Buying Intent Signals on Social Media: How to Find People Ready to Buy
People announce they are shopping for tools like yours every day in public threads. Here is how to recognize real buying intent signals, rank them and respond like a human.
Bhargab KalitaFounder of Xoru··6 min read
Somebody on Reddit wrote "is there anything cheaper than [your competitor]?" about an hour ago. Another person on X asked their followers what tool they use for the exact job your product does. These are buying intent signals, and for a small SaaS with no ad budget they are the warmest leads you will ever get. The hard part is seeing them in time and answering in a way that does not feel like a pitch.
I used to treat social media as a place to broadcast. Post, hope, repeat. It took me far too long to notice that buyers were already describing their problems in public, in detail, every day. I just was not listening. This guide covers what to look for, how to rank what you find and how to reply.
What are buying intent signals?
Buying intent signals are public or behavioral cues that show a person is actively looking for, comparing or about to purchase a solution.
In sales teams the term usually covers things like pricing page visits, demo requests and hiring patterns. On social media it is simpler and more direct. People literally write down what they want. "Looking for a tool that does X." "Fed up with Y, what are the alternatives?" "Has anyone used Z for a team of three?"
The value is timing. A cold message interrupts someone. A reply to a person who just asked for help is a response. Same product, completely different reception.
What are examples of buying signals on social media?
The clearest examples are direct requests for recommendations, complaints about a current tool and questions comparing specific products.
Not all signals carry the same weight. Here is how I rank them:
Signal
Example phrasing
Intent strength
Best response
Direct recommendation request
"What tool do you use for X?"
High
Answer with options, mention yours if it fits
Competitor frustration
"Thinking of leaving [competitor], it keeps breaking"
High
Ask what broke, suggest fixes and alternatives
Alternative search
"Cheaper alternative to [competitor]?"
High
Honest comparison, including who the competitor suits
Head-to-head comparison
"[Tool A] vs [Tool B] for a small team?"
Medium to high
Share criteria, not just a verdict
Workflow pain
"I spend hours every week doing X by hand"
Medium
Explain a manual fix first, then a shortcut
General interest
Liking a post about your category
Low
Do nothing. Not a lead yet
The top three rows are where most early customers come from. The bottom row is where most "social selling" advice wastes your time.
How do you identify buying signals in real conversations?
You identify buying signals by searching for problem and comparison phrases instead of your brand name, then filtering for recent posts from real people.
Nobody is searching for your brand yet. They are searching for their problem. So build your watch list around three kinds of phrases:
Problem phrases. The plain words someone uses to describe the pain your product solves, without knowing your product exists.
Competitor phrases. Competitor names paired with "alternative", "vs", "expensive", "down", "switching" or "cancel".
Request phrases. "looking for", "recommend", "any tool", "what do you use for".
Then filter hard. Skip posts older than a few days unless they rank on Google. Skip vendors fishing for leads. Skip threads in communities that ban any product mention. For the mechanics of keyword tracking on Reddit specifically, see how to monitor Reddit for keywords.
Channel intelligence filters thousands of posts down to the few where someone is actually asking for help.
Where buying signals show up by platform
Each platform leaks intent in a different way.
Reddit. Long, honest posts with full context. Strong for "alternatives" and "what do you use" threads. Subreddit rules vary a lot.
X. Short public asks to followers, plus loud complaints about tools that just failed someone. Speed matters most here.
LinkedIn. Polished posts asking peers for recommendations, often from people with buying authority.
Hacker News. Technical "Ask HN" threads where people want depth and dislike marketing tone.
First-party vs third-party intent data
First-party intent data comes from your own channels, while third-party intent data comes from activity elsewhere, and social conversations are the most readable form of the second kind.
First-party signals are things like pricing page visits and trial signups. They only exist once someone has already found you. Third-party signals tell you who is shopping before they know you exist. Traditional third-party intent data is inferred from browsing patterns and sold by data vendors. Public social posts are different. You can read the actual words. No guessing about whether a company is "surging" on a topic. The person wrote down what they need.
For a small team, that makes public conversations the most practical third-party intent source there is. You do not need a data contract. You need a good watch list and the discipline to check it.
How fast should you respond to a buying signal?
Respond within hours when you can, because public threads move fast and early helpful answers get the most visibility.
On X, a post can go quiet within the same day. On Reddit, the first few thoughtful comments tend to collect upvotes and stay near the top. Late answers still help, especially in threads that rank on Google, but speed improves your odds of being read.
Speed should never cost quality, though. A rushed, generic reply is worse than no reply. This is the tension every intent-based lead generation workflow has to solve.
How to reply to a buying signal without spamming
Reply as a practitioner first: answer the question fully, then mention your product briefly and disclose that you built it.
A structure that works on every platform:
Answer the actual question in the first line.
Add one specific detail that shows you understand the problem.
Offer a couple of options, including ones that are not yours.
Mention your tool in one sentence, with disclosure.
Stop. No calls to action, no "DM me".
Software can find the signal. A human should decide what to say back. That is the difference between being helpful and being one more bot in the thread.
This is the part where automation tempts people. Auto-replies at scale feel efficient until accounts get flagged and communities start recognizing the pattern. We explain why in AI-drafted, human-approved, and the practical side of doing this on Reddit is in how to find customers on Reddit without spam.
Drafts match your tone. You approve each one, so nothing posts without you.
Measuring which signals turn into customers
Track replies down to signups, because some signal types and communities convert far better than others.
Log each reply with its platform, signal type and thread link. After a month, look at which rows produced trials and paying users. You will likely find that one or two communities and one signal type carry most of the results. Put more of your time there. Our post on which posts actually bring users walks through the setup.
Where Xoru fits
Xoru watches for buying intent signals across Reddit, X, Hacker News and LinkedIn, and drafts replies you approve before anything goes live.
It surfaces relevant conversations so the direct requests and competitor frustrations rise to the top, writes a draft in your voice and waits for your approval. Your accounts stay at much lower risk of platform flags. Your replies stay human. And every helpful answer becomes part of the public discussion that AI engines like ChatGPT and Perplexity read later. Learn more on the AI social listening page, see how it compares with Syften, or check pricing.
Start small. Write down five phrases your buyers use when they are stuck. Search them today. Someone is asking right now.
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