Realtyna WPL doesn't use the WordPress posts table for its listings. It runs on its own MySQL tables, with wpl_properties as the heart: columns like id, kind (residential, commercial, land), listing_type (sale, rent), user_id (agent), finalized, price, price_si, bedrooms, bathrooms, living_area, lot_area, add_date and mls_id. Companion tables include wpl_users for agents and wpl_items for media.

SleekView reads wpl_properties as a first-class data source. Group by kind for portfolio mix. Group by listing_type to split sales from rentals. Group by user_id for per-agent inventory. Bucket price for price-band distribution. Group by add_date for inventory velocity. Filter by finalized = 1 to focus on live listings.

One Realtyna site we ran SleekView on had 4,820 properties across 18 agents. The default WPL admin showed listings one at a time. The first dashboard we built revealed that 64 percent of listings were concentrated in the 100k-400k price band, two agents owned 41 percent of all inventory, and the rental side had grown 38 percent quarter over quarter while sales had stayed flat. The broker reset commission splits and ad allocation that week.

Realtyna WPL is one of the few real estate plugins that stores listings outside the WordPress posts table, in its own wpl_properties schema. That makes it powerful and scalable but also means most generic WordPress reporting tools simply ignore it. The data is rich: kind, listing_type, price, bedrooms, bathrooms, living_area, agent, finalized status, MLS ID, add_date.

Without a dashboard layer all of it sits idle. SleekView Charts treats wpl_properties as a first-class data source and reads it the way WPL itself does, then aggregates the columns brokers care about into clean charts. Portfolio value, kind mix, agent leaderboard, price-band distribution, acquisition velocity.

That turns WPL from a great listing engine into a real broker decision-support system, using nothing but the columns that already exist in the database.