Exemples de lead magnets LinkedIn en performance marketing

J'ai passé des semaines à décortiquer Andromeda. J'en ai sorti un playbook interne de 43 pages pour produire des créas vraiment distinctes aux yeux de l’algo. Et j’ai décidé de l’offrir. Parce que 90% des marques qu’on audite brûlent leur budget sur des créas qui n'existent pas aux yeux de Meta. Je m'explique. Vous lancez 10 variantes par semaine. Nouveaux hooks. Nouvelles accroches. Nouvelles couleurs. Vous appelez ça du "creative testing". Meta appelle ça : la même publicité. Andromeda regroupe vos variantes en clusters. Si vos créas partagent le même concept, le même angle, le même persona cible, elles sont fusionnées. Une seule impression. Un seul apprentissage. Zéro diversification. Résultat ? → Vous brûlez du budget sur des tests qui n'en sont pas. → Vos CPAs explosent sans explication. → Vos "winners" meurent en 2 semaines. → Et vous pensez que c'est l'algo qui déconne. L'algo ne déconne pas. Il vous punit. Il punit la paresse créative déguisée en volume. Il punit les itérations cosmétiques. Il punit ceux qui testent des accroches au lieu de tester des visions du monde. Voici ce que j'ai mis dans le playbook : → La vraie grille de lecture de la diversité (ce qui compte vs. ce qui est ignoré) → 10 contre-exemples de diversité créative et 10 exemples de VRAIE diversité créative → Le test du floutage pour auditer vos créas en 10 secondes → Le Cascade Testing : Segment, puis Persona, puis Angle (l'ordre compte) → Les seuils de validation créa (dépense, volume, KPIs) → Une checklist Andromeda-friendly pour vos briefs C'est le système qu'on utilise chez DHS pour scaler sans exploser nos CPA. Commentez "PLAYBOOK" et je vous l'envoie en MP.

Google pushed modeled conversions even harder in Q1 2026. Search Terms reports are now 30 to 40% estimated data. Meta CAPI signal quality dropped to 68% across the accounts I audited last quarter. Most operators are making decisions on data that's lying to them. They just don't know which 30% is fiction. I watched a senior media buyer spend 5 hours last week pulling reports across Google Ads, Meta, and GA4 into one spreadsheet. Copy-pasting. Sorting. Guessing what's real. 5 hours. Every Monday. On modeled data. I ran the same accounts through my Claude system. Audit. Triage. Signal check. Done. 13 minutes. Zero guesswork. It found $11,400 in misattributed CAC the operator missed completely. 2,000+ search terms triaged in 60 seconds. Two Meta ad sets bidding against each other across 4 campaigns. → /conversion-audit on the real spend data → /search-term-triage with intent scoring → /signal-audit cross-checking GA4 + Meta + CRM → Anomaly flags ranked by dollar impact → A memory that learns from your corrections every week The operator went from 5 hours to 13 minutes per Monday. False positive rate dropped from 70% to near zero. I built this on real accounts. Real client money. Real spend. Now I'm showing you how to wire the same system. Thursday May 7. 12 PM ET. Live. Free. 90 min. Three Claude Code systems running on a real $140k/mo account. Live, blind, no rehearsal. 900+ operators already run pieces of this stack. 287 live seats registered. Comment "CLAUDE" and I'll DM you the workshop link.

This TikTok Shop system replaced a $450,000/year production team. We built a fully automated system that launches shoppable TikTok Shop content across hundreds of creator-style accounts fully with AI. It feels like running Facebook ads in 2017. It’s an AI content funnel driving nonstop organic sales — that: - Costs $0 in creators or UGC production - Takes 0 minutes to produce new content - Scales 10× faster than traditional creative teams - Runs with $0 ad spend — fully organic And the results? - 300% ROAS in 10 days - 6.2× engagement vs real UGC - 92 days of content produced in 1 hour - 98% of viewers couldn’t tell it was AI-generated Here’s the wild part: This entire system runs on a $100/month AI stack, replacing $15-50k+/month in creators, agencies, and production. What’s inside the stack: - Nano Banana Pro → UGC-style image generation - MakeUGC + Veo 3.1 → hyper-realistic UGC-style video creation - Kling 2.6 → motion control, shot consistency and replication at scale - AI Agents handle the rest → profiles, posting, scaling. No touchpoints. No delays. How it works: - Winning TikTok Shop content is scraped - Rebuilt with new hooks & angles - UGC-style videos are generated and posted daily Once a concept works… Pumping out high-performing variations at scale, posting nonstop across our AI account network, all driving traffic back to your TikTok Shop listings. No creators. No management. No scaling ceiling. Just AI content at scale. Want the full system? Comment “Tiktok” and I’ll send everything. (Must be connected) PS – Repost for early access to the full TikTok Shop system.

