Use case

Nothing posted at your brand goes unanswered in public

Automated social media responses are how you make sure nothing posted at your brand — a comment, a DM, a tag in someone else's post — goes unanswered, no matter which platform it landed on or what time it arrived. Handled manually, that means someone checking four or five different apps in rotation, hoping nothing slips through while they're logged into the other three. A custom AI agent watches every channel at once, works out what actually needs a reply, and either answers straight from real data or drafts a reply for a person to approve before it goes out.

· Reviewed by Artur Horimoto, Founder & CEO

The job: nothing goes unanswered, in public

Every other support channel has a wall around it. An email sits in an inbox only your team can see. A phone call is between two people. A support ticket lives inside a system the customer has to log into to check on. Social media has no wall. A complaint posted under your brand's own content, or sent as a DM that someone later screenshots, is visible to anyone scrolling past — including the prospect who was about to buy and stops to read the replies first.

That visibility cuts both ways. Answer well, fast, and in a tone that sounds like a person who cares, and it reads as proof the brand is paying attention. Say nothing for a couple of days, or answer with something that reads like it was pasted from a script, and the silence itself becomes the story — screenshotted and shared long after the original comment would have been forgotten. The job isn't to win every exchange. It's to make sure nothing addressed to the brand, wherever it was said in public, sits unanswered long enough to become its own problem.

For an ecommerce brand this shows up constantly: a shipping complaint under an ad, a sizing question in a DM, a tagged photo with a caption that could go either way depending on how fast someone responds. None of it is a support ticket in the traditional sense. All of it is public the moment it's posted.

The manual way vs. the automated way

The manual version usually falls to whoever on the team has social access and a few free minutes — a marketing coordinator checking notifications between other jobs, or a founder doing it personally because nobody else has the login. Comments get triaged by whoever happens to open the app first. DMs pile up in a separate inbox nobody checks as often as the main feed. A genuinely urgent complaint can sit next to a spam comment for the same stretch of time, because nothing is sorting one from the other.

The automated version starts by pulling every channel into a single queue the moment something arrives — a comment on a post, a DM, a mention, a reply to a story — so nobody has to remember to check five apps in rotation. From there the job is judgment: what needs an answer, what's noise, what can be answered immediately from data the business already has, and what has to reach a person before anything is posted back in the brand's name.

Manual Automated
Coverage Whichever platform someone remembers to check Every channel pulled into one queue
Response time Depends on who's free and when Read and sorted the moment it lands
Consistency Depends on who's answering that day The same read on urgency and tone, every time
Routine questions Answered from memory, or not answered at all Answered from real order, account, or product data
Anything risky Posted straight to the brand's public feed Drafted, held for a person to approve

How a build actually works

Pulling every channel into one queue

The first job is consolidation. Comments, DMs, mentions, and story replies from every platform the brand is active on get read into a single place, tagged with which platform and which post or thread they belong to. Nobody has to remember that DMs live in a different app than comments, or that a mention needs a different check than a direct message. One queue, everything in it, nothing waiting on someone to open the right app.

Separating what needs a reply from noise

Not everything that lands needs a response. A generic "nice" under a product photo doesn't. A bot account spamming the same comment across ten posts doesn't. A genuine question, a complaint, or a comment from someone who's clearly a real customer does. The system reads each item for what it actually is before deciding whether it needs a reply at all — the fastest way to bury a real complaint is to answer it with the same priority as a spam comment sitting next to it.

Answering the routine questions, from real data

Most of what does need a reply is routine — a shipping timeline, a sizing question, whether a product is back in stock, whether the brand ships to a particular country. A canned response that ignores the specific order or account behind the question reads as exactly what it is, and customers notice. A system connected to the actual order, account, or product data answers with the real answer, not a general one, and does it as fast in a public comment thread as in a private message.

Catching the complaint that needs a human, fast

Some messages aren't routine no matter how they're worded — a customer who's genuinely angry, a safety concern, anything with legal weight, a complaint that's already picking up replies from other people. Those need a person, quickly, not a polished reply that makes the brand look like it wasn't really listening. The system's job here is recognition: read the tone and the stakes, not just the words, and route anything past a certain threshold straight to a human with the full thread attached rather than leaving it in the same queue as a sizing question.

Draft-and-approve: the boundary we hold firm on

A public reply written in the brand's voice carries a kind of risk a support ticket never does. A ticket is a conversation between the business and one customer. A public reply is a statement the whole audience reads, screenshots, and can quote back later. That's why the sensible default on anything past the plainly routine is draft-and-approve rather than auto-post: the system writes the reply, a person reads it once, and only then does it go out under the brand's name. Human-in-the-loop is the general term for that pattern, and on a public channel it isn't optional — it's the point of the whole design.

The other rule we hold to without exception: the system never argues. Not with a customer who's wrong, not with someone clearly trying to bait a reaction, not with a competitor's plant in the comments. A reply either resolves what the person actually needs or it says nothing and routes to a human instead. Arguing in public has never once made a brand look better, and a system built to always have the last word is a system built to eventually have the wrong one.

What it connects to

A system like this is only useful if it reaches into what the business already runs:

  • Every platform the brand is active on, reading comments, DMs, mentions, and story replies into one place rather than checked app by app.
  • Order, account, or product data, so a routine question gets the real answer instead of a general one. For an ecommerce brand that usually means the order management and inventory systems directly.
  • Wherever the team already works — a shared inbox or a team channel — so a flagged complaint reaches a person fast, the same way email triage routes an urgent message instead of leaving it in a shared inbox nobody's watching.
  • Written brand voice guidelines, so a drafted reply sounds like the brand wrote it, not like a template borrowed from somewhere else.

None of this requires replacing the tools the team already uses to manage social accounts. It sits alongside them, reading what arrives and either answering it directly or handing it to a person with the context already attached.

Frequently asked questions

Will it ever reply publicly without a person checking first?

Only for the plainly routine — a shipping question answered from order data, a store-hours question, that kind of thing. Anything carrying brand risk, including a complaint or a clearly upset customer, gets drafted and held for a person to approve before it posts. That boundary is deliberate, not a limitation we're trying to remove.

How does it handle comments and DMs across different platforms?

It reads every channel the brand is active on and pulls everything into one queue, so nothing depends on someone remembering to check a specific app. What needs a reply is sorted from what doesn't, and each item is handled according to how urgent or risky it is, not which platform it happened to arrive on.

How does it recognise a complaint that needs to reach a person fast?

The same reading of tone and intent that sorts routine questions from noise also flags anger, urgency, or anything with legal or reputational weight — the kind of read sentiment analysis is built for. Flagged items go straight to a person with the original message and context attached, rather than waiting in the same queue as everything else.

How long does a build like this take to go live?

Most social response systems are live within weeks. We usually start with one or two platforms and the most common routine questions, then expand into more channels and more of the response logic once the first piece is proven against real messages.

What does it cost?

It depends on how many platforms it needs to read, how much of the routine-answer logic it has to own, and how deep the connection into your order or account systems goes. Every engagement gets a clear price agreed before any build work starts.

Bring us the platforms your brand is actually active on and what's currently slipping through. In a free 30-minute strategy call we'll tell you honestly what's worth automating and what still needs a person.

Automate this job

Walk us through how it works today. We will map the build and give you a clear price before anything starts.

Free 30 minutes. No pitch deck. You leave with a plan either way.