The PLP in the e-commerce funnel
A product listing page is a filtering surface: this is where a shopper narrows hundreds of products
down to a few candidates worth a closer look. The typical path:
Homepage → PLP (category) → PDP (product card) → Cart → Checkout
The PLP is where critical losses happen. If the right product is not visible in the first two rows
of the grid, a significant share of shoppers leave or start applying filters. Personalizing this
step raises the odds that a relevant product lands inside the visible area.
PLP structure
A standard PLP carries:
- Breadcrumbs — the navigation path (Home / Apparel / Jackets)
- Category title and description — for SEO and for orientation
- Facets (filters) — brand, price, size, colour, availability
- Sorting — popularity, price, newest, rating
- The grid of product cards — the main content
- Pagination or infinite scroll
PLP metrics
| Metric | Formula | Benchmark |
|---|---|---|
| PLP → PDP CR | Card clicks / PLP visitors | 30–60% |
| Time to first click | Seconds from load to click | < 30 sec |
| Filter usage | Share of sessions applying a filter | 20–40% |
| PLP bounce rate | Exits with no action / visitors | < 30% |
Personalized versus standard sorting
By default, sort by popularity shows the same top of the grid to everyone. That is efficient for a
cold start but suboptimal for returning shoppers.
Personalized sorting lifts the products that match the shopper’s affinity: preferred brands, the
price band they buy in, attributes they have looked at before. Someone with a history of buying
Nike in a given price range sees it at the top — without touching a filter.