Apple Visual Intelligence Is Live on iPhone: On-screen Shopping Routes to Google and eBay

What changed on September 15, 2025\n\nApple’s Visual Intelligence is no longer just a camera trick. With the September 15 rollout, iPhone users can press the screenshot buttons, highlight anything on their screen, and jump straight into product searches across Google and supported marketplaces like eBay. Apple says the feature now searches what is on screen and routes into Google and integrated shopping apps, including eBay, Poshmark, and Etsy. See the specifics in Apple’s September 15 update.\n\nWhy it matters: this change moves users from inspiration to product pages in a few taps, without copying links or switching apps. Discovery now happens where shoppers already spend time, not in a separate browser tab.\n\n## Why on-screen visual search is a different funnel\n\nTraditional mobile shopping paths start in a search box, then fan out to retailers or marketplaces. Visual Intelligence flips the path. The user is already mid scroll, taps the screenshot shortcut, traces part of an image, and lands on search results or a product page. There is no query typing and fewer back-and-forth steps. It effectively compresses the upper funnel into the mid funnel, where conversion rates are higher.\n\nTwo more shifts matter for growth:\n\n- Cross-app handoff is native. If a shopper has eBay installed, deep links can open the listing view directly. If not, the system routes to the web.\n- Context carries over. Visual Intelligence can parse titles, sizes, and color cues from the on-screen image, then seed the downstream search with those attributes. That makes high quality imagery and descriptive data your new ad creative and your new query expansion, rolled into one.\n\nFor additional discovery shifts, see how teams can win conversational image search and how answer-led browsing changes KPIs in the AEO playbook and KPI.\n\n## How Visual Intelligence works on iPhone\n\nThe user experience is simple. Press the screenshot buttons, choose Visual Intelligence, then either highlight an object or tap Search. Users can also ask a question about what is on the screen, or add a detected date to Calendar. For step-by-step instructions and device requirements, follow Apple’s support guide.\n\nFor growth leaders, this means your merch photos and metadata are now first-class inputs to Apple’s on-screen understanding and to the search destination it invokes. Treat every image, variant, and attribute as a ranking signal.\n\n## The growth implications for retailers and marketplaces\n\n- Image quality becomes a performance lever. Clean backgrounds, full object in frame, consistent angle, and true-to-color matter more because they drive better matches in visual search. Busy staging may look brand rich but will hurt extraction of shape, texture, and edges.\n- Structured data becomes a matching map. SKUs with complete attributes such as brand, model, material, color hex, size scale, and GTIN tend to map more accurately to marketplace catalogs and price graphs. That reduces detours to generic results and increases the odds of landing on a specific product detail page.\n- Marketplaces gain share mid journey. eBay listings with strong Item Specifics and multiple angles will surface more often from on-screen prompts. Direct-to-consumer brands can still win by making universal links resolve directly to in-app PDPs with preselected variants.\n- Creative and SEO work from the same inputs. The photo set and schema that power PDP conversion also power on-screen routing. Break down silos so the team that shoots hero images coordinates with the team that maintains Product and Offer schema.\n\nFor checkout acceleration beyond marketplace clicks, consider an Etsy instant checkout pilot.\n\n## The two-week experiment that proves impact\n\nYou do not need a long roadmap to benefit. Ship a focused, two-week sprint and measure lifts in on-screen discovery traffic and add-to-cart.\n\n### Week 1: Preparation and asset upgrades\n\n- Pick a product cohort. Select 50 to 200 SKUs that already sell steadily so you can detect signal. Focus on single-color apparel, shoes, small electronics, decor, and collectibles, which match well in visual search.\n- Photograph for shape and texture. Shoot three standard angles per SKU, plus one context shot on neutral background. Use even lighting, non-reflective surfaces, and keep the object at least 90 percent of frame height for the primary image. Avoid overlapping props.\n- Tighten image hygiene. No text overlays, badges, or watermarks in the primary image. Crop to center the object, align horizon lines, and save at high resolution with lossless compression.\n- Enrich attributes. For each SKU, confirm brand, model, color hex, material, size, and GTIN. For apparel, add silhouette, neckline, sleeve length, and fit. For electronics, add model year, chipset, storage, and compatible accessories.\n- Update structured data. On web PDPs, ensure Product, Offer, and AggregateRating schema are valid. Include gtin13 or gtin14, brand, color, material, size, sku, availability, price, priceCurrency, and the canonical PDP url. For variants, use separate offers or distinct variant URLs.\n- Prime marketplace listings. If you sell on eBay, update Item Specifics, primary image, and secondary angles on the same SKU cohort. Use consistent titles with model plus key attribute plus condition.\n\n### Week 2: Launch and measure\n\n- Publish updated images and schema. Roll out to the cohort only.\n- Enable deep links. Confirm that universal links resolve into the app’s PDP when installed, and to the canonical web PDP otherwise. If you sell through eBay, verify that your listing URLs open in the iOS app when available.\n- Tag entry points. In your app’s routing layer, add an origin parameter, such as origin=vi_onscreen, when your App Intent or universal link handler identifies a Visual Intelligence invocation. If the system does not expose a source label, record an inferred origin when the session starts within three seconds of a Visual Intelligence deep link.\n- Monitor KPI deltas daily. Compare the treated SKUs against a matched control group on impressions from on-screen discovery, PDP clickthrough, add-to-cart rate, and the new discovery-to-cart KPI defined below.