Every brand running LinkedIn influencer campaigns has received a folder of screenshots at the end of a campaign. Polished images showing 180,000 impressions, 4.2% engagement rate, audience breakdown by seniority. The creative was solid. The invoice was paid. But most brand managers, when they're honest, will admit they had no way to verify a single number in that report. They trusted it anyway, because they didn't know what else to do.
This is not a fringe problem. It is the structural reality of how LinkedIn influencer reporting has worked for the last several years.
Why LinkedIn Impressions Are So Easy to Fake
LinkedIn impression data is private. Unlike Instagram, where third-party analytics tools can access certain performance metrics, LinkedIn does not allow any external platform to independently read a creator's post impressions. The only person who can see real impressions is the account holder, inside LinkedIn Creator Studio.
This means every screenshot a creator shares with a brand is unverifiable by the brand. There is no way to cross-reference it. A screenshot is an image file. It can be edited in five minutes, generated from a different account, or taken from a short time window that doesn't represent the post's true performance period. It can show whatever number the creator wants it to show.
After three years of running LinkedIn influencer campaigns across B2B SaaS, fintech, HR tech, and D2C categories, the pattern at anchors has been consistent: in mass campaigns where creators self-report their impression numbers via screenshots, the figures cannot be independently verified roughly 90% of the time. That's not 90% that are definitely fake. It's 90% where a brand has no mechanism to tell the difference between real and fabricated.
That distinction matters. But it still means most brands are making spend decisions on unverifiable data.
What Brands Usually Do — And Why It Fails
The standard brand approach goes something like this: ask the creator for screenshots of their last three to five posts, check whether the engagement rate looks plausible, maybe run the numbers to see if anything looks inflated.
There are two problems with this. First, engagement rate is derived from the impression figure. If a creator reports 200,000 impressions and 1,800 likes, the engagement rate is 0.9%. That looks plausible. But if the real impression count was 12,000 and the creator fabricated the larger number, the rate is meaningless — it was calculated from a lie.
Second, asking for more screenshots is not the solution. It's asking for more of the same unverifiable data.
Some brand managers have started asking for video walkthroughs — a live screen share showing the creator's analytics. This is better, but it can still be staged: a different account's analytics viewed in a browser, a deliberately short time window that captures a high-impression moment, or a real account whose historic numbers don't match what they're showing. Most brands don't request this at all because it takes time to arrange, and most creators won't cooperate with that level of scrutiny without pushing back.
If you want a practical starting point for vetting LinkedIn creators before committing budget, there are signals beyond impressions that can tell you a lot — but they're a workaround for a broken system, not a fix.
Running campaigns on unverified data is a budget problem.
anchors shows you verified creator reach — pulled directly from LinkedIn — before you commit a rupee.
See how it works →The Agency Problem: Why Intermediaries Don't Catch This Either
If brands can't verify the data, surely the agencies running these campaigns can? Not quite.
Agencies are aware this practice exists. It has been documented within the industry for years. But their business model does not require them to verify creator delivery. A typical agency charges 10 to 15% commission on total campaign spend. That commission is collected regardless of whether the impressions that were reported were real. Their margin doesn't shrink if a creator fabricated their numbers.
In fact, the incentive runs the other direction. When creator-reported impressions are high, the campaign looks like a success. Clients renew. Agencies recommend bigger budgets next cycle. The reporting function is designed to make campaigns look effective, not to expose gaps in delivery.
This is a structural misalignment of incentives, not a moral failing of individual agencies. The way the agency compensation model is built, there is no mechanism that rewards verification. As the Edelman Trust Barometer has consistently shown, trust in institutional intermediaries is declining across industries precisely because the incentives of those intermediaries don't align with the interests of the people they serve. LinkedIn influencer marketing is no exception.
The brands that get burned are the ones who assumed their agency had verified the data, without ever asking how.
What Verified LinkedIn Influencer Data Actually Looks Like
Verified data looks nothing like a screenshot. It looks like a live dashboard.
On anchors, creators join the platform by connecting their LinkedIn accounts directly. anchors reads their real impression data from LinkedIn in real time — the same data LinkedIn holds for that account. When a brand evaluates creators on anchors before launching a campaign, they are looking at actual impression history from the creator's recent posts, audience composition by job title, seniority, industry, and location — all pulled from LinkedIn's own systems.
No screenshots. No self-reporting. No manual entry. The data the brand sees is the data LinkedIn has.
After the campaign goes live, the dashboard shows verified delivery: actual impressions delivered, broken down by creator, with a full analytics layer. anchors also runs AI analysis on every comment on every creator post — categorising sentiment, identifying product queries, surfacing purchase intent signals. The brand gets a post-campaign intelligence layer that most of them have never seen before, because most campaigns don't measure anything beyond the impression count that a creator emailed them in a PDF.
CARS24 came to anchors specifically because their previous campaigns had relied on screenshot-based reporting. The result of switching to verified data: ₹55 CPM across the campaign, verified delivery with no self-reported metrics, 10x ROI versus their expectations, and an 80% reduction in ops time spent managing the campaign. The team, in their words, "finally had access to all the data for better campaign planning, without chasing influencers."
That is what verified data changes. Not just the accuracy of the numbers — the confidence to act on them.
See what your LinkedIn influencer campaign reach would look like before you spend anything. Try anchors free
How to Protect Yourself If You're Not Using a Platform
If you're evaluating LinkedIn creators manually, there are three things you can do to reduce your exposure to fabricated data.
Ask for impressions from the last 10 posts, not a curated selection. A creator who can only share their three best-performing posts is telling you something. Real verified reach is consistent enough to show across a full month of content, not just highlight moments.
Cross-reference the claimed impressions against visible engagement. A LinkedIn post claiming 150,000 impressions that has 14 likes and 2 comments is almost certainly inaccurate. LinkedIn's average engagement rate is low, but not that low for organic content that genuinely reached that many people. The pattern of likes, comments, and reposts should be proportional to the claimed reach. If it isn't, treat the number as suspect.
Request a live screen share of LinkedIn Creator Studio, showing the specific post in question. Not a screenshot taken beforehand. A live walkthrough, where you can see the post title and the date alongside the analytics. This is harder to stage and significantly more reliable than any static image. Many creators will be uncomfortable with this request. That discomfort is itself useful data.
These steps don't solve the underlying problem — they're workarounds for a system where brands don't have structural access to real data. The signals of influencer fraud on LinkedIn go beyond impression manipulation and are worth understanding even if you switch to a platform that handles verification for you.
LinkedIn Influencer Red Flags Checklist
Use this before approving any creator whose data comes via screenshot:
- Impressions shared only via screenshot — no live screen share offered when asked
- Best-post cherry-picking — creator can only share 2 or 3 posts, not a rolling 30-day view
- Engagement-to-impression ratio that doesn't add up — 100K impressions with fewer than 50 visible interactions
- Follower count dramatically higher than typical impressions — a creator with 80,000 followers consistently delivering 4,000 impressions has an algorithmic reach problem worth understanding
- Reluctance to verify via screen share — pushback on live verification is a signal, not a coincidence
If a creator is willing to show their real data in real time, they almost certainly have nothing to hide.
Frequently asked questions
If your last LinkedIn influencer campaign came with a folder of screenshots, you were running on unverified data.
anchors shows you verified creator reach, audience composition, and cost before you commit a rupee. The data is pulled directly from LinkedIn — no screenshots, no guesswork.
Start on anchors →