WPC Smart Recommendations Premium

WPC Smart Recommendations Premium adds behavioural product recommendations to WooCommerce stores. It looks at products purchased together, products viewed in the same browsing session and customer affinities, then places related products in several parts of the buying journey. The result is a recommendation layer that covers product pages, sidebars, popups, thank-you pages and emails rather than relying on one fixed related-products block.

Several recommendation signals

The strongest part of the feature set is its range of signals. Co-purchase recommendations support the familiar “Customers who bought this also bought” pattern, while co-view recommendations use products viewed within the same session. When those signals do not provide a suitable result, the plugin falls back to popular products from the same category. That gives store owners a defined fallback instead of leaving every recommendation slot dependent on an established purchase history.

Recommendations can also reflect actions outside the current product page. Integration with WPC Smart Wishlist and WPC Smart Compare brings wishlist and comparison activity into the available recommendation sources. A Trending Now section uses time-decay scoring, so recent activity has a role in what appears. Recently Viewed products are stored with localStorage, keeping that particular feature in the browser rather than sending each view to the server.

Placement and presentation

The plugin offers enough placement options for a store to build different recommendation moments. A personalised For You popup appears once per session, while order-based recommendations target thank-you pages and emails. Manual recommendations are available per product, with drag-to-reorder controls for stores that want editorial control alongside automated results.

Display options are similarly practical:

• Carousel and slider layouts use CSS scroll-snap without a JavaScript dependency.
• Grid layouts use WooCommerce product cards and support between two and six columns.
• Compact List layouts suit sidebars and popups where a full product card would take too much space.
• Product links can open in the same tab, a new tab or a Quick View popup.

This combination lets a store use a dense list in a sidebar, a larger grid on a page and a swipe-friendly carousel elsewhere without treating every recommendation area the same way.

Control over the result

Store rules are not limited to whatever the algorithms select. Products that are out of stock or unpurchasable can be excluded, as can recently purchased products within a configurable timeframe. Specific product types and pages can also be excluded. Priority rules are drag-to-reorder, which gives administrators a way to decide which recommendation source takes precedence when several sections could apply.

Social proof badges add another layer, using messages such as “12 people bought this today”. Used with care, these badges give recommendation blocks a stronger indication of current activity. The manual per-product system is also useful for merchandising campaigns where a shop needs to put a particular accessory or complementary item ahead of a purely behavioural result.

What to weigh

The breadth of the system creates a configuration burden. Co-purchase and co-view recommendations depend on meaningful store activity, so a new or low-traffic catalogue has less behavioural material to work with and will lean more heavily on category fallbacks, trending products or manual selections. The plugin provides those alternatives, but someone still needs to decide which signals and placements make sense for the catalogue.

There is also a risk of overloading the shopping experience. Product-page recommendations, a For You popup, recently viewed items, social proof and post-order suggestions all compete for attention. Priority rules help organise the output, but they do not replace a merchandising plan. Finally, localStorage-based recently viewed products are tied to the shopper’s browser context, so that history is not the same as a profile that follows a customer between devices.

Who it suits

This is a good fit for WooCommerce shops with enough catalogue activity to support behavioural recommendations and enough product variety to benefit from cross-selling. It is particularly relevant to stores selling accessories, repeat-purchase goods or products commonly bought in combinations. Shops that need strict merchandising control also get useful tools through manual recommendations, exclusions and reorderable priority rules.

Smaller stores can still use category fallbacks, manual selections and recently viewed products, but they should keep the initial setup focused. The plugin is best approached as a collection of recommendation sources and placements to tune over time, not as a single switch that automatically produces the right product for every visitor.