Reddit is the best public source of buying intent that exists, for one reason: it is where people go before they know what the category is called. They describe a problem in their own words, to strangers, with no vendor listening, which is exactly what makes the description honest and exactly what makes it hard to match on keywords.
We're a 30-person agency and our client onboarding is completely out of control. Everything is in email threads, nothing is tracked, and I spent my whole Tuesday chasing three people for one document. What is everyone using?
If you sell onboarding software, that is the best lead you will see this month. It contains your brand name zero times, your competitor's name zero times, and your product category zero times.
Why keyword tools miss the good threads
A keyword alert on Reddit returns two kinds of result: posts containing your brand, and posts containing terms you guessed in advance. The first is small and mostly support requests. The second is where the volume goes, and it is where the noise lives: you are asked to predict, up front, the vocabulary of a person who does not yet know your category exists.
Openpulse inverts the input. You paste your website; it crawls your landing, product, pricing and about pages and proposes the whole plan (keywords, exclusions, per-source queries) for you to edit before anything runs.
Then the important part: the off-topic gate is soft. A candidate that shares no keyword with your plan is handed to a reranker rather than dropped, because "drowning in back-and-forth emails" shares no word with "client onboarding software" and is precisely the signal worth having. Every signal records passedBy: "keyword" | "rerank", so you can measure what a hard keyword gate would have cost you. Most tools in this category are the hard gate and have no way to know.
Full post text, and the comments
Reddit is one of only two sources Openpulse reads as full text: the whole post body, its author, its score and its comment count, rather than a 268-character search snippet. That matters more than any platform count: a model judging a snippet is the single biggest driver of bad labels anywhere in this category.
Two Reddit-specific capabilities the other modes do not pay for:
- Comment search.
filter=commentson the same query. This is where the other half of Reddit lives: the half where somebody names a vendor and says what went wrong. The complaint is almost always a comment under "what does everyone use for X?", never the question itself. - Thread expansion. A thread with 8+ replies becomes a container and a second call fetches what is inside it. Capped at three containers per query, because expansion is the one stage whose cost is multiplicative.
Full-text coverage depends on a social-data vendor key. Without it the badge in the wizard downgrades automatically to snippet and says so, rather than quietly degrading and leaving you to work it out from a run of bad labels.
What survives, and what does not
Every gate below runs before any model call, so filler is rejected for free:
- Page shape: a
site:search returns whatever is indexed for a domain, which is mostly not conversations. Only real post URLs (/comments/) are kept. - Off-topic: stemmed token match against your plan, soft when reranking is on.
- Exclusions: your
excludeKeywords, also pushed to the search engine as negations. - Recency: bounded by the listener's data window, six hours to thirty days.
- Duplicates: normalised URL and title, within a run and against what is already stored.
Then a reranker scores what is left against your intent and only the top 25 reach the classifier. On a reference listener that took a run from 102 classification calls to 37 while doubling the search results pulled.
Everything rejected is kept for 14 days with its reason. Without them, precision has no denominator.
Reading the result
Each signal carries an intent label (high_intent, evaluating, relevant shown by default, with competitor, content and noise filed behind tabs), a 0–100 score, the query that found it, the keywords genuinely present in the text (computed from the post, not supplied by the model), and one line on how to reply.
It also records inferenceHops: 0 if they said it, 1 if the connection was one step away. If your team is not ready for derived leads, filter to 0.
Replying without burning the thread
Reddit punishes marketing, and correctly. The action for a Reddit signal is a reply in the thread, not an email: the person is already there, already asking, and a helpful answer from someone who obviously read the post is the only thing that works.
Openpulse drafts that message: three channels and three tones, written from what the person actually said. No placeholders (a [Name] in a draft is a [Name] in a sent message), no invented facts, no claimed case studies, and none of the openers that announce themselves as generated.
There is no send button and there will not be one. Copy is the only exit. The product's claim is that it finds people worth talking to; the moment outreach can go out unread, signal quality stops mattering because every reply is to something nobody checked. On Reddit specifically, an automated reply is how an account gets banned and a brand gets a thread of its own.
The honest limits
No contact enrichment, by design. A Reddit username is pseudonymous. There is no legitimate route from u/throwaway_dentist to a verified work email, and products claiming one are inheriting the provenance of an identity graph you would not enjoy being audited on. The thread is the channel.
Volume is not the metric. A well-tuned Reddit listener produces tens of qualified conversations a month, not thousands. If you are shopping for mention volume, buy something metered per mention: it will be cheaper and better at it.
Nothing is real-time. Hourly at the fastest, on Pro. A thread stays live for days, so this is rarely the binding constraint.