Ho Ho Ho! Merry Script-mas! 🎄 Yes, we just published a new Google Ads script. It scans your web display placements (GDN) to make a list prioritized for possible exclusion. Google brags that GDN includes over 2 million websites, but at some point that asset has become a liability, with ads serving across countless poor-quality websites. This can affect brand safety, performance – or often both. To help out, we compiled research from spamhaus, ICANN, and other authoritative sources to create a watchlist of 125+ top-level domains (for example .xyz, .zip, .vip) with elevated abuse patterns. This list gets referenced against your web placements from the Content Suitability report, as well as country-code TLDs that diverge from your location targeting, which could be a low relevance signal. The data is then available in pre-sorted tables and visualized, including a recent history of watchlisted placements in your ad account. We also include your current exclusions for reference. Because we use the Content Suitability report, this works not only for PMax but also for any campaigns generating display impressions (Demand Gen, Search campaigns with GDN opt-in, etc). Please note: not all websites using watchlisted TLDs are spam, and not all spam sites use watchlisted TLDs, however it’s a great first line of defense Get the script (free with an email registration): https://lnkd.in/gAexTAPs

Comment guérir la Claudite ? Cette maladie nouvelle qui pousse tout le monde à commenter "Claude, Claude, Claude" sur Linkedin. Je n'ai malheureusement pas la réponse. Ce que je vous propose aujourd'hui, c'est d'arrêter de demander les skills, hacks ou autres boomer magnet qui arrosent Linkedin pour créer VOTRE skill Claude en moins de 10 minutes. Vous apprendrez comment améliorer Claude pour en faire votre propre assistant, et aussi votre meilleur contradicteur. Pour ce faire, il y a peu de ressources nécessaires : - Un accès à ma dernière vidéo Youtube : https://lnkd.in/ep8DN_Jb - Un abonnement Claude - Un cerveau et un ordinateur connectés à Internet Ça se passe de l'autre côté, on se retrouve très vite pour le retour des posts liés au marketing digital. En attendant, vous connaissez la musique, commentez Claude, c'est bon pour le karma (et pour l'algo)

VEO 3 + Nano Banana Pro just KILLED manual content production. And I’m never going back. I used to spend hours scripting UGC videos, briefing creators, waiting on edits, praying for something usable. Now? My AI UGC stack does it better than I ever could. No creator delays. No $15K/month agencies. No burnout at video #47. After testing every major AI tool this year, here’s what actually works now: VEO 3 + Nano Banana Pro = UGC ads that scale without humans. What this combo can now do: • Turn a single product photo into dozens of platform-ready ads • Auto-generate hooks, angles, CTAs & captions • Create hyper-realistic talking-head avatars • Produce endless variations for TikTok, Reels & Meta • Keep everything on-brand across hundreds of creatives 500+ ad variations this week. Performance matched our best real-creator campaigns. The difference? I saved 12+ hours per day. I just packaged the entire system into a doc: • How to train your AI agents to produce native UGC • Prompts for viral hooks & scroll-stopping patterns • The workflow that outputs 20–50 ads in minutes • When humans should step in for creative QC • How to scale winning variations to $1k–$5k/day This is the same setup top DTC & info brands are using right now. Want the full system? Connect with me and comment “ADS” and I'll send you the system P.S. Repost for priority access

