![How to Write Good Thought Leader Ads (TLAs) on LinkedIn [with EXAMPLES]](/_next/image?url=https%3A%2F%2Fcdn.zenabm.com%2Fmedia%2FHow-to-Write-Good-Thought-Leader-Ads-TLAs-on-LinkedIn-1200x675.png&w=1920&q=75)
The most common reason TLAs underperform has nothing to do with budget, targeting, or bid strategy. It’s the post itself. Specifically: it reads like an ad. The moment a reader senses they’re being sold to – even subconsciously – they scroll. I’ve analyzed 119 Thought Leader Ads from our 2026 LinkedIn ABM Benchmarks Report – covering over $300K in ad spend across multiple B2B accounts – and the single biggest driver of TLA performance has nothing to do with targeting, budget, or bid strategy. It’s the writing. Specifically: whether the post sounds like a real person thinking, or a marketer performing. In this guide I’ll share exactly what separates the top 25% of TLAs from the rest, including the hook formulas, content structures, and formatting rules that consistently drive clicks and pipeline. I’ll also walk through how Valueships got their TLAs working within the first week of their LinkedIn ABM campaign and why most teams are leaving significant pipeline on the table by promoting the wrong content. What you’ll learn:
👉 We front-loaded all these best practices into our FREE Linkedin Thought Leader Ads generator
A Thought Leader Ad appears in the LinkedIn feed under a real person’s name and photo. To the reader it looks like an organic post from someone they follow. That context is a huge advantage – but a hard task. The upside – People engage with personal content at a much higher rate than brand content. Our Linkedin ABM benchmarks report (based on 211 companies) shows TLAs deliver a 2.68% median CTR and a median CPC of $2.29 – compared to 0.42% CTR and $13.23 CPC for single image ads. That’s 77% cheaper per click for the same outcome. Now for the hard part: the moment the post sounds like marketing copy – corporate tone, feature lists, a hard sell CTA – the trust instantly disappears. The reader realises they’re being sold to – and they lose interest. The goal of a TLA is not to sell directly. It’s to be so useful, honest, valuable, funny or interesting that the reader wants to know more. The click is a byproduct of giving that genuine value – not a response to a call to action. As Gabriel Ehrlich, founder of Remotion (one of the top LinkedIn ads agencies, with clients including Monday.com and Gong), put it in our ABM Bootcamp session: “The whole post smells of AI – the em dashes, the vocabulary – it’s all AI. We make ads sound like humans, not AI slop.”

Before anything else: stop using the CTR number LinkedIn shows you in the Campaign Manager Performance tab. That number includes likes, comments, shares, “see more” clicks, and profile visits. A TLA showing 17% CTR in the Performance tab might have zero actual landing page clicks (!!!) To find the real metric: go to the campaign, click the ad, open the Engagement tab (not Performance), and look at Clicks to Landing Page divided by impressions. That’s the number that tells you whether the writing is working.

Tim Davidson, Linkedin Ads expert who has run TLA campaigns for ABM across dozens of B2B clients, breaks every high-performing TLA programme into three components: Right Person, Right Content, Right Distribution. Most teams get the distribution right and completely ignore the first two. Here’s how each works.
The author matters because LinkedIn users see the post as coming from that individual – their face, their name, their credibility. The wrong author creates friction before the reader has even processed the first sentence. In order of effectiveness:

2. Founder or CEO. Founder-led content outperforms all other sources consistently. Buyers trust that founders have earned the right to strong opinions about the problems their company solves. The credibility is front-loaded. 3. Any executive who posts consistently. Consistency beats title. An engaged VP who posts regularly is more valuable than a CMO who needs chasing for every post. 4. Influencers & customers. External influencers with established authority in your target audience often outperform internal ones for specific audiences. And happy customers are the most credible TLA source for late-stage buyers. Tim Davidson has found that approximately 99% of customers say yes when asked to post. Influencers in your space can be paid to post (as a sponsored post) and then promoted as a TLA – their followers see it organically while your ICP accounts see it as an ad. You can do it e.g. through your own customer advocacy program or Linkedin Partnerships tab:

