Web scrapping data from customer reviews

I'm trying to analyze customer reviews of Android and iOS apps using information like this: ANDRIOD [login to view URL] iOS [login to view URL] Specifically, it would be: 1) web scrapping that pulls out and structures data based on a) company, b) number of reviews, c) positive / negative sentiment of review (using keywords); d) number of community agreement (e.g., thumbs up) and e) ways to bucket complaints. 2) Analyzing the information leveraging some off-the-shelf AI / semantic analytics software (I would need your help in assessing which software would make the most sense for this project and I would cover cost of analysis). 3) Provide intelligence in an Excel sheet which I can then build out dashboard and analytics, etc. Select questions I would like to answer from this analysis (I can add further questions but including here to give a sense of how I would want to use the data) 1) Which companies have the worst / best experience? 2) Which industries have the worst / best experience? 3) What is the role in customer service in the overall experience of each app, company and industry? 4) What are the key buckets of experience that are worst / best? 5) What is the level of community engagement with what type of comment (e.g., number of thumbs up / thumbs down by comment, category and company. We could start first on either Android or iOS - ultimately I would need both but we could take one at a time. The purpose of this research is to understand how customer experience maps with size of copmany and the specific issues (if possible to bucket individual comments) and how this ties to comments. As part of this project, it would be important to first lay out what information could be included in this assessment. Thanks, Jesse