Firework

Proud to power Vogue's Met Gala fashion moments. Fashion lives in motion. Video is the only format that captures it the way it was meant to be seen. Firework makes that possible. #VideoCommerce #FashionRetail #MetGala Condé Nast

Beauty shoppers arrive with questions. Most sites can't answer them. They come ready to buy with questions about skin type, undertone, and routine. Generic product descriptions don't close that gap. Neither does a FAQ page. Firework gives beauty brands the tools to show up in that moment, with AI-powered tools that meet shoppers where they're making the decision. What would it take for your site to close the gap? #VideoCommerce #BeautyRetail #Firework

Your website runs 24/7. But shoppers continue to browse and leave. AI Digital Showroom changes that. Always-on video demos show your products in action. An AI host scales that experience across every page. And live product guidance answers questions in real time, moving shoppers toward a confident decision. Every shopper. Every product page. Every visit. Where do you think most shoppers lose confidence before checkout? #AICommerce #VideoCommerce #Firework

Shoppers don't read their way to a purchase. They watch their way there. Video answers what product descriptions never could: scale, texture, fit, real-world context. Firework's Shoppable Video makes every frame buyable. Pull from content you already have, let AI fill the gaps, and turn every video touchpoint on your site into a conversion moment. How would shoppable video change the way your customers move from discovery to purchase? #VideoCommerce #Ecommerce #Firework

14x. That is how much AI agent order volume grew on Shopify in the 12 months through January 2026. Most brand catalogs are not built to compete in it. Shopify President, Harley Finkelstein made one observation at the Upfront Summit that explains why: "Agentic is fundamentally merit-based. If you go to a search engine and type sneakers, you're going to see Footlocker. But an agentic shopper that knows your preferences will surface what you actually want." Merit-based means the product that best matches the query wins. Not the brand with the biggest ad budget. Not the retailer with the most shelf space. The product with the most complete, accurate, contextually structured data. That is a different competitive landscape than the one most brands built for. The data structure that wins in paid search that includes keyword-optimized titles, bullet-point features, conversion-tested copy, is not the data structure that wins in AI-mediated discovery. An agent evaluating "fragrance-free moisturizer that layers under SPF without pilling on combination skin" needs functional attributes, use-case framing, and ingredient specificity. A product title and five bullet points give it nothing. David's Bridal understood this and moved on it. Their recent announcement confirmed a comprehensive catalog audit targeting silhouette, neckline, fabric, sleeve length, train length, and size range, the specific attributes that directly influence ranking and visibility across AI shopping experiences. A bridal retailer restructuring its entire product data operation is the clearest real-world signal of what merit-based competition actually requires. But structured data solves the discovery half. The conversion half is a separate problem, and it is where most brands are leaving money on the table. The shopper an AI agent sends to a brand's owned site is the highest-intent traffic in commerce right now. They have already been through a consultation. They arrive with a specific question, a use case, and context the PDP was never built to receive. An owned AI shopping agent does three things a static PDP cannot. It answers the specific question the shopper arrived with, trained on product-level data rather than generic copy. It connects inventory, variants, and use-case context in real time, reducing the uncertainty that kills conversions. And it captures the relationship, the preference data, the purchase history, the context, on a surface the brand controls rather than handing it to the platform that sent the shopper. The brands that build the owned AI experience compound it through conversion. The first move gets the shopper to the site. The second move closes them and keeps them. What is the biggest gap in your product data right now, and is your owned site built to convert the shopper that AI sends? #AgenticCommerce #Ecommerce #Firework

The ecommerce website's job description changed. Most sites have not been updated to match it. In the old model, the site's job was to attract traffic and convert it. SEO drove visitors. Homepage and category pages organized them. PDPs closed the sale. The site was the entire funnel. In the new model, AI platforms handle discovery. The site's job is to close the shopper who arrives already knowing what they want, and to capture the relationship that makes repeat purchase possible. That requires four things most brand sites do not currently have: 1. AI-readable product data. An AI agent evaluating your product does not read marketing copy. It parses structured attributes, semantic context, and real-time inventory. Every gap in your product data is a recommendation you do not get. 2. On-site AI that can answer the 23-word question. The average ChatGPT query is 23 words. The average Google search is five. The shopper arriving from an AI interface has a specific, contextual question. A PDP with bullet points and a spec table cannot answer it. An on-site AI trained on product-level data can. The conversion gap between AI-assisted and unassisted sessions is 12.3% versus 3.1%. 3. Video at the SKU level. The site must maintain the customer relationship even as discovery happens elsewhere. Video is the highest-trust content format for product-level decisions. Products with video convert 86% higher. Return rates drop 40% because shoppers made accurate decisions. This is where video commerce becomes structural rather than promotional, but not a campaign format, rather at the content layer that closes the pre-qualified shopper that AI discovery sends. The operational challenge is coverage at scale: most brands have video for hero SKUs and nothing for the rest of the catalog, which means the conversion advantage is limited to a fraction of the assortment. 4. Post-purchase infrastructure that compounds. The point is not driving traffic. It is building the technology and the data to capture and compound that customer relationship. Every transaction that completes on your site preserves that relationship. Every transaction that completes inside an AI platform does not. The website's job description changed. The brands that rewrite it now will own the conversion layer of agentic commerce. The ones that wait are building discovery infrastructure that routes shoppers to someone else's checkout. What is the first thing you would change about your PDP if you knew the shopper arriving had already been pre-qualified by an AI? #AgenticCommerce #Ecommerce #Firework

