Comparing Search Functionality of Amazon, Best Buy and Walmart
Search engines have become integral to our daily lives. They serve as indispensable tools for conducting simple searches to find contact information, stock prices, and music on our smartphones. Contextual searches have further evolved to comprehend user intentions and provide an intuitive way to retrieve relevant information. Intelligent searches leverage query statistics and machine learning techniques to guide the ranking of search results, with the aim of enhancing product purchase probabilities through improved relevance.
A search engine acts as an all-knowing representative of your company, offering a convenient platform for users to ask questions and obtain information about your products or services. Users may prefer searching by category or topic, seek the best reviews, or sort results by the lowest price or highest quality. A seamless user experience, whether on desktop or mobile, encourages consumers to delve deeper into search results in order to find the most suitable product for their needs.
This ebook presents a comprehensive comparison of the search functionalities of the highest-rated e-commerce websites: Amazon, Walmart, and Best Buy. It evaluates their search features based on various metrics such as relevancy, precision, hit highlighting, facets, boosting, and ranking algorithms. Additionally, the ebook identifies areas where the search features of Walmart, Amazon, and Best Buy could be further improved to provide an even better user experience.
