Find the people asking for recommendations
Every day someone asks the internet who to hire, which tool to pick, or what to use instead. Buska watches those request phrasings across 30+ sources, scores each post from 0 to 100 for intent, and sends you the ones that match what you sell.
Updated August 2026
The recommendation-request challenge
Recommendation requests are rare and short-lived. In our study of 451,903 public posts over 60 days, only 1.4% were rated HOT, and the thirteen main B2B subreddits produced 533 of them, about nine a day for all of B2B Reddit. Miss the thread on the day it goes up and someone else has already answered.
- Requests are a trickle: 533 HOT posts across thirteen B2B subreddits in 60 days
- "Looking for", the most tracked phrase of all, carries no signal: 3.5% of HOT posts against 3.7% of the rest
- Raw searches return consumer noise: r/chinatravel produced more HOT buyers than r/smallbusiness
- Reddit and Google rank by relevance, so a question posted four hours ago sits on page three
How it works
Describe the service, not the keyword
Start from the sentence we help [who] do [what]. "Any recommendations" on its own buries you in advice threads. "Any recommendations" plus the noun for your category is the search that works.
Buska runs the request phrasings across 30+ sources
Reddit, X, LinkedIn, Quora, Hacker News, Bluesky and more, continuously. It covers the phrasings that carry signal, "any recommendations" at 2.5x lift and "best [category]" at 3x, plus switching language like "looking to switch from".
AI scores every post from 0 to 100 for intent
Only 1.4% of public posts are a real person with a real need right now. The score runs on the post itself, so you read the top of the list instead of the 7,500 posts a day our engine reads to find them.
Answer as a practitioner, then disclose
Reply while the thread is still open, give the real answer including the competitor that fits better when one does, and say plainly that you build one of the options. A ban costs more than the lead was worth.
Real signals Buska detects
“Any recommendations for a tool that tracks brand mentions on Reddit? Small team, small budget.”
“Anyone know a good B2B SEO agency? We want to start next month.”
“What are you all using for social listening now that GummySearch stopped taking new customers?”
“Looking to switch from our current monitoring tool. What is actually worth a look in 2026?”
“Best lead generation tool for a five-person startup? Budget around $100 a month.”
“Can anyone recommend a freelance developer for a two-week integration project?”
What teams get from recommendation requests with Buska
3x
lift on "best [category]" posts, measured across 451,903 public posts
2.55%
of LinkedIn posts are HOT, the densest general source in our 60-day study
0-100
intent score on every request, so you read the 1.4% that matter
Works with your stack
Slack
HubSpot
Pipedrive
Lemlist
n8nFrequently asked questions
How do I find people asking for recommendations on Reddit?
Search the request phrase with self:true and a subreddit filter, for example subreddit:smallbusiness self:true "any recommendations", then repeat it across the ten to fifteen subreddits where your buyers actually post. Reddit ranks by relevance rather than recency, so add a Google fallback (site:reddit.com/r/smallbusiness "any recommendations" with the Past week filter) or run a monitoring tool. F5Bot does the keyword part free; Buska scores each result for intent from $49/mo.
What is the best phrase to track?
"Any recommendations" and "best [your category]". In our analysis of 451,903 posts over 60 days, "any recommendations" appeared in 0.5% of HOT buying posts against 0.2% of everything else (2.5x), and "best [category]" in 0.3% against 0.1% (3x). Both are rare, which is the point: they are precise rather than high volume. The corpus is mostly English, so these lift figures describe English-language posts.
Why is "looking for" a bad signal?
Because it is not a purchase phrase. In our corpus "looking for" appeared in 3.5% of HOT posts and 3.7% of everything else, so tracking it is slightly worse than tracking nothing. The phrase is dominated by hiring posts, job seekers and people looking for collaborators. "Looking to switch from" is a different phrase and does work: switching intent was HOT 29.3% of the time, behind funding announcements at 45.1% and ahead of general shopping posts at 18%.
Why does a raw recommendation search return so much consumer noise?
Because most people asking the internet for a recommendation are not buying anything B2B. The single subreddit that produced the most HOT buyers in our 451,903-post corpus was r/chinatravel with 157, ahead of r/smallbusiness at 106, then r/personalfinance at 103, r/StudentLoans at 77, r/CleaningTips at 67, r/HomeImprovement at 55 and r/weddingdress at 47. The rule that follows: a request only becomes a lead once it is attached to a specific service. "Any recommendations?" alone is a grammar pattern, not intent.
Is there a free tool for this?
Yes, with one caveat. F5Bot emails you whenever your keyword appears on Reddit, Hacker News or Lobsters, but its free tier is personal use only and capped at 5 keywords and 20 alerts a day, so Silver at $9.99/mo is the business version. Its paid ladder runs Gold $49.99, Platinum $214.99 and Diamond from $500 (checked 5 September 2026). What does not change is the coverage: exact keyword matching on three sites (AI filtering only starts on the $49.99 Gold tier). GummySearch, which many people used for this job, stopped taking new customers on 30 November 2025 and keeps existing lifetime holders until 30 November 2026.
How many recommendation requests should I expect per week?
Far fewer than vendors imply. Across the thirteen B2B subreddits in our study, 533 HOT posts appeared in 60 days, roughly nine a day for all of B2B Reddit combined. For a single narrow category, one to five genuinely relevant requests a week is a realistic target, which is why coverage across 30+ sources matters more than depth on one. LinkedIn is worth the friction: 2.55% of LinkedIn posts were HOT, against 1.57% on Reddit, 1.54% on X and 0.36% on Hacker News and GitHub.
What do the tools for this cost?
On monthly billing, checked 5 September 2026: F5Bot $0 to $500, ReplyGuy $10 to $199 plus an Agency plan at $499, Syften $29.95 to $119.95 over 19+ sources, RedditMaster $59.99 to $79.99 (an auto-reply and karma agent, so read your subreddit rules before using it), Octolens $199 Pro and $599 Scale over 13+ sources ($159 and $499 if you pay annually), Brand24 from $249, and Buska at $49 Starter, $99 Growth and $249 Scale with a 7-day free trial and no card. The $249 and up media-monitoring tier counts brand mentions rather than finding someone asking a question today.
Can I reply with my product without getting banned?
Yes, if you answer the question first and disclose that you built one of the options. Give a real comparison, name the competitor that fits better when one does, and never post the same reply twice. Reddit's content policy and individual subreddit rules treat undisclosed promotion as spam, and account bans are permanent. On X and LinkedIn the risk is lower but the rule is the same: value first, disclosure always.