No social platform has ever published an average organic reach figure. Not a benchmark, not a distribution, not a percentage. Searching the documentation, help centres, transparency reports, newsrooms and developer documentation of the three platforms that matter for B2B returns nothing of the kind.

Every organic reach number in circulation therefore comes from somewhere else: commercial analytics vendors measuring the accounts of their own customers, which is a sample of people who buy analytics software rather than a sample of anything.

That would be a manageable problem if the underlying metrics were comparable. They are not, and the reason is specific enough to settle the argument permanently.

Scope of the search for a published organic reach figure and its outcomeThe scope of the search conducted for a published organic reach figure and the outcome of that search across the three platforms relevant to business to business marketing. For the professional network, the search covered its help centre pages on page analytics, post analytics, creator analytics and feed ranking, its marketing solutions and sales solutions business pages, its engineering blog and its official member blog. For the social network group, the search covered its transparency centre including the pages on ranking and content, explaining ranking and approach to ranking, its widely viewed content report, its corporate newsroom, its business news pages, its business help centre, its general help centre, its developer blog and page insights application programming interface documentation, and its creators site. For the third platform, the search covered its business help centre and advertising glossary, its general help centre, its application programming interface metrics documentation, and its corporate blog. No platform publishes an average organic reach figure, a reach benchmark, or a distribution percentage for organic content at any of those locations. What exists instead is the publication of the ranking mechanism by one platform, a report identifying widely viewed content rather than averages, and audited user counts in regulatory filings. Consequently every organic reach percentage in circulation originates from commercial analytics vendors measuring the accounts of their own paying customers, which constitutes a sample of organisations that purchase analytics software rather than a representative sample of any wider population, and which uses metric definitions that differ between platforms and that changed materially during 2025.Where the number was looked forProfessional networkHelp centre analytics pagesFeed ranking help pageMarketing and sales solutionsEngineering and member blogsSocial network groupTransparency centreNewsroom and business newsHelp centres, bothDeveloper blog and API docsThird platformBusiness help centreAdvertising glossaryAPI metrics documentationCorporate blogResult: no reach benchmark of any kind, anywhereNo average, no distribution, no percentage, no figure by industry, page size or format.So where do the published numbers come fromAnalytics vendors measuring their own customers’ accounts. That is a sample of companies that buy analyticssoftware, using definitions that differ by platform and that changed during 2025.
Documentation, transparency centres, newsrooms, developer docs and filings. No reach benchmark exists in any of them. Source : Search of the published documentation of three platforms (2026)

An impression is not the same thing on two platforms

This is the finding that makes cross-platform benchmarking impossible rather than merely unreliable.

One platform requires visibility and duration. “Impressions show the number of times each post is visible for at least 300 milliseconds with at least 50 percent in view on a signed in member’s device screen or browser window.”

The other requires neither. “Impressions are the number of times any content from your Page or about your Page entered a person’s screen.”

Entering a screen and being half-visible for a third of a second are different events. A post scrolled past at speed counts on one platform and not on the other. No conversion factor exists between them, and none can.

Reach is estimated on both, and sampled on one. For advertising reach: “This metric is estimated … This metric is calculated using sampled data.” The Page-level definition also carries the estimate warning: “Reach is the number of people who saw any content from your Page or about your Page. This metric is estimated.”

One platform does not use the word reach at all. It reports “members reached”, defined as “the number of distinct members and Pages that saw your post. This number is an estimate and does not include repeat displays.”

And engagement rate is calculated on different numerators. One defines it as “the ratio of interactions per impressions”, where interactions are clicks, reactions, comments and shares. Another defines it as engagements divided by impressions, with a different set of countable engagements.

Which produces a simple conclusion. Two platforms reporting the same engagement rate are not reporting the same thing, and a benchmark table placing them in adjacent rows is a category error rather than an approximation.

