Design a Search Ranking Algorithm for ShopSmart

Company Context

ShopSmart is a rapidly growing e-commerce platform specializing in consumer electronics, with over 5 million monthly active users and a revenue of $500 million in the past year. Despite its growth, the company faces challenges in search functionality, leading to user frustration and abandoned carts. Currently, the search feature yields a high bounce rate, with users often unable to find relevant products quickly.

Problem or Opportunity

The VP of Product has identified that the existing search algorithm does not adequately prioritize relevant results. A recent user survey indicated that 70% of users are dissatisfied with search results, leading to a 30% drop in conversion rates for users who rely on search. The goal is to design a new search ranking algorithm that enhances result relevance, improves user satisfaction, and ultimately increases conversion rates by 20% within six months.

Deliverables

1. Define user personas and their needs related to the search experience.
2. Outline the key factors that should be considered in the search ranking algorithm.
3. Propose a framework for evaluating the performance of the new algorithm.
4. Identify potential risks and mitigation strategies associated with the implementation.
5. Establish success metrics to measure the algorithm's effectiveness post-launch.

Constraints

• Limited engineering resources with only 2 data scientists available for the project.
• Must launch a minimum viable product (MVP) within 10 weeks.
• The solution must integrate seamlessly with existing infrastructure and not increase page load time beyond 300ms.