SleekView Charts for WooCommerce Product Recommendations
WooCommerce Product Recommendations runs rule-based and amplifier engines for cross-sells, frequently-bought-together, and recently-viewed blocks. SleekView Charts turns its impression, click, and order-attribution data into a saved dashboard.
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Recommendation engines write data, charts decide which ones earn their slot
WooCommerce Product Recommendations (the official Woo.com extension) lets merchants configure named recommendation engines (rules that pick which products to show in cart, checkout, product, and cross-sell locations). Each engine logs impressions and clicks, and orders that follow get tagged with the engine that drove them. The data lives in custom tables plus order meta, with the plugin's analytics screen summarising it engine-by-engine.
SleekView Charts reads those tables and exposes engine name, location, click count, impression count, and attributed order total as chartable columns. A Number sums attributed revenue this month. A Pie splits revenue by engine so the unproductive ones are obvious. A Bar shows click-through rate per location. An Area trends attributed orders so the impact of adding a new engine or tweaking an existing rule is visible.
The chart layer makes the trade-offs explicit. Cart real estate is finite; a recommendation block that does not earn its slot should go. SleekView turns that conversation into something the team can have with one saved dashboard.
Workflow
From recommendation logs to an engine dashboard in four steps
Pick the dataset
Pivot the columns
Configure chart cards
Save the dashboard
Sample dashboard
Charts you can build from WooCommerce Product Recommendations data
Attributed revenue this month
Sum(attributed_total)
Revenue by engine
Sum(attributed_total)
group by engine_name
Click-through by location
Average(ctr)
group by location
Attributed orders per day
Count
group by order_date
Comparison
Default WooCommerce Product Recommendations reporting vs SleekView Charts
Default Product Recommendations analytics screen
- Analytics shows per-engine summary rows but does not chart revenue share across engines.
- Click-through rate by location is reported only as a number, not as a comparable bar.
- Attributed revenue trend over an arbitrary range is not part of the default UI.
- No saved KPI for total attributed revenue across every engine.
- Engines that under-perform require manual export to identify.
SleekView Charts
- Reads the recommendation log tables and order meta directly, no extra sync needed.
- Pivots engine_name, location, ctr, and attributed_total as groupBy columns.
- Number, Pie, Bar, Area, Line, Radar, and Radial chart types on the same dataset.
- Aggregations cover count, sum, average, minimum, and maximum.
- Same data feeds Table, Kanban, and Charts views in one workspace.
Features
What SleekView Charts gives you for WooCommerce Product Recommendations
Revenue per engine
A pie of attributed revenue by engine name turns the engine list into a portfolio view that ranks each rule by impact.
Location-aware CTR
Click-through rate by location surfaces whether cart, checkout, or product slots actually engage shoppers.
One dataset, every view
Recommendation logs feed Table, Kanban, Feedback, and Charts views. Switch presentation without rebuilding the query.
Audience
Who builds WooCommerce Product Recommendations charts dashboards with SleekView
Growth and CRO teams
Revenue per engine and CTR per location feed weekly experimentation reviews and decisions on which engines to retire.
Merchandising teams
Attributed orders trend shows whether a manually curated cross-sell engine outperforms the amplifier defaults.
Founders and operators
One KPI for attributed revenue answers the recurring question of how much the recommendation stack actually earns.
The bigger picture
Recommendation engines need a portfolio dashboard, not a row-by-row list
Product Recommendations supports several engines at once: rule-based cross-sells, amplifier-driven frequently-bought-together, recently-viewed blocks, and more. Cart and checkout real estate is finite, so each engine has to earn its slot, but the default analytics screen lists engines row by row without making the portfolio view easy. SleekView Charts reads the same impression, click, and attribution data and turns engine_name and location into chart axes.
The team sees revenue share at a glance, retires the weakest engines, and trusts attributed revenue as a single KPI. The plugin keeps owning the rules and the amplifier; SleekView charts the outcomes.
Questions
Common questions about SleekView Charts for WooCommerce Product Recommendations
Yes. SleekView reads wp_wc_orders or wp_posts depending on the order storage, and the recommendation log tables are unchanged.
Yes. Click count divided by impression count surfaces as a chartable value on a bar or area card.
Yes. Any engine created in the plugin admin appears as a groupBy value once it has logged at least one event.
Yes. SleekView reads the same tables, it does not replace the screen. Many teams keep both.
Yes. Category taxonomy joins from wp_term_relationships surface as groupBy columns so category mix per engine is one chart.
No. Charts render in the admin and read existing tables. Recommendation blocks render unchanged.
There is no hard cap. Most growth teams build six to ten cards per saved view to keep the dashboard scannable.
Yes. The same capability checks that gate the Product Recommendations screens also gate the charts dashboard.
Pricing
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