Antla Virtual Try-On for Fashion: 20-Question FAQ (for Shopify & Headless)

1) What is Antla and how does AI Virtual Try-On work on a Shopify store?

Antla is a Shopify app that lets shoppers see themselves wearing your products in seconds. A customer uploads one photo, and Antla generates a high-fidelity try-on that preserves garment details and drape, creating a virtual fitting room right on the PDP. It’s plug-and-play (no code), works with your existing catalog, and is designed to increase conversion while reducing fit-related returns.

2) How is Antla Virtual Try On different from other “virtual fitting room” or AR try-on tools?

Antla focuses on fit + look accuracy (so results “look right”), speed (seconds per render), and commerce impact (Lookbooks, Try-On Upsells, share-for-discount). It’s built for Shopify merchants—so installation, analytics, and automation live where you work, instead of forcing a custom build.

3) What results can fashion retailers expect (conversion, AOV, returns)?

Merchants typically see more confident add-to-carts, higher conversion rates, larger baskets from outfit exploration, and meaningfully fewer fit-related returns. Exact lift varies by brand and category; most impact comes from removing “will this look good on me?” friction.

4) Do customers really upload only once? What are Lookbooks?

Yes. With Upload-Once Try-On, a shopper adds one photo and can then try on multiple items across your catalog. Antla turns that into a personal Lookbook—a scrolling gallery of “me in your products,” which boosts discovery and time-on-site.

5) What are Try-On Upsells and how do they increase AOV?

Antla can prompt shoppers to complete the look (e.g., jacket + top + pants). Because customers can see each item on themselves, add-ons feel helpful, not pushy—driving bundles and higher average order value.

6) Will Antla slow down my site or hurt Core Web Vitals?

No. The try-on widget lazy-loads and uses a CDN so it doesn’t block your initial render. You control where/when the “Try it on” call-to-action appears (PDP only, quick view, etc.) to protect performance.

7) Which fashion categories work best (dresses, tops, outerwear, modest wear, swim, etc.)?

Antla supports most apparel categories out of the box. Items with clear silhouettes (tops, dresses, outerwear, bottoms, sets) perform especially well. If you sell niche categories (e.g., modest wear, uniforms), results are solid as long as PDP images are clean, front-facing, and well lit.

8) How accurate are color, fabric, and fit?

Antla aims for true-to-fit visuals with stable color rendering. Fabrics with distinctive textures/patterns (denim, knits, prints) are handled carefully so they align and drape realistically. As with any AI system, best results come from high-quality product photos.

9) What photo guidelines should we give shoppers to get the best try-ons?

Recommend: bright, even lighting; face and torso visible; neutral background; minimal occlusions (no big scarves/props); camera at chest height. Selfies are fine—consistency matters more than perfection.

10) How does sharing/UGC work? Can we reward shoppers for sharing?

Yes. Antla’s share-for-discount lets customers share their try-on image to friends or social and receive an incentive (e.g., a code). This creates UGC that drives new visitors and adds a viral loop to your funnel.

11) What analytics does Antla provide?

You’ll see try-on starts/completions, products tried most, share events, add-to-cart lift, and downstream sales where attributable. Use this to prioritize hero items, optimize creative, and forecast demand.

12) Does Antla integrate with Shopify Flow and lifecycle marketing?

Yep. Trigger Flows and messages like “Still thinking about this look?” Include the customer’s try-on in abandoned browse/cart nudges or “new arrivals” alerts. Antla is designed to plug into your email/SMS/WhatsApp stack and on-site journeys.

13) Is Antla mobile-friendly? What about accessibility?

Antla is mobile-first and responsive. The CTA is keyboard-navigable, and copy/controls can be customized for clarity. The goal is a one-tap path to try-on on phones, where most fashion browsing happens.

14) Will Antla change my theme or require dev work?

No code required. Most stores add the “Try it on” button via the app and theme editor. Developers can further customize placement, styling, and conditions (e.g., show only on eligible variants).

15) How does Antla handle shopper privacy and compliance?

Antla is built with privacy by design. Merchants can configure photo retention, and customers can request deletion. Antla supports GDPR/CCPA-style rights and uses secure storage and transport. (Tip: add a short “Virtual Try-On Privacy” section to your site policy.)

16) What image assets do we need? Do we need new photoshoots?

Use your existing PDP images (front/angled, high-res, clean background). No special shoots are required. Better input images → better output quality. Keep color-true photography and avoid over-aggressive filters.

17) Can Antla work on headless storefronts (Hydrogen, Next.js) or custom stacks?

Yes. While Antla is a Shopify app, it can be embedded or triggered in headless builds with the right hooks. Your devs can render CTAs/widgets anywhere in your UX and pipe events to your CDP/analytics.

18) How do we A/B test Antla and measure ROI?

Simple approach: ship Antla to 50% of product traffic and compare conversion, AOV, return rate, and share-driven sessions over 2–4 weeks. Also track time-on-PDP and SKU discovery to capture the “browse lift” virtual try-on creates.

19) Pricing—how is Antla billed, and how do we forecast ROI?

Pricing is plan-based. Most brands justify Antla on the back of conversion lift, AOV, and return reduction—even modest gains typically cover subscription cost. For public pages, say “See pricing” and show a simple ROI calc (e.g., +X% conv × monthly sessions × AOV).

20) How do we get started (and how fast can we go live)?

Install from the Shopify App Store, enable the widget on PDPs, test on a few top SKUs, then roll out to the full catalog. Most merchants launch same day; larger stores often run a short A/B test first, then scale.