In-network / out-of-network: how we built the analytics LinkedIn isn't showing yet

One evening, two posts by Sam Corrao Clanon from LinkedIn’s product team caught my eye. They announced a metric I’d been looking for in my analytics for a long time — one LinkedIn still wasn’t showing me. I decided not to wait for the official rollout and to build it myself. Here’s how I approached it.

It started with two posts

In the first one Sam announced a new post-analytics metric: a percentage breakdown of your audience into those already in your network and those outside it. To quote:

„You’ll begin to see a percentage breakdown of who has seen your content, based on if they’re already in your network or not.”

The definitions were simple:

• In-network reach — the share of impressions from people already connected to you or following you.
• Out-of-network reach — the share of reach from people not connected and not following — a new audience reached through feed recommendations, reshares, search, and so on.

The card is meant to land in the Discovery section of post analytics, below the view count:

In the second post Sam shared his own result: a 20/80 split — 20% engagement from his direct network, 80% from outside it. He put it aptly: „a pure product announcement that has nothing to do with me or my opinions travels pretty broadly”.

This is exactly the kind of metric that changes how you think about content: does this post deepen relationships with my network, or open me up to new people? I thought right away: I want this in the analytics in our LinkedIn CRM, B2BMarketing.AI.

LinkedIn’s API: where is it, even?

First step — check whether I even have something to work with.

I opened my own post analytics on LinkedIn. Not there. I checked a few other people’s profiles I have access to in our platform. Not there either. The feature Sam announced as „rolling out globally over time” simply hadn’t reached us in the interface yet — and knowing how it goes, it might never arrive at all.

At that point I could have stopped and waited for LinkedIn to turn the card on for everyone. But since we work directly with the internal API, I asked a different question:

If the interface isn’t showing it — is the data already in the API?

LinkedIn has the data but doesn’t show it

I started digging through the responses of the endpoint we pull data from. And there, in the profile/post viewers section, was a breakdown by network distance:

• how many viewers are 1st-degree connections,
• how many from the extended network (2°/3°),
• how many outside the network,
• how many remain anonymous.

In other words: LinkedIn’s databases were already counting this split before the user-facing page started showing it.

It’s not the first time I’ve seen this with them — collecting various data but not presenting it to users. The same happened with LinkedIn Save and Send stats, which I presented at the I Love Marketing conference a few months before the rollout for everyone.

To sum up: the user-facing card was still being designed, but the raw numbers were already waiting in the database. That was a green light for someone like me. I decided to build my own solution and wire it into our analytics — without waiting for the official rollout.

What analytics did I build?

We extended our analytics pipeline so that on every run it collects and stores in the database:

• four total counters: your network, i.e. 1, acquaintances and strangers, i.e. 2 and 3, plus hidden profiles,
• a snapshot of the viewers list, because I have an idea for a new feature showing the biggest fans of your posts.

We show it to users as a pie chart split into percentages — even though I remember that pie charts send you to the corner, as Janina Bąk would say.

What mattered to me: it’s a better split than the binary in/out-of-network from LinkedIn’s card. Instead of two values we have four levels of distance, so you can see not just „in network vs. outside”, but also how much reach comes through the extended network (2°/3° — the effect of reshares and recommendations), and how much stays fully anonymous.

Here’s what it looks like for a real post (B2B Marketing.AI, 2026-05-20):

So: 33% are direct connections (1°), 44% extended network (2°/3°), barely 2% truly out-of-network, and 21% remain anonymous. A note on mapping: in LinkedIn’s binary view „in-network” means followers and connections, so our 2°/3° would fall into out-of-network for them — which is why I don’t compare these numbers 1:1 with Sam’s 20/80. But the qualitative takeaway is the same: this post resonates close to home (most viewers within 3 degrees, almost no one from outside), unlike a dry product announcement that „travels” broadly outward.

Engineering puzzles for nerds

Because it’s never as simple as on the slide:

1. LinkedIn likes to complicate things by obsessing over details. Checking data on specific profiles, we found that your connections aren’t always stored as 1 in the database, but as a combination of whether the contact is a Follower or not. You can confirm it by checking whether you see Connect or Message on the profile — but that’s another step in the process.
2. Chaos in how the data is stored. Basically a continuation of the previous point. Checking the data closely, we found that LinkedIn reports such optimistic values, inflates them so much, that the sums come out over 100%. Technically it’s a matter of the data being written several ways (why?), but along the way I caught that it also affects post-view stats and demographics. I fixed it and reported it as a bug, but I don’t know whether it’ll be fixed — because if your stats drop even further, nobody will want to publish on LinkedIn anymore.

What’s in it for you

• Data comes before the interface. When LinkedIn announces a „rolling out” feature, the data is often available earlier than the place for it on the page. It’s worth checking the source before you start waiting — it might be easy to implement.
• The new LinkedIn analytics changes how you think about content. Showing in/out-of-network data isn’t a curiosity to me — it’s the answer to the question of whether you’re building depth or reach. Now we have it in-house, on our own data, regardless of when LinkedIn turns on the official card.
• This data won’t be for everyone. As with other advanced metrics — e.g. Save, Send, Link Click — the data will be shown to selected users first. It’s typical LinkedIn practice that such novelties first go to paid LinkedIn account users, and only then possibly to everyone.
• It’s worth reading posts by LinkedIn employees.

And I’m waiting for that official rollout anyway — we set up a weekly monitor on the server (analytics-card-monitor) that’ll let us know when LinkedIn finally shows its version of the card. Then we’ll compare it with ours. For now, I invite you to test our tool that helps you work with your LinkedIn.

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This post is based on the rollout of the „profile-viewers in/out-of-network” feature in our analytics platform (June 2026). Inspiration: Sam Corrao Clanon’s posts linked above.