To implement faceted search for Google Shopping, we need to follow a few steps: 1. Identify relevant filters: Based on the search string entered by the user, we need to identify the relevant filters. For example, if the user searches for "Television", relevant filters could include size, brand, price, type, resolution, etc. 2. Group filters: Once we have identified the relevant filters, we need to group them logically to make it easier for users to navigate. For example, we could group filters by category (e.g. size, resolution), brand, or price range. 3. Display filters: We need to display the filters in a way that is easy for users to understand and interact with. One approach could be to display the filters in a vertical list on the left-hand side of the search results page. As the user selects different filters, the search results should update dynamically to reflect the selected filters. 4. Handle complex queries: We also need to handle complex queries where users enter multiple search terms or use operators such as AND, OR, NOT. In such cases, we need to ensure that the relevant filters are still displayed and that the search results are updated dynamically. 5. Optimize filter performance: Finally, we need to optimize the performance of the filters to ensure that they load quickly and don't slow down the search results page. This could involve using caching, lazy loading, or other performance optimization techniques. Overall, implementing faceted search for Google Shopping would require close collaboration between product managers, designers, and engineers to ensure that the filters are relevant, easy to use, and performant.