Listener Intent

SnitchFeed scores matches with AI based on intent: what you are trying to find (and what should be ignored). The clearer your instructions, the less noise—fewer job posts, promos, and off-topic threads—and the more actionable your feed and alerts.

This page uses the same running example as Keywords to track: you sell a Notion competitor and want people complaining about Notion or asking for alternatives—so you can join the thread while intent is high.

Intent and Negative Intent

In the listener dialog you’ll see two fields that work together:

Intent

Intent is a short, plain-language brief of the posts you want this listener to surface. It:

• steers relevance scoring so keyword hits that match your goal rank higher, and
• powers keyword suggestions when you click generate (the model needs a strong Intent to be useful).

Be sure to be as descriptive as possible.

Example (Notion competitor)

I want posts from startup founders, ops leads, and marketers who are frustrated with Notion or shopping for a replacement: complaints about sync, mobile, permissions, billing, or enterprise limits; threads asking what to use instead of Notion; and comparisons with other docs or wiki tools. Prioritize switching intent and real workflow pain—not influencer aesthetic drops or template giveaways unless someone is clearly evaluating tools.

Write in first person or imperative (“I want…”, “Find…”), name who (roles), what situations (complaints, comparisons, migrations), and what to prioritize vs skip. Vague intents (“anything about productivity”) produce vague scores and weak keyword suggestions.

Negative intent

Negative intent is optional but recommended. Describe what should score as low relevance: threads that technically match your keywords but are not worth your time.

Quick patterns many teams exclude: job listings, affiliate or promo spam, student homework, generic tutorials when you only want buyer conversations, or industries that noise up a broad keyword.

Negative intent is capped at a smaller character limit than Intent—keep it punchy and update it when you notice recurring junk patterns.

Example (Notion competitor)

Job listings and recruiting (including at Notion or unrelated roles); Notion template sellers, marketplace spam, and affiliate link dumps; pure fan posts with no complaint or purchase angle; student homework and shallow tutorials; giveaways and growth hacks with no evaluation; crypto, NFT, or unrelated hustle threads; generic motivational posts with no mention of tools, switching, or problems with Notion.

List categories of junk you keep seeing in the feed so SnitchFeed learns to score them down—even when keywords still match.

Listener-specific intent

Intent and Negative intent are listener-specific: you set them in each listener’s create/edit dialog (Create listener). Different listeners can target different competitors or motions while sharing the same workspace Brand Context.

Together, Intent + Negative intent narrow the gap between “matched keywords” and “matches worth replying to.” When you change either field, SnitchFeed may re-score recent mentions so the feed reflects the new guidance.

For workspace-wide company facts (who you are, what you sell), keep Brand Context accurate—listener Intent still tells the model what to listen for.