo to classify products as they surface (versus waiting for an entire batch to fill), and key-value caching. The pipeline itself runs a two-stage prediction: one model call to yield the product's category and another (dependent on the first) to yield its attributes. The pipeline has utilized different models over time; the blog post indicates that the system currently uses Qwen2VL 7B. The pipeline processes 30MM predictions daily and has achieved an 85% classification acceptance rate from merchants. Shopify also built a system to produce training data that sources inputs from multiple LLMs, along with a custom-built model for tie-breaking. Blog post linked below.

Shopify’s Fintech Stack Shopify’s fintech stack includes the following products : Shopify Pay — This is Shopify’s checkout button for online stores. It offers an accelerated checkout option for customers by allowing customers to save credit card information, along with other data. Shop Pay is remarkably similar to Amazon Pay and Apple Pay. Sellers can enable Shop Pay just like you would any other options for third-party providers on your Shopify website. Shop Pay Installments — More recently, Shopify integrated Pay with Affirm to offer Pay later option at check out, which will let merchants offer their customers more payment choice and flexibility at checkout, helping merchants boost sales through increased cart size and higher conversion. Shopify Balance — gives merchants access to critical financial products to start, run, and grow their business, including the Shopify Balance Account, Shopify Balance Card, and rewards such as cashback and discounts on everyday business spending like shipping and marketing. The key hook is that as soon as a customer has paid on the e-commerce store a merchant would have that cash available immediately. This will be instant and without fees, unlike most business bank accounts that take days and charge fees. Shopify Capital — Providing loans ranging from $200 to $1 million to merchants. Shopify has already distributed over $1 Billion in loans. Since Shopify has access to all the sales (and subsequently CashFlow) data, their risk underwriting can be more accurate than traditional banking Why is it valuable to Merchants? By integrating merchant focussed fintech products (Balance + Capital) into the Shopify platform, Shopify solves the most critical problem that small businesses run into — managing CashFlows. Typically, it takes 3–4 days to receive money into an external bank account, once a transaction is processed on Shopify (or on any online store). However, through Shopify Balance + Payments combination, merchants on Shopify can receive their funds the same day as the transaction happens. Secondly, through Capital, Shopify ensures that merchants can easily borrow funds they need for growth. Traditionally, merchants would either go to their bank to access a credit or to digtal lenders such as Kabbage to meet capital needs. Since Shopify has all the sales data of merchants, it can better predict the risk in providing loans to a merchant than traditional or digital lenders. Also, this underwriting is almost instantaneous since Shopify already has the required data. Thus making it easier for merchants to access capital and much safer for Shopify to lend. Source George Slawek / Hardik Tiwari #fintech #payments #shopify #ecommerce

Shopify made it a lot easier to monitor what’s really going on with your stock right inside your admin 👉 With the new Inventory Adjustment History reports in Analytics > Reports, merchants can now: ✔ Track every stock movement Every increase or decrease in quantity is logged across all SKUs and locations ✔ Get full transparency on changes Know exactly when, why, and who made a change. Yes, even that mystery inventory dip last Thursday ✔ See what’s on the way Incoming shipment data now shows expected arrivals by location ✔ Follow your internal transfers Whether it’s between stores or from your warehouse to retail, you’ll see pending transfer orders and timing ✔ Access deeper insights Historical inventory data now goes beyond the old 180-day limit, helping you spot long-term trends, not just short-term noise These reports are available if you're using the new Shopify Analytics You’ll find them in Analytics > Reports > Inventory 💡 Why this matters: If you’ve ever had to answer: > “Why does this SKU show negative stock?” > “When is the new stock arriving at this location?” > “Where did 20 units just disappear to?” …you now have the audit trail to answer confidently, no more digging through emails or Slack