> For the complete documentation index, see [llms.txt](https://wishlistsuite-1.gitbook.io/wishlistsuite-help-doc/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://wishlistsuite-1.gitbook.io/wishlistsuite-help-doc/app-overview/wishlist-analytics.md).
# Wishlist Analytics
### Overview
The **Analytics tab** gives you a data-driven overview of how customers interact with your wishlist feature.
By tracking wishlist engagement, conversions, and product demand, merchants can better understand **customer purchase intent** and make smarter marketing and inventory decisions.
***
### โฑ๏ธ Date Filters
At the top of the analytics dashboard, you can filter data by time period.
Available filters include:
* Today
* Yesterday
* Last 7 Days
* Last 30 Days
* Last 90 Days
* Last 365 Days
* Custom Date Range
This allows you to track trends and evaluate how wishlist performance changes over time.
***
### ๐ Key Performance Metrics (KPIs)
These high-level metrics provide a quick overview of how customers are using wishlists in your store.
**โญ Total Wishlists-** The total number of wishlists created across all customers.
**๐ฅ Total Customers-** The number of logged-in customers who have interacted with the wishlist feature.
**๐ฐ Conversion Rate**- The percentage of wishlist items that were eventually purchased.
This metric helps merchants measure how effectively wishlists translate into actual sales.
***
### ๐ Customer Engagement Metrics
These metrics show how customers interact with your wishlist feature.
**๐ Wishlist Views**\
The total number of times customers have viewed their wishlist pages.
**โ Items Added**\
The number of products customers have added to their wishlists.
**๐๏ธ Conversions**\
The number of wishlist items that resulted in completed purchases.
Tracking these metrics helps merchants understand **customer interest and purchase intent**.
***
### ๐ Saves by Surface
The **Saves by Surface** section shows where customers are adding products to their wishlists within your store.
Examples include:
* Product pages
* Collection pages
* Cart page
* Other storefront surfaces
This insight helps merchants determine **where wishlist buttons are most effective**.
***
### ๐ Top Products
The **Top Products** section highlights the most wishlisted products in your store.
This helps merchants quickly identify:
* High-interest products
* Trending items
* Products customers intend to purchase later
These insights can help with:
* inventory planning
* merchandising decisions
* promotional campaigns
***
### ๐ต Revenue Insights
Wishlist analytics also helps track how much revenue your wishlist feature generates.
**๐ฐ Revenue from Conversions**\
The total revenue generated from products that were purchased after being added to a wishlist.
**๐งพ Average Order Value (AOV)**\
The average order value for purchases that originated from wishlist conversions.
These metrics help merchants understand the **direct financial impact of wishlist engagement**.
***
### ๐ How This Helps Your Store
Wishlist analytics provides actionable insights that merchants can use to improve store performance.
**๐ฆ Inventory Planning**\
Use the **Top Products** list to ensure high-demand items stay in stock.
**๐ Optimize Wishlist Placement**\
Use **Saves by Surface** data to determine where wishlist buttons perform best.
**๐ฃ Improve Marketing Campaigns**\
Target customers with reminders, discounts, or emails for products they have saved.
**๐ Track ROI**\
Measure how much revenue your wishlist feature generates through **conversion and AOV metrics**.
***
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