This TikTok Shop system replaced a $550,000/year production team. We built a fully automated system that launches shoppable TikTok Shop content across hundreds of creator-style accounts fully with AI. It feels like running Facebook ads in 2016. It’s an AI content funnel driving nonstop organic sales — that: - Costs $0 in creators or UGC production - Takes 0 minutes to produce new content - Scales 10× faster than traditional creative teams - Runs with $0 ad spend — fully organic And the results? - 220% ROAS in 10 days - 4.2× engagement vs real UGC - 90 days of content produced in 1 hour - 99% of viewers couldn’t tell it was AI-generated Here’s the wild part: This entire system runs on a $100/month AI stack, replacing $15-50k+/month in creators, agencies, and production. What’s inside the stack: - Nano Banana Pro → UGC-style image generation - MakeUGC + Veo 3.1 → hyper-realistic UGC-style video creation - Kling 2.6 → motion control, shot consistency and replication at scale - AI Agents handle the rest → profiles, posting, scaling. No touchpoints. No delays. How it works: - Winning TikTok Shop content is scraped - Rebuilt with new hooks & angles - UGC-style videos are generated and posted daily Once a concept works… Pumping out high-performing variations at scale, posting nonstop across our AI account network, all driving traffic back to your TikTok Shop listings. No creators. No management. No scaling ceiling. Just AI content at scale. Want the full system? Comment “Tiktok” and I’ll send everything. (Must be following) PS – Repost for early access to the full TikTok Shop system.

AI creatives crushed real footage, here's the proof. We ran AI-generated avatars against traditional UGC on Meta Ads for a water sports brand in Thailand. Same ad set, same audience, same budget. The algorithm decided. 4 AI creatives: 1,049 clicks, ฿1.74 CPC, 2.95% CTR. 5 UGC creatives: 237 clicks, ฿2.15 CPC, 1.19% CTR. 4.4x more clicks. 19% cheaper. 2.5x higher CTR. AI captured 82% of total campaign clicks while spending 78% of the budget, Meta's algorithm literally chose AI content over real footage because it converts better. I'm sharing my automated Ads Report powered by Claude AI, upload your Meta Ads export, and it generates a full performance breakdown with creative rankings, CTR analysis, and budget recommendations in seconds so you can make your arbitrage decisions instantly. 🟣🟣 Connect with me + comment "DOC" to receive it. 🟣🟣 #AIads #MetaAds #AIcreative #PerformanceMarketing #AIavatar #MediaBuying #PaidSocial #DigitalMarketing #AIforBrands #CreativeStrategy #AdCreative #CTWAads #WhatsAppMarketing #AIcontentCreation #GrowthMarketing #PaidMedia #SocialMediaAds #AImarketing #AdPerformance #CreativeAutomation

How do you produce 350+ video ads per hour without a creative team? You don’t. Our AI does. For years, top brands scaled with one unfair advantage: - Massive creative output - Hundreds of ad tests daily - Endless UGC variations But behind the scenes, it took: - Dozens of editors - Endless creator outreach - Sky-high agency retainers That model doesn’t work anymore — it’s too slow, too expensive, too fragile. So we built something different. We call it Sora V2 — the AI Ad Agent. It generates 350+ videos per hour with Sora-style quality, built for performance marketing, not cinematic fluff. This isn’t theory. It’s live. Campaigns are scaling right now. Here’s what Sora 2 handles: - Writes hooks & captions in seconds - Generates product demos, testimonials & lifestyle videos - Auto-edits for TikTok, Reels & Shorts - Publishes + tests ads 24/7 Just AI — producing, testing, and optimizing nonstop. For brands, that means: - UGC cost: $0 - Production time: 0 mins - Scale: 10× overnight - Output: 350+ ads/hour All built for one thing: conversion. The fastest-growing DTC brands and agencies are already switching to this system — scaling creative testing 10× faster than human teams ever could. Want the full playbook? Comment “AI” below and I’ll DM you the full breakdown. (must be connected)

We’re getting more conversions from AI-generated ads than traditional creatives now. and the brands winning today aren’t the ones with the biggest budgets… they’re the ones who learned how to scale AI ads before everyone else. most companies are still stuck on the old UGC model — slow shoots, inconsistent creators, expensive testing — while the real shift is happening right under them. the future of high-performing ads isn’t coming from creators or agencies. think about it… when a brand needs 50 new ad variations, they no longer hire a team — they prompt an AI ad engine that writes, edits, and produces everything in minutes. your ads either convert in this new ecosystem… or you get buried by brands that produce 10x more content at 1/10th the cost. right now, this is the Facebook Ads 2016 moment for AI-driven creative. AI ad systems are improving faster than any creator workflow before them — and almost no one understands how to fully optimize for them yet. this isn’t the same as using ChatGPT to write a script. AI ads require a totally different approach: a different performance structure, a different creative logic, a different way to engineer hooks, emotions, and outcomes. I just built a full guide that shows you how to create, optimize, and scale AI ads using the exact system top DTC brands are quietly adopting right now. this is the earliest you’ll ever be to a creative shift this big. want the AI ads playbook? connect with me and comment “Ads” I’ll send it over.