LinkedIn’s Partnerships tab shows everyone who has tagged your brand organically, which is a direct pipeline of TLA candidates. 5. Anyone who will actually do it. Beats nothing 🤷♀️ Who not to use: sales reps (unless you’re selling to sales reps, of course 😉). The context of their role colours how the content is received even when the content itself is good.
Now this is the tricky part – most of your ICPs are not writers, don’t share anything on Linkedin organically, and are reluctant to do the heavy lifting of writing TLAs themselves:
of all landing page clicks – from Thought Leader Ads
of total budget — TLAs cost $391 of $6,204 (6%) total
cheaper CPC to LP — $0.15 TLA vs $10.02 Image Ads
Same LinkedIn ABM campaign — 3 ad formats running simultaneously (~1 week). All figures in USD.
Format | Spent | Impressions | All Clicks | LP Clicks | CPM | CPC to LP |
Single Image Ads | $3,076 | 63,669 | 307 | 307 | $48.09 | $10.02 |
Thought Leader Ads (TLA) | $389 (6%) | 169,571 | 18,113 | 2,669 | $2.30 | $0.15 |
Carousel Ads | $2,724 | 49,412 | 234 | 234 | $55.12 | $11.64 |
TOTAL | $6,204 | 282,652 | 18,654 | 3,210 | $32.87 | $2.89 |
Key takeaway: TLAs got 6× more impressions than single image ads at 1/8th the CPM ($2.30 vs $47.60–$55.16), drove 83% of all LP clicks 66 x (!) cheaper ($0.15 vs $than image ads came from just 6% of the TOTAL budget.

75 TLAs + 432 Image Ads analyzed across ZenABM customer accounts. CTR is currency-agnostic.
Metric | TLAs | Image Ads | Advantage |
Aggregate CTR | 0.67% | 0.38% | TLA +75% ↑ |
Avg CTR per ad | 0.58% | 0.41% | TLA +41% ↑ |
Median CTR per ad | 0.42% | 0.40% | TLA +5% ↑ |
Aggregate CPLP | 5.52 | 17.20 | TLA 3× cheaper ↓ |
Avg CPLP per ad | 14.13 | 17.55 | TLA +24% ↓ |
Top 25% Avg CTR | 1.49% | — | vs Bottom 25%: 0.02% |
Top 25% Avg CPLP | 4.55 | — | vs Bottom 25%: 64.88 |
✅ Do: “Seat-based pricing is still cool! (it’s not)” or lead with a hard number creating tension. ❌ Avoid: “A big part of preventing burnout is planning ahead” — generic, no tension.
✅ Do: Lead with precise data — $51,217, $801k pipeline, 140% price increase. The number IS the hook. ❌ Avoid: “We made some major changes” — vague, unquantified.
✅ Do: Reference Amos Bar-Joseph/Swan AI, Jenna/Netflix, Notion’s pricing. Credibility by proxy. ❌ Avoid: “A customer I spoke to” — unnamed, unverifiable.
✅ Do: “I made all the ABM mistakes in the book” — vulnerability earns trust. ❌ Avoid: Product testimonials or brand announcements written in 3rd person.
✅ Do: CTA in P.S. after delivering real value — feels like a natural next step. ❌ Avoid: “Introducing the speaker lineup” — the post IS the CTA, kills engagement.
Every top performer follows the same arc: situation → problem → insight → proof → light CTA
Source: ZenABM analysis of 75 TLAs — top 25% average 1.49% CTR vs bottom 25% at 0.02% CTR

The most common objection I hear: “But the post only got 3 likes organically. It won’t work as an ad.” This confuses two completely different things. Organic performance depends on your existing follower base, how the algorithm distributes content, and whether the post triggered early engagement in the first hours. TLA performance depends on how relevant the content is to the specific audience you’re targeting. The same post that flopped organically can perform exceptionally as a TLA because you’re now putting it in front of exactly the people it was written for – not your general follower mix. Tim’s clearest example: a post about making a specific B2B marketing mistake got 5 organic likes. As a TLA targeting exactly the persona the post referenced, it drove 3 demo requests in the first week. The three qualities shared by almost every top-performing TLA I’ve analyzed: personal, specific, and honest about failure or challenge. Content that fails tends to be corporate, vague, or focused on achievements rather than struggles. Our data from 119 TLAs shows that 65% of top performers use first-person “I” voice throughout:

A few setup decisions have an outsized impact regardless of how good the writing is:

The first 2-3 lines are the only thing 90% of your audience will ever read. They determine whether someone clicks “see more” – which is the first micro-conversion before they ever click to your LinkedIn page or landing page. Everything else in the post is written for the people who clear that first hurdle. I’ve generated this “model TLA” based on all the best practices I noticed in our 2026 LinkedIn ABM Ads benchmarks report:

From analyzing the top-performing TLAs in our dataset, five hook patterns consistently drive the most Clicks to LinkedIn Page:

Open with something the reader already believes – then immediately complicate it. This creates cognitive tension that demands resolution. Example: “It’s tempting to believe there’s a single source of truth for understanding your users.” The reader nods, then reads on to find out what’s missing from their current view. Better still – use humour to laugh out (can you even say that? 😅) the problem you’re trying to contest.

