Swym Wishlist runs on 6.6% of the 3,500,000+ Shopify stores across our full detection dataset. For how its share is moving right now, see app trends.
#10 most-used app in our datasetSwym Wishlist is a Shopify app used by 6.6% of the Shopify stores in our dataset, ranking #10 among all apps we track. The figure reflects the app detected on live storefronts, not App Store install counts.
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Swym Wishlist has slipped from 8.2% to 2.6% of the stores scanned each month over recent months. See all Shopify trends →
Swym Wishlist lets shoppers save products they are not ready to buy yet, then return to them later from any device. It adds a wishlist button to product and collection pages, keeps the saved list synced whether a customer is logged in or browsing as a guest, and can send reminder emails when a saved item drops in price or is running low. For stores with a longer consideration cycle, it captures intent that would otherwise leave with the visitor.
Beyond the save button, Swym ties wishlists into email and back-in-stock alerts, so a saved product becomes a reason to bring the shopper back. Merchants can place the wishlist in the header, on product cards, and on a dedicated page, and the app reports on what gets saved most. It fits fashion, jewelry, home, and other catalogs where people browse widely before committing, and it works alongside the review, loyalty, and email apps those stores already run.
Reach: Swym Wishlist sits just inside the ten most detected apps in our dataset. That puts wishlists in the same tier as reviews and email capture, not the long tail of niche tools. For a feature many merchants treat as optional, that level of adoption is a sign it earns its place on a real storefront.
Store profile: The stores running it carry a larger than average catalog. That fits the feature exactly. The more products a shopper has to weigh, the more they need a way to set some aside and come back to them. A wishlist does little for a five product store and a lot for a deep catalog where browsing outpaces buying.
Stack context: It shows up next to a typical stack of around ten apps, and the company it keeps is telling. Reviews, email, loyalty, and back-in-stock tools appear in the same stores, all of them built to pull a shopper back for a second visit. Swym fits that retention layer rather than the acquisition side, which is where its saved-item and price-drop reminders do their work.
Theme fit: Its top homes are mainstream themes led by Dawn, Prestige, and Impulse, with Horizon and Symmetry close behind. That spread matters, because it means the app is proven on both the default free theme and the paid themes serious stores buy. You are unlikely to hit a compatibility wall on a common template.
Bottom line: Adoption at this level says wishlists have moved from nice to have to expected, especially for considered-purchase catalogs. If your shoppers browse widely before they buy, Swym is a low-risk way to capture that intent and give your email flows a concrete reason to follow up.
| # | App | % of stores | Usage |
|---|---|---|---|
| 1 |
Klaviyo
Email Marketing |
55.2% | |
| 2 |
Judge.me Product Reviews App
Product reviews |
32.6% | |
| 3 |
Loox ‑ Product Reviews App
Product reviews |
25.8% | |
| 4 |
Yotpo
Product reviews |
20.5% | |
| 5 |
Vitals: Reviews, Bundles & 40+
Product reviews |
19.8% | |
| 6 |
Countdown Timer
Countdown timer |
17.3% | |
| 7 |
Recharge
Subscriptions |
17.2% | |
| 8 |
Gorgias
Support - Other |
14.7% | |
| 9 |
Triplewhale
Analytics |
11.1% | |
| 10 |
PageFly ✦ Landing Page Builder
Page builder |
11% |
| # | Theme | % of stores | Usage |
|---|---|---|---|
| 1 | Dawn |
14.2% | |
| 2 | Prestige |
7.3% | |
| 3 | Impulse |
6% | |
| 4 | Horizon |
3.9% | |
| 5 | Symmetry |
2.6% | |
| 6 | Broadcast |
2.6% | |
| 7 | Impact |
2.3% | |
| 8 | Be Yours |
1.6% | |
| 9 | Focal |
1.5% | |
| 10 | Warehouse |
1.5% |
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This figure comes from live detection: we scan Shopify storefronts and read the apps each one runs, then express it as a share of the 3,500,000+ stores in our dataset. It is a share of every store in our dataset, not just recently scanned stores, so it moves more slowly than the month-over-month figures on our trends page. We report what is currently detected, not historical installs or Theme Store / App Store counts.
Independent by design: rankings are determined solely by live detection data. Affiliate relationships never affect what ranks or how stores are counted. Read the full methodology →