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Product Listing Pages (PLP)

Product Listing Pages (PLPs) are pages in e-commerce that offer a structured overview of products within a specific category or search query and therefore play a central role in user guidance and product selection: They serve as a central point of contact for customers searching for specific items and are designed to help them find suitable products quickly and easily.
 
Elements of PLPs
Important aspects of PLPs are:
  • Product list/product grid: Clear presentation with product images, titles, prices.
  • Category description / editorial content: SEO-optimised introductory texts and advisory content such as shopping guides or thematic notes provide users with orientation and additional information on the category. At the same time, this content contributes to better findability in search engines.
  • Filter functions: Users can narrow down the product selection, for example by price, brand, colour, size, ratings, material or availability.
  • Sorting options: Users can sort the displayed products according to criteria such as price, popularity, new products, bestsellers, ratings or relevance. This makes it quicker to find the right product.
  • Search function for a targeted search for products or features.
  • Call-to-action elements such as "Add to basket".
 
Optimisation and automation of Product Listing Pages (PLPs)
The optimisation and automation of Product Listing Pages (PLPs) aims to improve the efficiency, relevance and scalability of these pages in e-commerce.

Automation:
  • Automated generation of category descriptions: With the help of Natural Language Generation (NLG) or AI-supported systems such as GPT, search engine optimised texts can be created and updated automatically.
  • Multilingualism: By combining translation services such as DeepL with AI models, it is possible to automatically create category texts in multiple languages.

Optimisation:

  • Personalisation of the product display: Product displays can be dynamically adapted based on user data (e.g. behaviour, location, interests).
  • Dynamic filter and sorting options: Filters and sorting functions automatically adapt to product availability, category or user behaviour to support relevant product selection.
  • Impact measurement and A/B testing: By measuring the impact on user behaviour and conversion rates, the most effective design can be determined and optimised based on data. A/B testing makes it possible to directly compare different variants of PLPs (e.g. filter position, product sequence, text length).

(Englisch) PLP
 
These activities enable the scalable maintenance and continuous improvement of PLPs while simultaneously reducing manual effort.