Many TV shows start strong but decline in quality over time, leaving viewers frustrated after investing hours into them. Currently, there's no easy way to identify when this drop happens, making it hard to decide whether to continue watching or stop before disappointment sets in.

How It Could Work

One way to address this could be by analyzing review data from platforms like IMDB or Rotten Tomatoes to pinpoint when a show's quality significantly declines. This information could then be displayed to viewers through:

• An integrated tool on review platforms
• A browser extension for streaming sites
• A standalone recommendation app

The system might look at factors like episode ratings over time, critic score changes, viewer sentiment in comments, and drop-off rates to determine quality dips. For divisive shows, it could show different perspectives (e.g., "Critics suggest stopping after Season 2, but fans enjoyed Season 3").

Potential Benefits and Challenges

For viewers, this could save time and improve entertainment experiences. Review platforms might benefit from increased engagement, while streaming services could see higher satisfaction despite potentially reduced viewing hours.

Key challenges would include:

• Ensuring recommendations don't contain spoilers
• Handling shows where quality decline is subjective
• Getting access to comprehensive review data

A simple starting point might be a browser extension that analyzes publicly available ratings, with options to expand into more sophisticated analysis and platform integrations later.

How It Compares to Existing Options

While platforms like IMDB show episode ratings and Rotten Tomatoes provides season scores, none currently analyze this data to give clear "stop here" recommendations. This approach would automate the analysis that viewers currently have to do manually when scanning rating graphs or reading multiple reviews.

Such a tool could help viewers make more informed decisions about their TV watching, potentially saving countless hours of disappointing viewing while helping people focus on content they'll truly enjoy.