This AI Agent got 3M impressions + $597K in sales for $6K.... This AI Agent replaced a $25K/month SEO team with $1K/month in compute and turned organic search into a compounding revenue engine. Here’s what changed 👇 SEO is dead if you’re still playing Google-only. The winners now rank on: ✅ Google ✅ ChatGPT ✅ Perplexity ✅ Claude AI search layers (AEO + GEO) And almost no one is optimized for that. So we built an AI Agent that is. Before: → $25K/month on marketing → 6 months → Agencies, writers, backlinks → $0 attributable revenue After: → $1K/month running an AI Agent → 6 months → Fully autonomous AEO + GEO + backlinks execution → $597,000 in tracked revenue Here’s what the agent actually does: 👉 Scrapes competitors + AI answers (ChatGPT, SERPs, GEO layers) 👉 Rewrites pages to win answer slots, not just rankings 👉 Publishes daily across buyer-intent keywords 👉 Continuously updates content based on impressions + clicks 👉 Trains itself weekly on what converts, not what “ranks” 👉 Backlinks + directory listings. No content team. No waiting 12 months “to see if SEO works.” Just compounding distribution inside AI search. The unfair advantage... Once you’re embedded in AI answers, traffic doesn’t decay, it stacks. That’s why this isn’t SEO.... It’s an AI Growth Asset. If you’re spending $5K–$25K/month on marketing with unclear ROI, this replaces it. If you want this for your business comment "SEO Agent" and I will hook you up for only $1K per month - your mind will be blown!

NEVER hire Media Buyers again You must have seen headlines like this floating around LinkedIn these days. What these headlines won't tell you is that it's incredibly time consuming and complex to set up Claude skills, n8n workflows, or any of these "AI replaces everything" solutions. You'll be in a rabbit hole dealing with API integrations, terminals, and code requirements. AI wasn't meant to increase complexity or workload. It should be easy to use. Here's the other truth: → Media buying is part science, part intuition, part chaos management. → No AI is going to hop on a client call when ROAS tanks. → No AI is going to navigate a brand's messy attribution setup. But here's what AI can do: Give every media buyer a brilliant analyst who never sleeps That's what we built with GoMarble AI. Not a replacement. A partner. No code required. Imagine, as a media buyer, you need to audit a client's Google account. All you need to do is type "/", select the "Audit" prompt, and it will automatically (as shown in the video): → Connect your Google Ads, Meta Ads, GA4 → Pull spend + revenue across Google + Meta instantly → Show ROAS trends → Map funnel health: Reach → Engagement → Conversions → Retention Think of it as having a senior analyst on call at 2am when a campaign breaks. Media buyers aren't going anywhere. But the ones using AI as a co-pilot? They're going to outwork everyone else. Comment 'AGENT' & Repost and I’ll send you the link to our agent.

I just built a Claude skill that audits your entire Google Ads account in under 5 minutes 🤯 One prompt → a full account score, wasted spend breakdown, and a prioritized fix list telling you exactly what to change this week. All inside Claude Cowork. Perfect for DTC brands and agencies who are running Google Ads but have no idea how much budget is leaking. If you're managing Google Ads and your "optimization" process is logging in, staring at the dashboard, sorting by cost, and hoping you spot the problem before it costs you another $500... This audit skill finds it for you: → Connects to your live Google Ads data via MCP → Scores your account across 6 dimensions: wasted spend, search term quality, keyword health, quality scores, budget allocation, and creative performance → Calculates your exact wasted spend in dollars — search terms burning budget with zero conversions → Flags quality score issues dragging up your CPCs → Identifies keyword cannibalization across campaigns → Surfaces your top 5 highest-priority fixes ranked by budget impact → Generates a clean audit report you can hand to a client or share with your team No CSV exports. No pivot tables. No guessing where the money went. What you get: → A single Claude skill file you install once → An account health score (0-100) every time you run it → Exact dollar amount of wasted spend identified → Prioritized action list — not "optimize your account," but "pause these 12 search terms and save $847/month" → Works with any Google Ads account connected I'm giving away the full audit skill — the actual .md file you drop into Claude and run against your own account. Want it? Like this post Comment "SKILL" And I'll send it over (must be following so I can DM)

