SleekView Charts for TI WooCommerce Wishlist
TI WooCommerce Wishlist (TInvWL) persists data in tinvwl_lists and tinvwl_items. SleekView Charts turns those tables into the merchandising and marketing dashboard the default admin lacks.
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TInvWL data your team can read at a glance
TInvWL is widely deployed because it adds multi-wishlist support and reasonable privacy controls without much fuss. The downside is that the same multi-wishlist feature makes the default admin harder to read, not easier: per-customer aggregation falls apart because each customer can carry multiple lists. Merchandising teams typically end up running SQL or exporting CSVs to find most-wanted products, and marketing skips wishlist-driven campaigns because the segmentation is too much work.
SleekView Charts reads tinvwl_lists and tinvwl_items directly and aggregates them into a latent-demand dashboard. Most-wanted products rank on a Bar chart by add count, with TInvWL's per-item quantity respected so B2B-style stores see the real demand signal. Wishlist age mix breaks down on a Donut. Top multi-wishlist owners (customers with the most active lists) rank as a separate Bar for share-link analysis and high-engagement customer outreach. Daily activity layers on an Area trend.
The dashboard pairs with the SleekView TInvWL table view so a merchandiser clicks the most-wanted Bar and gets the row-level customers behind it. A marketer clicks the stale slice and exports the segment for a win-back campaign without ever leaving WP Admin.
Workflow
TInvWL dashboards in four steps
Connect tinvwl tables
Build demand cards
Save segment dashboards
Drill and export
Sample dashboard
Charts you can build from TI WooCommerce Wishlist data
Total wishlist items
Sum(quantity)
Most-wanted products
Sum(quantity)
group by product_id
Wishlist age mix
Count
group by wishlist_age_bucket
Top multi-wishlist owners
Count
group by user_id
Comparison
Default TI Wishlist reports vs SleekView Charts
Default TI admin
- Most-wanted aggregation isn't a built-in chart
- Per-quantity demand signal isn't surfaced for B2B stores
- Wishlist age mix requires manual filtering
- Multi-wishlist user analysis needs custom SQL
- Daily activity trends aren't graphed in WP Admin
SleekView Charts
- Most-wanted products ranked by quantity on one Bar
- Wishlist age mix as a Donut for outreach segmentation
- Total wishlist quantity as a single Number card
- Top multi-wishlist owners ranked as a Bar
- Privacy and share-key filters apply across every card
Features
What SleekView Charts gives you for TI WooCommerce Wishlist
Quantity-aware demand ranking
TInvWL stores per-item quantity, useful for B2B stores. The most-wanted Bar respects quantity so a wishlist of 50 units of one SKU ranks accordingly instead of being treated as one add.
Outreach segments
Donut chart of wishlist age separates fresh interest from stale and abandoned. Marketing builds win-back campaigns from the right slice without exporting raw tables.
Multi-list customer ranking
Bar chart of customers by number of active wishlists surfaces high-engagement users. Per-customer outreach lands on customers who actively curate, not just casual browsers.
Audience
Who builds TI WooCommerce Wishlist charts dashboards with SleekView
Marketing
Abandoned-list Donut slice feeds win-back campaigns. Click, filter, export, send. The full segment workflow stays inside WP Admin.
Merchandising
Most-wanted Bar ranks products by quantity demand. Stocking decisions reflect actual wishlist signals rather than past-cycle best-sellers.
B2B ops
Quantity-aware demand cards turn TInvWL into a draft-purchase-order signal. The dashboard reveals which SKUs B2B customers plan to buy in bulk before they actually buy.
The bigger picture
TInvWL data is wasted without a dashboard
TInvWL's multi-wishlist feature is useful for end users but actively harmful for default-admin operational reporting: per-customer aggregations break down when customers carry multiple lists with different privacy states. The raw data is good, the surface is bad. SleekView Charts builds the dashboard directly on the two TInvWL tables and respects the per-item quantity that B2B-style stores actually depend on.
Most-wanted products rank by real demand. Wishlist age mix splits the segments that marketing needs. Top multi-wishlist owners surface the high-engagement customers worth specific outreach.
Daily activity confirms when promotion lands. The dashboard pairs with the SleekView TInvWL table view so drill-down from chart segment to row-level customers happens in one click and exports keep the segmentation work inside WP Admin. The plugin is doing all the work of capturing the signal; the chart layer just makes it usable instead of leaving it to gather dust in two custom tables.
Questions
Common questions about SleekView Charts for TI WooCommerce Wishlist
Yes. TInvWL stores quantity per tinvwl_items row, which matters for B2B stores. Most-wanted product Bars use Sum on quantity rather than row count so a wishlist of 50 units ranks higher than 50 separate single-unit wishlists. The configuration is per-card.
 Yes. Joining tinvwl_items with WooCommerce orders by product_id and customer_id produces a conversion-rate column. A Bar chart of conversion rate per product surfaces which wishlist items actually convert versus which languish across cycles.
 Yes. Guest wishlists with session_id sit in tinvwl_lists with no user_id. Cards count them alongside authenticated wishlists or filter to authenticated-only for clean customer-segmentation aggregations. Either configuration works.
 Yes. The Top Multi-Wishlist Owners Bar groups by user_id and counts distinct list IDs per user. Pair with a Donut of privacy distribution per multi-list user to understand whether high-engagement customers prefer private curation or public sharing.
 Yes. The two TInvWL tables are indexed on user_id and product_id. SleekView Charts aggregates server-side and caches per-card results at a configurable interval. Stores with millions of wishlist rows render dashboards in well under a second with caching enabled.
 Yes. Privacy and share_key live on tinvwl_lists as filterable columns. Dashboard-level filters cascade across every card, useful for share-link debugging or for public-list-driven social-proof analysis scoped to public lists only.
 Yes. Wishlist data lives independent of order storage, so HPOS configuration changes only the order table. The conversion-rate analysis reads from whichever order table HPOS is configured to use; the wishlist-side cards remain unaffected.
 Yes. Cards and dashboards save with WordPress capability gating. Marketing sees outreach cards, merchandising sees most-wanted Bars, B2B ops sees quantity-aware demand, and support sees per-customer Number cards. Each role keeps its own pinned view.
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