Sentiment Dashboard/data analysis & Monetization

I’m building a service that pulls public sentiment from our Facebook pages, & groups, Instagram, and Twitter, shows it in a live, interactive dashboard, and then turns those insights into value data and revenue. To get there, I need a clear, repeatable system that relies primarily on browser-based scraping extensions (my preferred method), yet remains flexible enough to swap in Python scripts or third-party APIs later if necessary.

Here’s what I want to walk away with:

• A working scrape-to-dashboard workflow
– Configure the chosen browser extension, run test scrapes on the three platforms, and 30+ pages, and map the raw fields (post text, reactions, comments, timestamps, etc.).
--Advise on automatic commenting and like, share methods to save time in engagement.
– Clean and transform the output, stream it into an interactive dashboard (Power BI, Tableau, Looker Studio, or a tool you propose), and add filters so end-users can drill down by keyword, date range, and platform.

• Hands-on demonstration & documentation
– Live screen share or recorded session that walks me through each step, from launching the scraper to publishing the dashboard.
– A concise “how-to” guide so my in-house team can reproduce the process without you.

• Monetization blueprint
– Practical ways to package the insights: subscription tiers, pay-per-report models, white-label dashboards, alert services, or data licensing.
– Clear examples showing how the workflow you build feeds directly into those revenue streams.

Acceptance criteria: the dashboard must refresh with new data pulled via the browser extension, sentiment scoring should be visible at a glance, and I need at least two monetization pathways mapped with projected pricing.

If you’ve done something similar, a quick demo or portfolio link will help me see your approach. Let’s make social sentiment both clear to our clients and profitable for us.