Discover the AWS solution that requires the least operational effort to optimize an ecommerce site’s search tool and present customers with the most relevant products they are likely to purchase. Learn how Amazon CloudSearch can boost search relevance with minimal configuration.
Table of Contents
Question
An ecommerce company discovers that the search tool for the company’s website is not presenting the top search results to customers. The company needs to resolve the issue so the search tool will present results that customers are most likely to want to purchase.
Which solution will meet this requirement with the LEAST operational effort?
A. Use the Amazon SageMaker BlazingText algorithm to add context to search results through query expansion.
B. Use the Amazon SageMaker XGBoost algorithm to improve candidate ranking.
C. Use Amazon CloudSearch and sort results by the search relevance score.
D. Use Amazon CloudSearch and sort results by the geographic location.
Answer
The correct solution that will meet the requirement of improving the ecommerce search tool to present the most relevant results to customers with the least operational effort is:
C. Use Amazon CloudSearch and sort results by the search relevance score.
Explanation
Amazon CloudSearch is a fully managed service that makes it simple and cost-effective to set up, manage, and scale a search solution for your website or application. It supports 34 languages and popular search features such as highlighting, autocomplete, and geospatial search.
Importantly, CloudSearch automatically ranks results by relevance score out-of-the-box, without needing to configure any custom algorithms or models. The relevance score is calculated based on factors like text match, term frequency, fields, and distance for geospatial searching.
By simply using CloudSearch and sorting the results by the relevance score it provides, the ecommerce company can immediately start presenting more relevant search results to customers that they are likely to purchase. This requires very minimal setup and configuration compared to the other options.
The other options would require more significant effort:
- Using the SageMaker BlazingText algorithm for query expansion requires training a custom Word2Vec model and modifying the search indexing and querying system to incorporate the model’s output.
- Using the SageMaker XGBoost algorithm to rank results requires collecting training data, selecting features, training and deploying a supervised learning model, and integrating the model with the search system.
- Sorting CloudSearch results by geographic location doesn’t actually improve the relevance of the search results themselves. It just reorders relevant results by location, which doesn’t address the core issue.
Therefore, using Amazon CloudSearch’s built-in relevance ranking is the solution that will improve the search tool’s performance for customers with the least amount of effort for the ecommerce company to implement and maintain.
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