Relevance Threshold
Relevance threshold is the minimum AI relevance score a Reddit match must reach to appear in the digest — the user-tunable cutoff between "send to me" and "filter out."
Relevance threshold is the minimum AI relevance score a Reddit match must reach to appear in the digest — the user-tunable cutoff between "send to me" and "filter out." In a 1-10 scoring system, a threshold of 6 means matches scored 6+ are surfaced and matches scored 5 or below are suppressed.
The right threshold depends on how the user wants to use the tool. A founder who wants only the strongest buyer-intent leads might set a threshold of 8, accepting that they'll see fewer matches but every one will be worth a careful reply. A marketer doing broader research and wanting to spot emerging trends might set a threshold of 5, accepting more noise in exchange for fuller category visibility.
The threshold also interacts with the volume of incoming matches. A user with broad keywords and many subscribed subreddits might generate hundreds of raw matches per week; a high threshold (8+) brings the digest down to a readable size. A user with narrow keywords might generate only 10-20 raw matches per week; a low threshold (4+) makes sure they see almost everything.
RedNudge defaults the threshold to a middle value (typically 6) on signup and lets users adjust it from settings. The dismissal pattern naturally informs threshold-tuning too: if a user is dismissing nearly everything at the current threshold, raising it produces a tighter digest; if they're acting on most low-scored matches, lowering it might surface more relevant content the AI is underweighting.
A related concept is per-keyword thresholds: some keywords (your brand name) might deserve a low threshold because you want to see everything, while broader category keywords might benefit from a high threshold to keep noise out. Whether a tool supports per-keyword thresholds is one of the differentiators between basic and advanced monitoring setups.
Related terms
- AI Relevance Scoring — AI relevance scoring is the use of a language model (like Claude or GPT) to read each Reddit match and assign a numeric score indicating how well it fits the user's product or research target.
- Dismiss-to-Train — Dismiss-to-train is the pattern where a user dismissing an irrelevant match in a monitoring tool teaches the underlying scoring system to filter out similar matches in the future.
- Signal vs. Noise — Signal vs. noise is the ratio of useful, actionable matches to total matches in any monitoring system — the central quality metric for Reddit keyword monitoring.
- Intent Tagging — Intent tagging is the practice of classifying each Reddit match by the type of intent expressed — buying, asking, complaining, comparing, or generic mention — so users can prioritize replies and research.