I I have data visualization related problem

Context: The data is from a search platform that the end customers use as a capability within their products. Data: Attached file contains Query performance, Product performance, and product description of a sample set from one of the search product customers. Objective: To increase conversions for customers. Question: What would you do keeping in mind that the customer uses this search product? How can you use this data to bring out insights to improve the search product? Definitions of some terms: 1) Hits - Number of Search Queries 2) Click-throughs - Number of times visitors clicked on any one of the results in the search listing page 3) Clicks - Cumulative Number of times visitors clicked on any result in the search listing page (Clicks would always be greater or equal to than clickthroughs) 4) CTR = Clickthrough rate = Click Throughs/Hits 5) Orders - Orders placed against the search query (Query report) or for the particular product (Product Performance report) 6) You can ignore the initial price and final price from your analysis. Look forward to your reply with the insights that you can derive from this data using basic data exploration methods. If you are doing this on Python Notebooks, please share both the .ipynb as well as .html versions.