\n\n## The new KPI: Onscreen Discovery to Cart\n\nDefine a metric that captures the new journey.\n\n- Metric name: Onscreen Discovery to Cart (ODC)\n- Definition: Percentage of sessions that originate from Visual Intelligence and add at least one item to cart within the same session.\n- Numerator: Count of sessions with origin=vi_onscreen that include an add_to_cart event for any SKU.\n- Denominator: Count of sessions with origin=vi_onscreen.\n- Target: Start with a baseline over the first 7 days. Aim to exceed organic mobile session add-to-cart by 20 percent on the treated SKU cohort.\n\nImplementation notes\n\n- If you support App Intents for Visual Intelligence, instrument the intent handler to set a session property like source=vi_onscreen. If traffic arrives via a universal link, append a query parameter from your server that your app reads on first launch.\n- In web analytics, create a channel grouping for vi_onscreen, and build a segment where the landing page path contains your designated parameter.\n- In the marketplace context, such as eBay, use listing-level performance logs to infer ODC by matching timestamps of Visual Intelligence clicks with add-to-cart events, then normalize by estimated impressions.\n\n## Attribution and measurement, the practical playbook\n\n- App deep linking. Verify universal link association files and route PDP paths without interstitials. Log the first screen view after the link and set a session-scoped property for origin.\n- Server event plumbing. Forward app events, including view_item, add_to_cart, begin_checkout, and purchase, to your customer data platform. Attach origin, sku, variant, and marketplace fields.\n- Web fallbacks. When the app is not installed, preserve the origin parameter on the web redirect and set a first-party cookie for attribution.\n- Cohort analysis. Compare treated versus control SKUs, not just global performance. Calculate ODC, PDP view rate, and PDP-to-add-to-cart rate. Use synthetic control if volumes are small.\n- Creative QA. If ODC underperforms, review false negative cases where the image failed to match. Look for busy backgrounds, partially occluded items, or low-resolution crops.\n\n## Creative and data checklist for visual search readiness\n\n- Primary image on neutral background, high resolution, centered subject\n- Secondary angles showing profile, back, and close-up of texture or ports\n- No text overlays or logos in images unless required by marketplace policy\n- Consistent naming in titles, model plus key attribute plus color\n- Product schema with gtin, brand, color hex, material, size or dimensions\n- Offer schema with price, currency, availability, and url\n- Variant handling, either separate offers or variant-specific URLs\n- eBay Item Specifics filled completely, including brand, model, style, material\n- Universal links tested for PDPs and carts, no pop-ups blocking deep links\n- App and web analytics set to capture origin=vi_onscreen\n\n## Marketplace tactics, from eBay sellers to DTC brands\n\n- For eBay sellers, prioritize image clarity and Item Specifics. Listings with multiple clean angles and complete specifics tend to rank better in visual matches. Keep titles readable, for example, Brand Model Size Color Material.\n- For DTC brands, build a clean deep link path to PDPs and a fast add-to-cart flow. If your collections have visually similar items, add a Similar Items module that keeps the shopper on site if the exact match is out of stock.\n- For product teams, expose a lightweight intent endpoint if you plan to integrate with Visual Intelligence via App Intents. Return a compact payload that maps image features to SKUs and yields a stable deep link.\n\n## How this affects ad budgets and SEO\n\nVisual search shifts some discovery away from typed keywords and paid listings into native routing driven by imagery and structured data. That means the ROI on improving photos and schema can rival paid search optimizations. Over the next quarter, reallocate a small share of non-brand paid search to creative operations and schema validation, then compare marginal returns by channel.\n\n## Where Upcite.ai fits\n\nTeams use Upcite.ai to pressure test how their product images and schema perform across visual search destinations. You can run head-to-head queries with your own photography, audit schema coverage at the SKU level, and surface the handful of attributes that most improve match quality. Treat it like a search quality lab that tightens the loop between creative, data, and conversion.\n\n## Frequently asked implementation questions\n\n- Do we need an app to benefit? No. Visual Intelligence can route to web PDPs. An app improves conversion with faster PDP loads and saved payment methods.\n- Can we pass campaign parameters? On web, yes, via query strings on your PDP URLs. In app, tag sessions inside the deep link or intent handler.\n- Does Visual Intelligence replace Google Lens on iPhone? It coexists. iPhone users can also use Google’s tools, but Apple’s native flow is faster for what is on screen and now routes into integrated shopping apps.\n- Will this help categories beyond apparel and decor? Yes, especially where shape and texture matter, such as sneakers, handbags, small appliances, and collectibles. Complex technical products also benefit if your titles and attributes are precise.\n\n## Conclusion and next steps\n\nOn September 15, 2025, Apple made the iPhone screen a shopping channel, not just a canvas. Visual Intelligence compresses the discovery journey and, crucially, hands it off to Google and marketplaces like eBay where buyers already convert. You do not need a long integration to benefit. Run the two-week test above, raise your image quality bar, and enrich structured data for a defined SKU cohort. Ship deep link instrumentation and a clean ODC KPI so you can see impact quickly. After two weeks, double down on the winning photo patterns and attribute sets, then expand the cohort.\n\nThe teams that treat images and schema as performance assets will capture this new stream of mid-funnel demand. Start now, measure precisely, and scale what works.