I’ve helped SaaS companies generate $50m+ with organic traffic. This is the playbook. Our clients do stuff like this: - Heymarket grew from 7.5k/mo > 45k/mo traffic - A marketing data platform 10x’d leads @ 40% lower cost - An SMM platform grew from 4k to ~1M monthly traffic - Nectar grew from 1k > 40k/mo traffic After 10 years of helping SaaS companies turn SEO into their most powerful channel… I’ve put together a guide that includes: 1 - SaaS’s “secret weapon” for SEO 2 - 4-week plan to deploy the secret weapon 3 - 80/20 to copy the BEST SaaS companies’ campaigns 4 - 12-mo full zero-to-hero SEO checklist 5 - Swipe files for important tactics These aren’t one-offs. Theses are the the things virtually ALL of the best SaaS companies do to open the floodgates of organic traffic. If you want the guide: 👉 Connect with me + comment “SaaS” below. I’ll send you a copy.

Most Google Ads audits miss the real problem. They look at bids. They look at creatives. They look at ROAS. They don’t look at leaks. I built a different audit layer. I export raw performance and search term data and audit it by intent. Not to optimize campaigns. To expose where money is escaping. What it uncovers: • Overlapping campaigns bidding on the same searches • Brand traffic inflating non-brand performance • High-spend terms with zero downstream revenue • Queries that never should have entered the funnel On one account, this revealed four hidden intent clusters draining budget every week. Same platform. Different lens. Most teams trust platform summaries. I trust raw signals. Google can only optimize what it understands. If your structure is noisy, the model learns noise. That’s why optimization feels random for most advertisers. Not because automation failed. Because control was never built in. Audit intent before you optimize spend. Like this post and comment TRACK and I’ll send you my Google Ads Audit Checklist so you can run this leak audit on your own account.

NEVER open Meta Ads Manager to launch a campaign again. 8 ads. 4 minutes. Straight from a Google Drive folder. Here's what the old workflow looked like: → Download creatives from Drive → Duplicate last week's winning ad set → Upload 8 videos one by one → Paste UTMs 8 times and hope none break → Hit publish, watch it crash on the 4th ad 33 clicks per ad. 264 clicks to ship 8. Two hours of execution tax for what should be a 5-minute decision. Then I tested GoMarble's new Agent Mode. One message: "Launch the 8 creatives in this Drive folder into my existing retargeting ad set, same copy pattern as last week's winner, UTMs per campaign, wait for my approval before going live." 3 minutes later, Agent Mode showed me the preview. I approved. Live on Meta. 4 minutes total. Ads Manager never opened. Strategy stayed on autopilot. This is the real shift. The job isn't getting faster at Ads Manager. It's removing the clicking entirely. The execution tax is dead. I put the 20 exact prompts I use to run a full Meta account through Agent Mode (launch, pause, scale, bulk URL swap, UTM fix) into a playbook. Want the full playbook + Agent Mode access? 1️⃣ Connect with me 2️⃣ Comment "AGENT" below + Repost I'll DM you the playbook + Agent Mode access.

