Social listening

Social listening is an automation that watches what people say about your brand, product, and category across social platforms, Reddit, review sites, and forums, then sorts every mention by theme and sentiment and flags the ones that need a human. It catches the conversations that never tag you directly, which is most of them, and delivers a short digest plus real-time alerts for the urgent items: a complaint gaining traction, a buying signal, a factual error spreading. It does the watching and sorting a person would do by hand, on a schedule. A human decides how to respond.

Native notifications only fire when someone tags or @-mentions you, so they miss the untagged conversations where most of the candid talk happens, and they arrive as a raw pile with no sorting. Competitive monitoring is a sibling automation that watches your named competitors' moves, their pricing, product, and hiring. Social listening points the other way: it watches what people say about you and your category, sorted by sentiment, so complaints and buying signals surface fast. Many companies run both. This one is scoped to your brand, tuned to your definition of what matters, and delivers where your team already works.

Good enough to trust for triage, and honest about its limits. Sentiment is hard: sarcasm, slang, and context fool naive tools, so a raw sentiment score alone will get some calls wrong. That is exactly why the setup spends the first few weeks tuning against your real mentions until the sorting matches how you would read them, and why every item links back to the source so you can check it in one click. The system is set to flag uncertainty rather than guess, and to push borderline urgent items to a human instead of burying them. You are reviewing a sorted feed with receipts, not trusting a black box.

Yes, always. The automation finds, sorts, and flags. It does not post replies, comment, or message anyone on your behalf. When a complaint or buying signal surfaces, it lands in front of the right person with the context and a link to the source, and that person decides whether and how to respond. That line is deliberate. A public reply in your brand's voice is a judgment call, and getting it wrong in front of an audience is worse than being a little slower. The automation buys back the time and the speed of noticing. The response stays human.

On the source side, the major social platforms such as X, Reddit, LinkedIn, Instagram, Facebook, and YouTube, plus review sites like G2, Trustpilot, Google reviews, and app store reviews, and specific industry forums where your buyers gather. On the delivery side, Slack, email, and your CRM such as Attio, so the digest and alerts land where your team already works. Most sources with a public feed or an API can be added. The audit maps your exact stack and picks the sources where your customers actually talk about you.

Usually one to two weeks. The first days go to naming what to watch, your brand and product terms, the people your buyers name, category and competitor keywords, and the sources that matter, then defining what counts as urgent. After that the listening and sorting run against your real mentions for a week or two so the sentiment calls and escalation rules get tuned before anyone relies on the digest. You are live quickly, and the tuning window is what makes the feed worth reading instead of another alert stream to mute.

Two parts. Tooling runs as a monthly cost for the mention data and model usage, typically a range that scales with how many sources and how much volume you track. Implementation is a fixed scope, quoted once the audit maps your sources, keywords, sorting rules, and delivery setup, so you are pricing a defined build rather than an open-ended retainer. The audit itself is where the scope and price get set against every other opportunity in your business, so you are not guessing at effort up front.