Next-gen customers have access to multiple shopping channels and low tolerance to latencies. They expect retail sites to provide best-in-class experiences along with complete and relevant search result for the products they are looking for. Retail giants like Amazon and Walmart are giving top notch experiences in site search and customers expect the same or better experiences from everyone else.
Based on the complexity of implementation and impact on user engagement, search features can be divided into 3 layers.
These are the features that help users with faster search experiences – these are like hygiene factors that today’s users expect from all the e-commerce search engines.
These are features driven by AI/ML models and understand users intent and context to give relevant results. Some examples are:
Advanced features create engine’s own understanding of product and search queries driven by user behaviour – these features read between the lines to capture user’s interest and give engaging products even though user might not have mentioned it explicitly through the search query
Search is fast emerging as the centre of all eCommerce stores. More and more people are using search to find relevant products instead of relying on traditional menus and navigations. With deeper understanding of user’s intent and interpretations derived through user behaviour using advanced AI algorithms, search engines are making bigger strides than ever. With domain specific use cases, eCommerce companies will be able to give seamless, satisfying and engaging user experiences
AIE can strong experience in building custom search engine solutions that are robust and bring relevant, lightning-fast search capabilities to your application. If you are interested in deploying a lightning-fast search solution for your customers, then contact us for a free consultation and quote