VEO 3.1 + Nano Banana 2 just completely changed how I produce UGC. Honestly, I’m not going back. A few months ago my workflow looked like this: Write scripts → brief creators → wait for footage → request edits → hope one ad actually performs. Hours wasted. Money wasted. Energy wasted. Now? My AI UGC stack handles most of it. No creator delays. No $18K/month agency retainers. No burnout after making video #50. After testing pretty much every AI video tool this year, this is the setup that actually works: VEO 3.1 + Nano Banana Pro + MakeUGC = scalable UGC-style ads without the usual production chaos. What this combo can do now: - Turn a single product image into dozens of ad-ready videos - Auto-generate hooks, angles, captions, and CTAs - Create realistic talking-head style avatars - Produce endless variations for TikTok, Reels, and Meta ads - Keep branding consistent across hundreds of creatives This week alone we generated 550+ ad variations. And the crazy part? Performance matched some of our best real-creator campaigns. The difference? I saved 10+ hours every single day. So I documented the entire workflow: - How to train AI agents to produce native-feeling UGC - Prompts for viral hooks and scroll-stopping patterns - The workflow that outputs 20–50 ads in minutes - When humans should step in for creative quality control - How to scale winning ads to $2k–$6k/day This is the same type of setup a lot of DTC and info brands are quietly starting to use. If you want the full system: Connect with me and comment “UGC” and I’ll send it over. P.S. If enough people want it, I’ll also share the exact prompt stack we use. Repost for priority access.

most agencies sold their clients on AI in 2024. then they spent 12 months pasting GPT into reports. the report got smarter. the account did not. i spent 3 months building 18 claude code skills that run on the account itself, not on a slide about the account. last month i ran one of them on a real $140K/mo google ads account. caught $47,200 in misattributed CAC in 6 minutes. four months of dashboards lying. smart bidding optimizing on garbage signal. if the signal is wrong, the algo learns wrong. that is the whole game. 3-min walkthrough of the full stack: https://lnkd.in/eEPN6nnT paidmedialab.com/start comment "audit" if you want me to point you at the door that fits your spend tier.

i made claude run my monday google ads review today. not write ad copy. not summarize a dashboard. run the actual review. the one media buyers do every monday: - check spend - check cpa - scan campaigns - pull search terms - check pmax - check tracking - write client notes and detailed reports - flag what needs attention manual version: 45 minutes per account. claude workflow: about 10 minutes. every monday. if you want it comment "SKILLS" i'll drop it in your DM! (must be connected)

The most expensive 15 minutes in Paid Media is the ones you never spend checking your conversion setup. here is what i found on a $970K account last week. step 10 of a 10-step funnel had no tag. the GTM migration in march created tags for steps 1 through 9. step 10 was skipped. the trigger existed. zero tags connected to it. $34,000 in PMax spend. zero completed-application data. PMax was flying blind on the conversion that mattered most. same account. bing had 86 funded customers worth $446,000 flowing from the CRM. the "include in conversions" toggle was off. one click. the algorithm could see funded customers for the first time. same account. $4,300/mo going to a single search query for prospects who could never qualify for the product. $51,600/yr recovered from one negative keyword. three fixes. under 2 hours total. the campaigns were not bad. the tracking was not complete. if you have not audited your conversion setup since your last GTM migration, check it. the things that break are never the things you expect. if you spend on google ads and have not audited tracking since your last gtm migration, comment “CHECKLIST” and i’ll send you the 100+ point conversion tracking audit checklist.

R.I.P. attribution dashboards. Triple Whale starts at $1,800/yr. Northbeam starts at $18,000/yr. Cortana, Dreamdata, Rockerbox, Measured all want $30K+/yr. across 50 accounts i audited last quarter, every single one had at least one broken pixel feeding the dashboard. average ROAS gap vs actual bank revenue: 23%. these tools don't fix anything. they pretty up whatever signal you give them. if the pixel is broken, the dashboard makes the lie look pretty. last live audit i ran on a $200K/mo DTC brand: triple whale said 4.1x ROAS. the bank account said 2.3x. $47,200/mo of CAC was being optimized against numbers that didn't exist. the team had been scaling spend for 6 months on phantom performance. the campaigns were never broken. the data was. 3 checks before you trust ANY attribution tool: 1. open your ad platform. pull last month's revenue.   open your bank or CRM. pull actual deposited revenue.   gap over 15%? your dashboard is reporting fiction. 2. test the pixel firing. open developer tools, place a test order, count the conversion event fires.   should be exactly 1. 3. check offline conversion import frequency.   not running daily? your refunds and quality scores are missing from the model. dropping the full 90-second breakdown of the signal chain at noon ET tomorrow. walks click → site → CAPI → platform → algorithm. plus the audit i run before recommending any attribution tool. comment "ATTRIBUTION" and i'll DM you the link the second it goes up.