Buska is a social listening tool that finds buyers, people publicly posting that they need a product or service, across more than 30 platforms. This report is built from Buska's own engine, not a survey: every number below comes from the public posts Buska's AI actually analyzed over a 60-day window, July 4 to September 2, 2026, against the 6,538 buying-intent signals actively configured by 2,344 teams (paying and trial). Buska scores each matching post into a tier: HOT (strong buying intent), WARM (medium intent), EXPLORE, or none. This is what that scoring found at scale: how rare a real buyer actually is, which platforms carry them, which day of the week produces the most of them, and what buyer language looks like once you strip away the guesswork. Every figure is shown with the math behind it, so you can check it yourself.
The 8 findings
Only 1.4% of posts are buyers. 93% carry no buying signal at all.
Buska's engine scored 451,903 public posts against 6,538 active buying signals over a 60-day window. 6,392 of those posts were tagged HOT, strong buying intent: 6,392 / 451,903 = 1.41%. A further 24,326 were WARM, medium intent, and 420,867 carried no buying signal at all: 420,867 / 451,903 = 93.1%. Buying intent is not rare because people do not talk about their problems online. It is rare because most of what they post is not a purchase decision in progress.
What to do
If a human reads every mention before deciding what matters, that person is spending roughly 93 minutes out of every 100 on posts the engine found no buying signal in. Filter for HOT first, and let a person read second.
Reddit carries most of the volume, and even more of the buyers.
Reddit produced 312,703 of the 451,903 posts Buska analyzed, 69.2% of everything scanned. 26 sources produced posts in the window: 21 social platforms plus 5 signal feeds (funding, hiring, M&A, product, leadership). It produced 4,919 of the 6,392 HOT posts, 77.0% of every HOT-tagged post in the dataset. In other words, Reddit is not just the biggest channel by volume, it over-indexes on quality too: its share of buyers is larger than its share of posts.
Reddit carries most of the volume and most of the buyers.
Table
| 77.0% | |
| 6.0% | |
| Bluesky | 5.6% |
| X (Twitter) | 4.8% |
| 1.4% | |
| Hacker News | 0.9% |
| GitHub | 0.9% |
| YouTube | 0.5% |
What to do
If you can only afford to monitor one platform well, monitor Reddit. Treat everywhere else as a supplement, not the core of your coverage.
A LinkedIn post is 7 times more likely to be a buyer than a GitHub post.
hot-buyer rate measures what share of a platform's own posts turn out HOT, which isolates buyer density from raw volume. LinkedIn tops every real social channel at 2.55% (89 HOT out of 3,492 posts analyzed). Hacker News and GitHub sit at 0.36% each, below every major social channel except web, YouTube and Quora, which are lower still. 2.55 / 0.36 = 7.08, so LinkedIn's buyer density is roughly 7.1 times higher than either developer platform.
Density is a different story: LinkedIn posts are the most likely to be buyers.
Table
| 2.55% | |
| 1.62% | |
| 1.57% | |
| X (Twitter) | 1.54% |
| Bluesky | 1.20% |
| Hacker News | 0.36% |
| GitHub | 0.36% |
| Quora | 0.33% |
| YouTube | 0.31% |
What to do
Developer forums are excellent for product feedback and weak for pipeline. If your buyer is technical but reachable elsewhere, LinkedIn will out-produce GitHub and Hacker News on lead density, even with far fewer posts to sift through.
A company that just raised money is 32 times more likely to be a buyer than the average post.
Posts carrying funding-intent, a company announcing new capital, score a 45.1% HOT rate (123 HOT out of 273 posts), the highest of any intent category Buska tracks. The average HOT rate across all 451,903 posts analyzed is 1.4%: 45.1 / 1.4 = 32.2. Switch-intent posts, someone naming a competitor they are ready to leave, hit 29.3%; shopping-intent hits 18%; pain-intent, someone describing a problem without naming a solution, hits 21%. Pure discussion posts score 0% by construction. Funding, hiring, M&A, product and leadership items come from Buska's signal feeds (news and company events), not from social posts, so their rates are not like-for-like with the 1.4% social baseline that applies to social platforms.
Intent type is the strongest predictor of a hot buyer.
Table
| Just raised funding | 45.1% |
| Switching tools | 29.3% |
| Describing a pain | 21.0% |
| Shopping for a solution | 18.0% |
| Hiring | 7.9% |
| General discussion | 0.0% |
What to do
Track funding announcements in your ICP as a buying trigger, not a news item. At a 32x multiplier over baseline, it deserves its own alert, not a line buried in a general feed.
Wednesday is the best day to find a buyer, Sunday the worst.
Dividing HOT posts by all posts for each day of the week turns raw counts into an actual rate, which matters because posting volume itself swings by day. Wednesday peaks at 1.91% (1,133 HOT out of 59,467 posts). Sunday is the floor at 1.20% (720 out of 60,040), with Saturday and Monday close behind, both at 1.24% (701 out of 56,683 for Saturday, 918 out of 73,795 for Monday): all three roughly 1.5 to 1.6 times lower than Wednesday's rate. Posts without a publication date, 29,497 posts, 6.5% of the total, including 66 HOT posts, are excluded from these weekday rates.
Midweek posts are more likely to be buyers than weekend posts.
Table
| Sun | 1.20% |
| Mon | 1.24% |
| Tue | 1.67% |
| Wed | 1.91% |
| Thu | 1.65% |
| Fri | 1.64% |
| Sat | 1.24% |
What to do
Weight midweek monitoring and outreach review more heavily. A post published on a Sunday is less likely to be a buyer than one published on a Wednesday.
Buyers write in the first person and ask questions. They rarely say 'looking for.'