Take a clear position that’s mildly provocative without being clickbait. The reader has to find out if they agree or disagree – both responses pull them in. Example: “No one has ever bought software because you used their logo on a landing page.” Don’t hedge. A hedged contrarian take doesn’t work.

Lead with the data before you explain anything. Forces the reader to ask “how?” Example: “[UPDATE: $801,000 pipeline, $189k revenue, 4.5 months in]” – this was one of our highest-performing TLAs across all accounts in the dataset. Specificity is what earns the click. “Good results” earns nothing.

The specificity – “5 years”, “three times”, “in Q3 specifically” – makes it feel real rather than manufactured. Generic admissions of failure don’t land. Specific ones do. Example: “I spent 5 years on the customer side before joining this team. Here’s what I wish I’d known.”

Signals “I know your world” before the reader has read a full sentence. Immediately establishes that this is written for them. Example: “Every CFO I talk to in this space says the same thing:” – the reader in that role thinks “that’s me” and reads on. Hooks to avoid: generic openers like “In today’s fast-paced world…” (= AI slop laughing stock), opening with your product or company name, and starting with a question (questions consistently underperform statements in the TLA dataset).
Once the hook has landed, the formatting of the body determines whether the reader stays with you long enough to hit the CTA.

This is non-negotiable on mobile. LinkedIn truncates long blocks of text. White space signals “this is worth reading.” Like this 😉 The top-performing TLAs in our dataset use single-sentence paragraphs at key moments for emphasis. A wall of text is a skip on any screen.

Lists work great to summarize insights – but don’t open with a list. Build tension first, then deliver the framework or step-by-step breakdown as the resolution. A bulleted list at the start signals “this is a generic tips post” – the reader has seen it a thousand times and scrolls.
The old broken way vs. the better way is one of the most reliable structures in TLA content. Make sure you can clearly articulate both sides – if you can’t, the post isn’t ready yet. The contrast format works because it validates the reader’s current pain before offering the resolution.
Pull CTA (works) | Push CTA (underperforms) |
|---|---|
“Happy to share more if you’re exploring this” | “Click here to book a demo” |
“Read the full report here: [link]” | “Sign up now” |
“You can try it free for 37 days” | “Get started today” |
In a TLA context – where the post appears as a personal share – a hard sell CTA breaks the frame and destroys the trust built by the content. Use pull CTAs that respect the reader’s autonomy.
Gabriel Ehrlich is direct about this: “Don’t use hashtags in TLAs. We pay to reach the right people – hashtags are unnecessary if your targeting is set up correctly.” The same applies to AI-generated vocabulary and formatting patterns (em dashes, symmetrical bullet structures, words like “delve” and “leverage”). Read the post aloud. If it sounds like a press release, rewrite it.

1. The What/Why/How post. Hook with what most people do or believe. Explain why it fails using specific, relatable examples. Deliver a numbered framework for how to do it better. Close with a soft link. Best for evergreen topics where the reader has lived the frustration you describe. The framework gives them something immediately usable, which is why they click through for more. 2. The Honest Results post. Share real numbers – including the uncomfortable ones. The highest-performing post in our entire dataset was an update post: specific pipeline figure, revenue number, timeframe, and an honest admission that something went wrong mid-campaign (“mistakes – scratch that: learnings”). The vulnerability is what makes people trust the numbers. Polished results posts don’t get shared. Honest ones do. 3. The “I Made This Mistake” post. Outperforms self-congratulatory content consistently. The reader recognises themselves in your mistake. The solution becomes a natural resolution rather than a pitch. Structure: describe the mistake in specific terms – show you understood why it was a mistake – show the turning point – show the result with a number. 4. The Contrarian Take. Pick a widely-held belief or common tactic in your space and argue it’s wrong or overrated. Back it up with a specific observation – not just an opinion. This format generates comments from people who disagree, which LinkedIn rewards with more organic reach. The rule: take a clear side. Hedged contrarianism doesn’t work. As one of our top-performing posts put it: “ABM personalization AT SCALE is an oxymoron.”5. The Framework post. Present a way of thinking about a common problem as a named mental model or process. Give it a name – “the product adoption loop”, “the Analyse – Prioritise – Launch cycle”, “the RPCD framework.” Named frameworks spread because they give the reader something to repeat in their own conversations. If they’re quoting your framework in internal meetings, they’re already halfway through the buying process.
Pattern | Why it kills performance |
|---|---|
Opening with the product or company name | Signals “this is an ad” before the reader has read any value. Protective walls go up immediately. |
Feature lists without a problem frame | No tension means no reason to care. The reader doesn’t know why they should want what you’re listing. |
Vague pain without specificity | “Teams struggle with X” – the reader thinks “not my problem.” Specific pain creates recognition. |
Long unbroken paragraphs | Readers bounce before the hook resolves. On mobile, a wall of text is a skip. |
Multiple CTAs in one post | Dilutes intent. The reader does nothing because they don’t know which action to take. |
Corporate tone or passive voice | Destroys the “real person” credibility that TLAs depend on. Reads like a press release, performs like one. |
No admission of failure or challenge | Reads as PR. Buyers are sceptical of unqualified success stories. Honesty about difficulty makes the result believable. |
Hashtags | Signals “this is a scheduled brand post.” Undermines the personal voice of the TLA format entirely. |

