Boolean search for listener queries: tighter monitoring, less noise

Flat keyword lists are fine until your feed fills with job posts, template spam, and threads that technically mention your brand but are not worth replying to.

Today we are rolling out boolean search for listener queries. Instead of a single list of included and excluded keywords, you build structured queries with AND, OR, and NOT logic, tune match behavior per term, and choose which platforms each query runs on.

What changed

Open any listener and go to Keywords. Each term in the left sidebar is its own boolean query:

• Main term: the anchor phrase you are monitoring
• Must also include: AND terms that must appear alongside the main term
• Must mention at least one of: OR terms where at least one must appear
• Ignore posts mentioning: NOT terms that drop posts before scoring

Each AND/OR chip can be Exact (tighter) or Broad (more volume). Whole word and Case sensitive apply to the main term.

You can also expand Raw Boolean Query and edit the compiled string directly. The builder stays in sync.

Why this matters

Social listening breaks when monitoring is either too broad or too brittle.

Boolean queries let you stay broad on the brand (notion) while requiring intent language (alternative, frustrated, switching) and filtering predictable junk (hiring, template for sale) in the same query.

You also get per-term platforms. Run one query on X and LinkedIn for buyer-intent phrases, and another on Reddit for community complaints, without duplicating the whole listener.

Example: monitoring a Notion competitor

Say you want threads where people complain about Notion or ask for alternatives.

Query 1: switching intent

• Main term: notion
• Must mention at least one of: alternative, replacement, switching
• Ignore posts mentioning: hiring, template for sale, affiliate
• Platforms: X, LinkedIn

Query 2: complaint language

• Main term: notion
• Must also include: frustrated, slow, broken
• Ignore posts mentioning: tutorial, giveaway
• Platforms: Reddit

Pair this with a strong Intent signal so Fit Score favors evaluation and pain, not generic product chatter.

LinkedIn and X search settings

Each term has its own Search settings when those platforms are enabled.

LinkedIn

• Author job title: focus on roles you care about (for example CEO, Head of Marketing, Founder)
• Author company: narrow to people at target companies
• Post type: person, company, or any

X

• Minimum likes: skip low-engagement posts
• Language: limit results to a specific language

These filters sit on top of your boolean logic, so scheduled scans stay closer to the conversations you actually want to join.

Generate Keywords

If you already filled in Intent signal, click Generate Keywords. SnitchFeed suggests boolean queries from your intent, brand context, and noisy signals. Review the table, add the ones that fit, and tweak in the builder.

Get started

1. Open a listener (or create one).
2. Go to Keywords and select a term, or click Add term.
3. Start with one strong main term. Add AND/OR refinements only when you need them.
4. Turn on the right platforms per term.
5. Save and watch the feed.

Docs: Boolean search queries · Create listener · Keywords to track

Questions or feedback? Reach out via in-app chat.