Incompatible definitions of impressions and reach across social platformsThe incompatible definitions of impressions, reach and engagement rate published by the principal social platforms, which make cross platform benchmarking arithmetically impossible rather than merely unreliable. The professional network defines impressions as the number of times each post is visible for at least three hundred milliseconds with at least fifty percent of it in view on a signed in member’s device screen or browser window, meaning both a duration threshold and a visibility threshold must be satisfied. The social network defines impressions as the number of times any content from a page or about a page entered a person’s screen, with no duration threshold and no visibility threshold whatsoever. A post scrolled past rapidly therefore registers on the second platform and does not register on the first, and no conversion factor exists between the two quantities because they count different events. On reach, the social network states that reach is the number of people who saw any content from a page or about a page and that this metric is estimated, while its advertising reach metric carries the additional disclosure that the metric is calculated using sampled data rather than counted. The professional network avoids the term reach entirely, reporting instead members reached, defined as the number of distinct members and pages that saw a post, described as an estimate excluding repeat displays. On engagement rate, the professional network defines it as the ratio of interactions per impressions where interactions comprise clicks, reactions, comments and shares, while another platform defines it as engagements divided by impressions using a different set of countable engagements. The consequence is that two platforms reporting an identical engagement rate are not reporting the same quantity, and a benchmark table placing their figures in adjacent rows commits a category error rather than introducing an approximation.The same word, two different eventsProfessional network: impression”Visible for at least 300 millisecondswith at least 50 percent in view.”Two thresholds: duration and visibility.A fast scroll does not count.Social network: impressionContent that “entered a person’sscreen.”No duration. No visibility threshold.A fast scroll counts.Reach is estimated on bothAnd the advertising version is explicitly”calculated using sampled data”.One does not say “reach” at allIt reports “members reached”: distinctmembers and Pages, excluding repeats.Which settles the benchmarking questionTwo platforms reporting the same engagement rate are not reporting the same thing. A table putting them inadjacent rows is a category error, not an approximation.
One requires 300 milliseconds and half the post in view. The other requires the content to enter the screen. There is no conversion. Source : LinkedIn Help, post analytics; Facebook Help, Page insights; Meta Business Help, ads reporting (2026)

One metric was deleted and replaced mid-series

Even single-platform comparison over time has a break in it, and it is recent.

The deprecation. The impressions metric in the Page insights interface was deprecated and replaced by a views metric on all versions, effective 15 November 2025, announced in August 2025.

What replaced it is two things. The views metric, introduced in November 2024, is defined as the number of times a video or reel was played, or the number of times a text or photo post appeared on screen. Those are different events sharing one name.

Which means any series crossing that date is broken. A page comparing its 2024 impressions to its 2026 views is comparing a count of screen entries with a count that mixes video plays and post appearances.

And the same period saw the page fans metric removed. So follower-relative reach, the basis of most published benchmark figures, lost its denominator too.

One consequence worth stating plainly. Any organic benchmark published as a time series spanning 2024 to 2026 is comparing incompatible quantities within a single platform, before any cross-platform issue arises.

What the platforms do publish

The absence of reach data is not an absence of information. One platform publishes a great deal about how ranking works, and the asymmetry between the two is itself informative.

The feed selection process, stated in stages. The system “gathers all potential posts shared by friends, Pages you follow and groups you’ve joined”, then “a lightweight model is run to select approximately 500 of the most relevant posts”, then it “calculates a relevance score for about 500 posts and puts them in order by this score.”

With prediction targets named. Among them: “How likely you are to scroll past a post rather than engage with it”, with signals including “number of times you quickly scroll past the same friend’s post in the past 7 days” and “average time spent on each post.”

And demotions named as categories. “Our Content Distribution Guidelines describe the types of content we think may either be problematic or low quality, so we reduce its distribution in Feed for everyone.” Named categories include clickbait links and engagement bait.

The other platform publishes almost nothing. Its help page on feed ranking says only that “our AI systems and algorithms consider hundreds of signals to determine what content appears in each member’s Feed”, plus a statement that demographic information is not used as a ranking signal.

One warning about sourcing on that platform. Pages under a content aggregation path on its own domain look official and are not: they are collections of member posts, and they contain exactly the unsourced reach multipliers this article is about. Domain is not provenance.

And on the decline itself, one platform has been on the record twice. In 2014: “Of the 1,500+ stories a person might see whenever they log onto Facebook, News Feed displays approximately 300”, and “Facebook is far more effective when businesses use paid media to help meet their goals.” In 2018: “Pages may see their reach, video watch time and referral traffic decrease.”

No equivalent statement from the professional network was found. That absence is worth noting rather than filling with an assumption.

