Skeptical Tom

Analyzes historical pricing data for products on e-commerce pages and displays price trends to show whether the current price is at a peak, discount, or historical low. Integrates with price tracking databases to surface pricing patterns across time.

Calculates the effective cost-per-use of a product by dividing total price by estimated usage frequency or lifespan. Particularly useful for fashion, lifestyle, and durable goods where true value isn't immediately apparent from price alone.

Analyzes customer reviews on product pages to extract overall sentiment and surface key themes about product quality, durability, and value. Aggregates review sentiment into a digestible summary to help users understand real customer experiences.

Injects a deliberate moment of pause before checkout by surfacing analytical insights about the product. Creates a decision-making event rather than allowing automatic dopamine-driven purchasing by presenting cost-per-use, price history, and sentiment data at the critical checkout moment.

Automatically detects and analyzes product pages in real-time as users browse e-commerce sites. Triggers data collection and insight generation without requiring manual input or navigation to a separate tool.

Identifies the same product across different retailers and displays price variations to show where the best deal is available. Helps users avoid overpaying by showing lower prices on competing platforms.

Calculates and projects the total cost of subscription-based purchases over time, showing annual and multi-year costs. Helps users understand the true financial commitment of recurring purchases before subscribing.

Synthesizes all collected data (price history, cost-per-use, reviews, competitor pricing) into a holistic recommendation on whether to purchase now, wait, or skip the product entirely. Provides a clear decision-support output based on multiple analytical dimensions.