Your team published solid content this month, and the platform served it to plenty of people, but the public engagement barely registered. Now you're staring at a flat LinkedIn report wondering whether the content failed or the scoreboard did, and somebody above you is going to ask which one it was.
Sarah and I spent this episode pulling that apart, and you'll come away with a working theory for why engagement went private, a sense of how much analytics data has quietly gone missing on you, and a smarter way to talk about flat numbers with whoever signs off on your budget.
This post is based on Episode 74 of Revenue Rewired | Visibility No Longer Equals Influence: What Marketers Get Wrong About Engagement.
If you'd rather listen than read, find the full episode on Apple Podcasts, YouTube, Spotify, or Amazon. It's worth your time.
Sarah Shepard, our COO and my co-host, opened this episode with something that happened to us the week we recorded. We'd been reviewing our channel metrics, LinkedIn included, and the numbers weren't looking great. Then about 24 hours after everything went out, the text messages started, people telling us how much they enjoyed the content. That kind of private feedback feels great when you made the thing, but if you're a marketing manager judged on public numbers, none of it shows up anywhere a report can see.
The same day we recorded, Sarah and I hosted a webinar with a warm, engaged audience that gave us lots of positive feedback afterward. When we ran polls during the session, maybe 5 percent of the audience responded. That wasn't a content problem, and I don't think it was an interest problem either. My theory is paranoia. As a dad of two young adults, I've told my kids for years that anything you put online is there forever, whether you delete it or not, and a thousand other parents and managers have said the same thing. We may have raised a generation of professionals who hesitate before publicly attaching their name to anything, even a comment on an industry post.
So the engagement didn't vanish; it moved somewhere your dashboard can't follow. We've spent seven hours building a five-slide deck for a 20-minute presentation, put it out there, and heard nothing publicly while the private notes rolled in. That gap between what's happening and what's measurable is what this whole episode is about.
Social media isn't really social anymore, and Sarah and I have started calling it what it is: interest media. The phrase has been circulating lately; Gary Vaynerchuk told a version of this story recently, and it describes a real shift. Platforms no longer prioritize showing your content to your network. They prioritize whatever keeps each user scrolling, because their core metric is how long you stay on the platform, and stickiness sells ads.
Sarah brought up an algorithm researcher whose first ten posts were AI content, skills courses, and ads. This is a guy who studies feeds for a living, and he couldn't find his own network in his own feed. We got into the LinkedIn algorithm back in episode 65, and things have only gotten stranger since. People are now complaining publicly on LinkedIn about LinkedIn, begging for their feed to show peers and clients again instead of another AI lead generation pitch.
The platforms deserve to make money, and I don't fault the shareholder math. I do worry about the trust cost, though. LinkedIn is, in theory, the only place B2B professionals can have proper business conversations at scale, and users are getting frustrated enough that the second a better alternative shows up, I think you'll see real migration. Sarah bets that professional community gets smaller before it gets bigger again, moving into niche Reddit threads and private Discord servers where the group polices its own quality.
More than you'd guess, and it's not a rounding error. Between cookie deprecation and private browsing, a growing share of your Google Analytics traffic now arrives with no identity attached at all. On the episode, I used 15 percent as a working number. If 15 percent of your audience is invisible to your reporting, there's a real chance your best-fit, cream-of-the-crop buyers are sitting inside that blind spot, and every decision you make off the visible data quietly ignores them.
Old metrics deserve a second look too. Time on site used to appear on slide two of every analytics report as a win, and the longer I've sat with it, the more I think a high number can signal a user experience problem. If your site exists to generate leads and visitors are wandering around for ages without converting, the data isn't flattering you, it's warning you. A metric only means something once a human decides what question it's answering.
Sarah's research brain is useful here. She treats every piece of content like a hypothesis with an expected outcome, then follows the attribution trail to find where the breakdown happened. You can't run that play if the only number you ever look at is visibility, because someone will eventually ask what happened after the impression, and "we got served a lot" isn't an answer that survives a budget meeting.
I had lunch recently with a client who was second-guessing his full-time marketer. She produces a steady stream of content, but when she walks him through the numbers, he leaves unimpressed, and he'd started wondering out loud whether he had the wrong person in the seat. A version of that conversation is happening inside a lot of companies right now, and in plenty of them the marketer is doing solid work the platform simply isn't surfacing.
My advice cuts both ways. Marketers need to understand their internal audience as well as their external one, because the pressure usually comes from inside the building. Explaining the algorithm shift is fair context, but delivered wrong, it sounds like an excuse. Bring the private signals into your reporting: the texts and email replies that never touch a dashboard, and pair them with a plan for what you'll test next. And if you invested serious hours in a white paper or a presentation, don't stop at posting it and hoping for 19 likes. Send it directly to the audience you built it for through channels you control.
Executives have a role here too. Before concluding the content stinks or the marketer does, step back and have the strategic conversation, because these platforms make money by keeping people scrolling and your team doesn't control that. Content that reaches the right people compounds over quarters, not weeks, even when the public scoreboard stays quiet. I hear from real humans that our work matters to them, and a handful of likes was never going to be the reason I stop making it.
Q: My posts get impressions but no engagement. Does that mean the content is bad?
A: Not by itself. Getting served means the platform sees value in the content, and silence often means your audience now engages privately instead of publicly. Check what's coming back through private channels before you judge the work.
Q: What is interest media?
A: It's what social media has turned into. Platforms serve content based on what holds each person's attention rather than on who they're connected to, which is why your own network may never see what you post. Stickiness drives ad revenue, so it beats relevance to your network.
Q: How much of my Google Analytics data is unknown or not set?
A: It varies by audience, but with cookie loss and stricter privacy settings, a double-digit share is common. The uncomfortable part is that your best-fit buyers may be concentrated in that invisible group, so treat the visible data as a sample, not the whole story.
Q: Should I keep posting on LinkedIn if engagement stays low?
A: Yes, with adjusted expectations. Use it for research and relationship building, and distribute the same content through email and other routes you own. The payoff builds slowly, so judge it on pipeline conversations, not likes.
StringCan helps B2B companies figure out what their marketing is doing for revenue, from audience strategy and positioning through the attribution work that shows which efforts deserve more investment. A lot of that work starts exactly where this episode did, with a leadership team staring at numbers that don't add up to a clear decision and wanting a better way to choose what happens next.
If this conversation hit close to home, listen to the full episode and subscribe so the next one reaches you before an algorithm decides whether it should. Sarah and I read everything that comes into podcast@stringcaninteractive.com, and we'd love to hear how engagement is shifting in your world.