Valueships, a B2B services company running LinkedIn ABM campaigns through ZenABM, saw their TLAs smashing all other ad formats in terms of cost efficieccy and number of landing page visits, and generting 12 meetings within the first week of their campaign – and one closed won deal within three 🤯.

The posts that performed were personal narratives from the founder addressing a specific operational pain point – written in the exact voice the target persona would recognise as their own.

In our own ZenABM campaigns, the highest-performing TLA across the entire dataset started with an update sharing real numbers: $650,000 in pipeline and $12 in pipe per $ spent in revenue 3 months in:

That post combined the honest results format with a visible admission that the cost per pipeline dollar had declined due to mistakes made. The transparency was the mechanism – not the pipeline number alone. From the broader benchmarks dataset: across 119 TLAs and $300K+ in spend, the top 25% of ads by Clicks to LinkedIn Page share four traits: a hook that creates tension in the first line, at least one specific number or data point, a named framework or clear structure in the body, and a pull CTA that earns the click rather than demanding it. You can download the full breakdown in our 2026 LinkedIn ABM Benchmarks Report.

TLAs are the most cost-efficient format in the LinkedIn ads stack. Based on our 2026 benchmarks data:
Ad Format | Median CTR | Median CPC | Efficiency Score |
|---|---|---|---|
Thought Leader Ads | 2.68% | $2.29 | 9.5 |
Single Image Ads | 0.42% | $13.23 | – |
Video Ads | 0.24% | $15.61 | – |
Carousel Ads | 0.32% | $13.30 | – |
TLAs deliver clicks at 77% lower cost than single image ads. This makes them the right format to start with when testing messaging or warming up a new target account list. Budget minimums: Below $2,000-$3,000/month it’s difficult to see statistically meaningful results. Gabriel Ehrlich’s red flag benchmark: if you’ve spent $3,500 with zero gated content leads, something is structurally wrong – the content, the offer, or the targeting. Attribution stack that actually works:

The three most important factors are: a hook that creates tension or makes a bold, specific claim in the first 1-2 lines; a body that’s personal, specific, and honest about failure or challenge; and a pull CTA (not a hard sell) with a link placed in the body of the post. Based on our analysis of 119 TLAs, 65% of top performers use first-person “I” voice and lead with a hook that challenges an assumption or opens a real story.
Between 150-400 words of post body text tends to outperform in our dataset. More important than length is density – every sentence should advance the argument or add a specific detail. Padding kills performance. The test: could you delete any sentence without losing meaning? If yes, cut it.
Not necessarily. Organic performance depends on your follower base and the algorithm. TLA performance depends on targeting relevance. The post that got 5 organic likes and drove 3 demos as a TLA is a real example – not an edge case. Evaluate posts on whether they address a specific ICP pain point, not on their like count.
From our 2026 LinkedIn ABM Benchmarks Report, the median CTR for TLAs is 2.68% – more than 6x higher than single image ads at 0.42%. But ignore the CTR number LinkedIn shows you in the Performance tab – it includes social actions. Use Clicks to Landing Page from the Engagement tab divided by impressions for the real figure.
Last-click attribution significantly undervalues TLAs because most buyers see the ad, don’t click, and convert later through a different channel. The most complete approach: UTMs on every link, an open-text self-reported attribution field on your forms, LinkedIn CAPI for aggregate conversion data, and a tool like ZenABM to track which target accounts are engaging with your TLAs at the company level and how that engagement correlates to pipeline over time.

