TI WooCommerce Wishlist (TInvWL) stores wishlist data in tinvwl_lists and tinvwl_items, two dedicated custom tables that hold lists, items, privacy, share keys, and quantities. The default admin separates lists and items into different screens and surfaces basic counts but no cross-aggregation, so questions like which products are most often wishlisted require manual SQL or per-list clicks.

SleekView joins the two TI tables directly and exposes the views that actual operations need: most-wanted-products with add counts, abandoned-list segments by age, per-customer histories with privacy state, and shared-list audits filtered by share key. Merchandising decisions about stocking and promotion stop relying on past best-sellers alone and start incorporating the latent demand the wishlist data captures.

For multi-wishlist users — TI's signature feature — rows group naturally by user, so support sees that one customer maintains four lists with different privacy settings and can troubleshoot share issues in seconds rather than minutes.

TInvWL is widely deployed because it adds multi-wishlist support and reasonable privacy controls without much fuss. That ubiquity also means a lot of wishlist data is being captured and almost none of it is being used. The default admin shows counts but not aggregations, and the multi-wishlist feature — useful for end users — makes per-customer reporting harder rather than easier in the standard view.

A merchandiser planning quarterly stocking has no built-in route to most-wanted-products. A marketer building a win-back segment can't filter wishlists by last-update without exporting and processing in a spreadsheet. A support agent helping with a shared-list issue clicks into each of the customer's four lists to find the right share token.

Joining the TI tables and exposing them as views fixes that. Most-wanted-by-product becomes a single sortable list. Abandoned-wishlist outreach becomes a saved filter that piles into the marketing tool.

Per-customer history groups all of a user's lists in one place. The plugin's data model is good; what it lacks is an operational layer to make the data actionable rather than archival.