HOT posts use first-person language, I, we, my, in 65.1% of cases versus 53.5% for everything else (WARM, EXPLORE and no-signal posts combined), and phrase themselves as a question 40.2% of the time versus 30.6%. Budget gets mentioned in 5.9% of HOT posts versus 4.3% elsewhere. The counter-intuitive result: 'looking for' shows up in 3.5% of HOT posts versus 3.7% of the rest, marginally less common among real buyers, not more. What does hold up: 'any recommendations' (0.5% HOT versus 0.2% other) and 'best X' (0.3% versus 0.1%) are roughly 2 to 3 times as dense among HOT posts, on rounded figures, both rare phrases individually but strong signals whenever they appear.
What to do
Stop treating 'looking for' as your keyword anchor, it barely separates buyers from browsers. Weight recommendation-seeking and comparison phrasing instead, and combine them with first-person and question framing rather than any single phrase alone.
B2B buyers cluster in a specific, recognizable set of subreddits.
Among the top 40 subreddits ranked by HOT-post volume, thirteen subreddits we classify as B2B together account for 533 HOT posts: r/smallbusiness (106), r/DigitalMarketing (81), r/SEO (70), r/GrowthHacking (44), r/marketing (34), r/webdev (34), r/startups (31), r/SaaS (29), r/AI_Agents (24), r/aeo (22), r/digital_marketing (22), r/AskMarketing (18) and r/ecommerce (18). In the interest of an honest picture, the same top-40 list also includes clearly consumer communities, r/chinatravel (157), r/personalfinance (103), r/weddingdress (47) among them: Buska tracks whatever signals a customer configures, and a meaningful share of Buska's own customers sell to consumers, not businesses.
Communities where Buska customers' B2B buyers surfaced most often.
Table
| r/smallbusiness | 106 |
| r/DigitalMarketing | 81 |
| r/SEO | 70 |
| r/GrowthHacking | 44 |
| r/marketing | 34 |
| r/webdev | 34 |
| r/startups | 31 |
| r/SaaS | 29 |
| r/AI_Agents | 24 |
| r/digital_marketing | 22 |
| r/aeo | 22 |
| r/AskMarketing | 18 |
| r/ecommerce | 18 |
What to do
If you sell B2B, treat these thirteen subreddits as your starting watchlist before you configure anything more exotic. They are where the buyers in this dataset already are.
The dataset behind this report: 451,903 public posts scored in 60 days, across 25+ platforms.
This report covers 60 days of Buska's engine activity: 451,903 public posts scored in a window ending 2 September 2026 07:05 UTC (a rolling window filtered on ingestion date, so both edge days are partial), against 6,538 buying signals actively configured by 2,344 teams (paying and trial); signal and team counts are a snapshot at generation time. That works out to 451,903 / 60 = 7,532 posts scored per day.
What to do
Every rate in this report is built on thousands of independently configured signals, not a handful of hand-picked examples. The volume is large, but sub-1% phrase rates, like GitHub's 0.36%, remain estimates: no confidence interval has been computed here.
Methodology and limits
This report comes entirely from Buska's own engine logs, not a survey or a panel. Every post counted here is a public post that matched at least one of the 6,538 buying-intent signals actively configured by Buska's 2,344 teams (paying and trial) across 30+ platforms, then classified by Buska's AI into a tier: HOT (strong buying intent), WARM (medium intent), EXPLORE (a smaller exploratory tier), or none (no buying intent detected). Three limits follow directly from that design. First, the dataset is skewed toward what Buska's existing customers sell and watch: it is not a random sample of the internet, it is a sample of the markets and platforms real companies are already monitoring. Second, the corpus is, by our estimate, mostly English, since most active signals today are configured in English; the dataset has no language field, so this cannot be verified directly. Third, HOT and WARM are Buska's own AI classification, the same tiers a customer sees live in their dashboard, not a separate human-reviewed research standard. Publication dates in the underlying data are stored at day-level precision, so this report cannot break volume or hot rate down by hour of day. The window analyzed covers 60 days ending 2 September 2026 07:05 UTC (a rolling window filtered on ingestion date, so both edge days are partial); signal and team counts are a snapshot at generation time.
How to cite this study
How to cite: Buska, 'The State of Buying Intent on Social, 2026', buska.io/research/state-of-buying-intent-2026
Download the aggregated data (JSON, CC BY 4.0)Frequently asked questions
What percentage of social media posts show real buying intent?
Across 451,903 public posts Buska's engine analyzed over a 60-day window, only 1.4% (6,392 posts) showed strong buying intent, Buska's HOT tier. A further 5.4% (24,326 posts) showed medium intent, the WARM tier. The remaining 93.1% (420,867 posts) were pure discussion with no buying signal detected at all.
Which social platform produces the most buyers?
Reddit, by a wide margin. It accounted for 69.2% of all 451,903 posts Buska analyzed and, more importantly, 77.0% of every post tagged with strong buying intent, more HOT buyers than every other platform in the dataset combined.
Which platform has the highest concentration of buyers, not just the highest volume?
LinkedIn. 2.55% of the LinkedIn posts Buska analyzed were tagged HOT, the highest buyer density of any social platform measured, about 7.1 times higher than Hacker News or GitHub, which sit at 0.36% each, below every major social channel except web, YouTube and Quora, which are lower still.
Does a company's funding announcement predict it is about to buy?
Not exactly: it is the strongest HOT-rate signal of any intent category Buska measures, rather than a prediction. Posts about a company raising new funding hit a 45.1% HOT rate, versus 1.4% for the average post analyzed, making a funding announcement roughly 32 times more likely to be tagged HOT than a random post. Funding items come from Buska's signal feeds (news and company events), not from social posts, so this rate is not like-for-like with the 1.4% social baseline.