SnitchFeed vs Awario

Awario is a long-running, well-built social listening tool and on annual billing it costs less than we do, so this is not a page about price. Both tools give you boolean queries. The differences that decide it are what happens after the query runs, and which platforms it can run against: Awario returns matches, SnitchFeed scores them for relevance and intent, and Awario cannot see LinkedIn at all.

Awario discounts steeply on annual billing, so both axes are shown. They are cheaper than us on the annual comparison at both tiers, and the table is arranged so you can see it.

All of this is true. If any of it is a requirement rather than a preference, buy Awario.

• Cheaper than us on annual billing, at both tiers

  $29 a month against our $47, and $89 against our $95. Their annual discount is steeper than ours, so on the axis we normally compare by, they win.

• A longer track record on complex queries

  Boolean search is their signature feature and they have been refining it for years. If you already have query strings you trust and want to bring them across largely unchanged, that maturity is worth something.

• Volume, stated plainly

  30,000 new mentions a month on the entry tier with 5,000 stored per topic, rising to a million on Enterprise. Clear numbers, no credit model to reason about.

• White-label reports and 10 seats at $89

  Reporting features aimed at agencies, on every tier including the cheapest, and ten team members where our Pro allows five.

The cases where we would tell you to pick us.

• LinkedIn, Bluesky and Hacker News

  None of the three are on Awario's platform list. For a B2B team, LinkedIn alone usually settles this: it is where buying committees talk about software, and Awario cannot see it.

• Scoring on top of the query, not instead of it

  You get the same boolean building blocks, and then every match is scored for relevance and intent. A query tells you something matched. It cannot tell you whether the person is asking for a recommendation, complaining, or mentioning you in passing. That second layer is what turns 30,000 monthly matches into a queue somebody actually works.

• The query does not have to carry all the precision

  Because scoring ranks what comes back, a broader query stays usable. Products get nicknamed, competitors launch and slang drifts, and with Awario a string that was precise in January quietly stops matching in June, with nothing to catch it. Here the scoring absorbs some of that drift.

• Built for acting, not reporting

  Awario's shape is dashboards and scheduled reports, which suits agencies reporting to clients. Ours is alerts into Slack and Discord, shared feeds and reply drafting, which suits a team responding to what it finds.