Competitor social listening: from scraping to report

The quickest way to see a competitor's social performance in a market is a ready-made Apify Actor that scrapes posts and comments. But an Actor returns a pile of raw data: hundreds or thousands of comments, mostly in another language.

Three problems:

• Raw comments, no conclusions: it won't say what share is negative or what people mainly complain about
• No sentiment or topic tags: telling praise from complaints, or service from price, means tagging by hand or exporting to another tool
• Not decision-ready: you get a spreadsheet, not something to report or act on

I packaged the whole analysis method as a reusable Skill:

• Designed the workflow: posts → comments → analysis → report
• Wrote the analysis playbook: how to tag sentiment and topics, what the report contains
• Documented the Actors and wrote the scraping scripts, called through the Apify API from Claude Code

From a pile of comments to a report worth discussing in 20 minutes. What it does for the business:

• Competitors' marketing calendar: read alongside product roadmaps, it shows their monthly, quarterly and yearly rhythm
• Targeted moves: weaknesses the report exposes, such as promotion depth or recurring complaints, become openings for us
• Longer horizons: stretched to a year, it shows how competitors' story and user sentiment shift