Recommendations
E-commerce
E-commerce
Recommendations suggest products or content that may suit you. In an online store, they can appear as alternatives or complementary items.
A recommendation system selects products or content using available information. This might include the product you are viewing, similar attributes, popular items or previous behaviour. It can use fixed rules, AI or a combination of both.
Recommendations serve different purposes. Alternatives help you compare similar products. Complementary items go with what you are viewing or buying, such as shoe care products. Personalised recommendations use information about your preferences or behaviour. A bestseller list is not automatically personalised.
Recommendations can appear on a product page, in your basket or in an email. Assess relevance and outcomes: do they help people choose, lead to suitable purchases, and how do returns change? More clicks alone do not prove that recommendations are better.
Tip
Check stock, variants and compatibility. Shoes in an unavailable size or an accessory that does not fit are not useful recommendations.
Related terms
- MerchandisingMerchandising is selecting and presenting your range to help customers discover and buy products. Online, it includes product ranking, categories and recommendations.
- Conversational CommerceConversational Commerce helps you choose or buy products through a conversation with a person, chatbot or AI assistant.
- AI SearchAI Search uses AI to match queries with information. It can power an online store's search function or a search service that generates answers.