AI agents can't read your PDP. That's the conversion gap nobody is talking about. In March, OpenAI shut down ChatGPT Instant Checkout. Six months in, only 30 merchants were live. The reason wasn't checkout, it was data. Inventory, pricing, and attribute data scraped from the open web was too unreliable for an agent to transact against. That's not a checkout problem. That's a PDP problem. What actually shifted in the last 90 days: Google's UCP (Universal Commerce Protocol), co-developed with Walmart, Target, Shopify, and others added an AI agent-specific shopping cart and identity linking for loyalty last month. Salesforce announced its ChatGPT integration pilot on April 13, enrolling dozens of retailers to syndicate product catalogs directly into conversational search. Amazon won a preliminary injunction against Perplexity in March, blocking its Comet agent from its marketplace while building Rufus and Buy For Me internally. Morgan Stanley projects nearly half of online shoppers will use AI agents by 2030, accounting for roughly 25% of online spend. McKinsey pegs the channel at $3 to $5T globally by the same horizon. Why this breaks the traditional PDP: An AI agent doesn't scroll your image carousel. It doesn't read your bullet list. It parses structured product data, semantic attributes, verified reviews, and conversational Q&A, and makes a recommendation in milliseconds. If your content layer isn't built for that, you're invisible in the consideration set regardless of how much you spent driving the shopper to the page. The emerging standard, what's being called the Triple-A framework, is: Accessible → machine-readable structured data with complete, typed attributes. Authentic → verified UGC, real reviews, attributable Q&A that agents can trust. Abundant → fresh, syndicated, and updated across the retailer network. Miss any of the three and the agent skips you. The reframe: The old question was "how do we get shoppers to our product page?" The new question is "when an AI agent is answering for the shopper, what does our product content actually tell it?" Discovery is being owned by agents. Conversion is being owned by product data quality. The middle of the funnel, the part nobody has been investing in, is where the category is now being decided. If your product content can't be parsed, interpreted, and trusted by an agent in under five seconds, you're not losing a conversion. You're losing a shopper who will never see your SKU again. Is your PDP ready for the agent? #AgenticCommerce #Ecommerce #Firework

The PDP is the new storefront – this is where buying intent peaks. It’s where shoppers decide. Yet many product pages are still static, built to inform, not to guide. So why aren’t you treating it like your homepage? AI is changing that. Retailers are using it to surface the right content, adapt in real time, and turn PDPs into dynamic conversion engines. The shift is already here. If you’re thinking about how your PDP should evolve in 2026 and beyond, this perspective is worth a read. #EcommerceStrategy #PDPOptimization #RetailInnovation #VideoCommerce #Firework

Fashion ecommerce is uniquely complex. Fit, fabric, styling, and personal taste all influence whether a shopper feels confident enough to buy. Historically, brands tried to solve this by adding more photos, more copy, and more reviews, often creating more noise instead of more clarity. Two capabilities are reshaping how decisions get made on fashion PDPs: AI shopping assistants and video content. They serve different roles, but when applied intentionally, they work together to reduce uncertainty at the moments shoppers hesitate most. Swipe through to see how AI and video support key moments across the fashion shopping journey, from answering fit and styling questions to helping shoppers evaluate options and move forward with confidence. We take a deeper look at these use cases and how fashion brands are applying them today in our latest blog: https://lnkd.in/ejWXgvkC #VideoCommerce #EcommerceInnovation #AIinEcommerce #RetailStrategy #Firework

Brands and retailers already rely on influencers for social proof, now it’s time to rethink how to scale with AI – finding the right content, making it feel personalized and relevant, and scaling it without manual effort. Firework makes it possible to operationalize influencer trust at scale through AI Content Curation. Instead of manually sourcing and sorting through creator posts, our AI surfaces brand-relevant social content and intelligently connects it to your product catalog, using social tags, hashtags, brand mentions, and contextual signals to match the right video to the right context. What already exists becomes immediately shoppable, directly on your site. This approach transforms creator content from a top-of-funnel awareness play into a measurable ecommerce asset. Product storytelling becomes more credible. Shoppers move forward with greater confidence. And teams scale high-performing video without the production lift typically required. If you’re rethinking how creator content fits into your ecommerce strategy, let’s continue the conversation: https://lnkd.in/esAfiNwy #CreatorCommerce #VideoCommerce #EcommerceInnovation #RetailTrends #Firework