Asymmetry in what social platforms publish about their own content ranking systemsThe marked asymmetry between what two major platforms publish about the operation of their own content ranking systems. The social network publishes the ranking process in explicit stages, stating that the system first gathers all potential posts shared by friends, pages followed and groups joined, excluding posts flagged as contravening its community standards, that a lightweight model is then run to select approximately five hundred of the most relevant posts while applying integrity processes intended to reduce the distribution of problematic content, and that the system finally calculates a relevance score for those approximately five hundred posts and orders them by that score. It further publishes named prediction targets together with the signals feeding them, including a prediction of how likely a person is to scroll past a post rather than engage with it, whose signals include the number of times the person has quickly scrolled past the same friend’s post within the preceding seven days, the average time spent on each post, and the position of the post within the feed. It publishes named demotion categories, stating that its content distribution guidelines describe types of content considered problematic or low quality whose distribution is reduced for everyone, with named categories including clickbait links and engagement bait, and stating that the distribution of borderline content approaching but not violating its policies is also reduced. The professional network publishes almost nothing equivalent, its help documentation on feed ranking stating only that its systems and algorithms consider hundreds of signals to determine what content appears in each member’s feed, together with an assurance that demographic information such as age, race or gender is not used as a signal determining visibility. A sourcing warning applies to that platform, since pages under a content aggregation path on its own domain appear official but consist of aggregated member posts containing unsourced reach multipliers, meaning the domain does not establish provenance.One explains itself. One does not.Published: the stages1. Gather all potential posts2. “Select approximately 500 of themost relevant posts”3. Score those 500 and order themPlus named prediction targets and thesignals behind them.Published: one sentence”Our AI systems and algorithms considerhundreds of signals to determine whatcontent appears in each member’s Feed.”No stages. No named signals. No demotioncategories. And no statement, ever, thatorganic reach has declined.On the decline, one has been on the record twice2014: “Facebook is far more effective when businesses use paid media.” 2018: “Pages may see their reach … decrease.”Sourcing warning: pages under a content aggregation path on the professional network’s own domain are memberposts, not documentation. They carry exactly the unsourced multipliers this article is about.
One names its prediction targets and its demotion categories. The other says 'hundreds of signals'. Source : Meta Transparency Center, Facebook Feed AI system and approach to ranking; LinkedIn Help, feed ranking (2026)

The audited numbers are narrower than you think

Regulatory filings are the one place where user figures carry legal weight, and what they contain is less than the press implies.

The largest group reports one cross-app figure. “Family daily active people (DAP) was 3.58 billion on average for December 2025”, defined as a registered and logged-in user of any of its four products “who visited at least one of these Family products” on a given day, with an estimated margin “of approximately 3% of our worldwide DAP”.

It no longer publishes any single-app number. The phrase “monthly active” appears nowhere in its annual report. There is no Facebook user count, no Instagram user count. So the widely quoted “three billion Facebook users” cites a figure its own publisher stopped reporting.

One platform has no audited number at all since 2021. Its last filed figure was 217 million monetizable daily active usage for the quarter ending December 2021, with the company’s own caveat that “our calculation of mDAU is not based on any standardized industry methodology.” It delisted in October 2022 and has filed no annual report since.

And the professional network has never had one. Its parent’s most recent annual report mentions it eighteen times, all of them about revenue, segment reporting or litigation. There is no member count, no monthly figure, no daily figure, in any year.

Its public number is a cumulative registration count. “1 billion members in more than 200 countries and territories worldwide.” How many of those log in is not published by anyone.

Which matters for a B2B plan. Reach planning that starts from a billion-member figure is starting from a total that includes every account ever created.

The one solid statistic about the platform that matters

For B2B, one institutional measurement stands out, and it is worth more than any reach figure.

The methodology is published. A national survey of 5,733 US adults, fielded 19 May to 5 September 2023, with a stated margin of error of plus or minus 1.8 percentage points at 50 percent.

The headline. 31 percent of US adults reported using LinkedIn.

And the finding the researchers themselves flagged as exceptional. “53% of Americans with at least a bachelor’s degree report using the platform, far higher than among those who have some college education (28%) and those who have a high school degree or less education (10%). This is the largest educational difference measured across any of the platforms asked about.”

One important caveat about currency. The same organisation dropped LinkedIn from its 2025 platform battery entirely. There is no 2025 figure, and its interactive fact-sheet page can produce apparently current LinkedIn numbers that are artefacts of stale labels paired with newer values. The last real measurement ends with fieldwork in September 2023.

Why the education finding is the useful one. It is a statement about who is there, from a probability sample with a published margin of error. That is a better input to a channel decision than any reach rate would be, and unlike a reach rate it actually exists.

