SNAG
- von Native User
- Free plan available
- von Native User
- Free plan available
Track what customers want to buy, capture emails, and turn product interest into sales data that guides your inventory decisions.
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Über SNAG
Snag helps you track what customers want to buy before they leave your store. Shoppers can save their favorite products to a wishlist with one click—no login required. Every saved item syncs to Shopify with product tags and customer emails, giving you real data on product interest and buying intent.
See which items get the most likes each day and spot trending products in one dashboard. Perfect for boutiques needing inventory clarity or growing brands wanting behavioral insights. The slide-out drawer keeps favorites accessible without page reloads.
Customize colors, text, and labels to match your brand directly from the theme editor. Add heart icons to collection and product pages in seconds. Lightweight and optimized at under 10KB, Snag loads fast and won't slow down your store. Stop guessing what to stock—let customer favorites guide your decisions and drive more sales.
Veröffentlicht: September 15, 2026
Hauptmerkmale
- Hearts on every collection and product page. Toggle them on or off in seconds.
- A slide-out drawer for saved favorites. No page loads, no logins, always there.
- Spot trends, track daily likes per product and see what's rising all in one view
- Match your brand - customize colors, text and labels from the theme editor.
- Under 10KB, async-loaded and fully optimized. Built to stay out of the way
Kategorie:
Preise von SNAG
FREE
Free
- Full analytics with 75 likes per month
- Hearts inherit your theme's look
- Toggle heart visibility placements
- Liked-items drawer w/item image & price
- Works without customer accounts
PRO
$11.99 / month
- Everything in Free, plus Unlimited likes
- Full customization drawer, email, button
- Shopper table w/wishlist value
- Shopper table w/email tracking & sync
- Sync emails 2 shop client w/product tags
- Recent activity feed in real time
- Export shopper data as CSV