Audited user figures in regulatory filings and what each one actually countsThe user figures available in regulatory filings, which are the only user counts carrying legal weight, and what each one actually measures. The largest platform group reports a single cross application figure, being family daily active people of three point five eight billion on average for December 2025, defined as a registered and logged in user of any of its four products who visited at least one of them through a mobile application or a web or mobile browser on a given day, with an estimated margin of error of approximately three percent of the worldwide figure and an estimate that fewer than five percent of that figure consists solely of violating accounts. That group no longer publishes any single application user count, the phrase monthly active appearing nowhere in its annual report, so there is no separate figure for its social network or its image sharing application, meaning widely quoted single application user counts cite a figure the publisher itself ceased reporting. A second platform has published no audited figure since the quarter ending December 2021, when it reported two hundred and seventeen million monetizable daily active usage, accompanied by the company’s own caveat that its calculation is not based on any standardized industry methodology, and it delisted from public markets in October 2022 and has filed no annual report since. A third platform has never published an audited user count at any point, its parent company’s most recent annual report referring to it eighteen times exclusively in connection with revenue, segment reporting and litigation, with no member count, monthly figure or daily figure disclosed in any year. That platform’s public figure of one billion members in more than two hundred countries and territories is a cumulative count of registered accounts rather than a measure of activity, and no party publishes how many of those accounts log in.What is actually auditedCross-app daily figure, filed for December 20253.58bnAnyone who visited at least one of four products on a given day. Margin “approximately 3%”.And the phrase “monthly active” appears nowhere in that filing. No single-app number exists.Last audited figure, quarter ending December 2021217m”Our calculation of mDAU is not based on any standardized industry methodology.”Delisted October 2022. No annual report filed since.The professional network: never auditedEighteen mentions in its parent’s latest annual report, all about revenue, segments or litigation.Its “1 billion members” is a cumulative registration count. Nobody publishes how many log in.Which matters if your channel plan starts from a billion-member figure that counts every account ever created.
One cross-app daily figure, one number frozen in 2021, and one platform that has never published an audited count. Source : Meta 10-K for FY2025; Twitter 10-K for FY2021; Microsoft 10-K for FY2026; Pew Research Center, 2024 (2026)

What to measure instead

If no benchmark exists, the alternative is not to stop measuring. It is to measure against yourself.

Your own baseline, per platform, never across them. Twelve weeks of your own posts is a comparison set that shares a definition. Nothing published gives you that.

A denominator you control. Followers is a poor one because it changes and because one platform removed the metric. Posts published is better: reach per post, replies per post, profile visits per post.

Outcomes that leave the platform. Clicks to a named destination, direct messages received, meetings that mention where the person saw you. These survive every definition change, because they are counted on your side.

And one qualitative measure worth more than any of them. Whether anyone in a sales conversation refers to something you posted. It is rare, countable, and it is the only evidence that the channel did anything.

What to stop doing. Comparing your engagement rate to a published average, because the average was computed from a vendor’s customer accounts using a metric definition that differs from yours and that changed in November 2025.

Measurement approach for social media activity in the absence of any published benchmarkThe measurement approach available for social media activity given the absence of any published organic reach benchmark, based on comparing against one’s own history rather than against external figures. The first measure is a self baseline established per platform and never across platforms, using twelve weeks of one’s own posts, which produces a comparison set sharing a single consistent metric definition, something no published source can provide. The second measure concerns the choice of denominator, where follower count performs poorly both because it fluctuates and because one platform removed the page fans metric entirely in November 2025, making posts published the more stable denominator and producing measures such as reach per post, replies per post and profile visits per post. The third measure comprises outcomes occurring outside the platform, specifically clicks arriving at a named destination, direct messages received, and meetings in which the participant mentions where they encountered the organisation, all of which survive platform definition changes because they are counted on the organisation’s own systems rather than reported by the platform. The fourth measure is qualitative and is described as worth more than the other three, namely whether any participant in a sales conversation refers to something the organisation posted, which is rare, countable and constitutes the only direct evidence that the channel produced an effect. The corresponding practice to abandon is comparing an engagement rate against a published average, since that average was computed from the accounts of an analytics vendor’s paying customers using a metric definition that differs from the one applied to the organisation’s own account and that changed materially in November 2025 when the impressions metric was deprecated and replaced.Measure against yourself1. A twelve-week self baselinePer platform, never across. It is the onlycomparison set with one definition.2. Posts as the denominatorNot followers, which move and whosemetric was removed in November 2025.3. Outcomes off the platformClicks to a named destination, directmessages, meetings that mention you.4. The one worth mostWhether anyone in a sales conversationrefers to something you posted..Three of the four are counted on your side, which is why they survive every definition change the platforms make.The fourth is rare, and it is the only one that proves anything.And stop comparing your engagement rate to a published average. There is no average to compare it to.
Four measures that survive every definition change, because three of them are counted on your side. Source : Method (2026)

What to do with this

Delete the benchmark row from your reporting. Replace it with your own trailing twelve-week median, per platform, so that every comparison uses one definition.

Then check whether any series you keep spans November 2025. If it does, break it there and label the break, because the metric behind it was replaced.

Choose the demographic evidence over the reach evidence when picking a channel. One published, methodologically sound finding about who uses a platform beats a reach rate that nobody has ever published. Where the reach has to be countable rather than estimated, it has to be bought, and our page on B2B paid acquisition sets out how paid distribution is planned and reported with one definition per metric.

And when a proposal quotes an organic reach figure, ask which platform’s definition it uses and where the sample came from. Both questions have answers, and neither answer is “the platform published it.”

The related pieces are the real cost of social selling and editorial line for B2B.