Marketing

Amazon's $68 billion ad machine now has access to 190 million Netflix viewers. Here's what it means for advertisers. Amazon's ad business makes $68 billion a year. Now advertisers can target right audiences on Netflix through expanded targeting capabilities via Amazon DSP. Starting Q2 2026, brands buying ads on Netflix through Amazon's platform can now use Amazon's shopping data to target their 190+ million viewers. Think about what this means. Amazon knows what a huge chunk of U.S. households buy, browse, and search for. Netflix knows what they watch. That data is now being combined for targeting. So a skincare brand can target someone who searched for serums on Amazon - while they're watching a show on Netflix. Here's why this matters: → Netflix made $1.5 billion from ads in 2025 and is targeting $3 billion this year  → Early tests are already beating previous benchmarks → A large share of new signups now choose the ad-supported plan. Till now, streaming ads were about showing up in front of millions and hoping it works. This changes that. Now brands can connect what people watch to what they actually buy. For anyone running ads, this is worth paying attention to. Shopping and streaming just became one ecosystem. How do you think this will change the way brands plan their ad budgets?

Markiplier just broke Hollywood's playbook, and most studios still don't understand what happened. His horror film Iron Lung opened this weekend to $21M worldwide. On a $3M budget. Self-financed. Self-distributed. Virtually zero marketing spend. Let that sink in for a second. No studio backing. No bank financing. No distribution deal. He wrote it, directed it, starred in it, and released it under his own Markiplier Studios. When it came time for theatrical distribution, he didn't go hat-in-hand to distributors. His fans called theaters directly and demanded they screen it. The result? All three major US theater chains. 3,000+ venues in the US and Canada. 1,200+ screens internationally. Opening weekend? He rivaled Disney's Send Help for first place, a film with a $40M budget. He beat Melania's theatrical release as well. 7x return on budget in three days. Here's what the entertainment industry needs to reckon with: The traditional model assumes you need studios for financing, agencies for packaging, distributors for access, and massive marketing budgets for awareness. Markiplier needed none of it. He had something more valuable, a direct, loyal audience built over a decade on YouTube. This isn't a one-off anomaly. It's a preview of where entertainment is heading. MrBeast is building a content empire. Ryan Trahan just launched a feature. KSI, Logan Paul, and others are expanding into media businesses. The creator-to-studio pipeline is real, and it's accelerating. The question for traditional entertainment companies isn't whether creators can compete at the box office. Markiplier just answered that. The question is: what's your strategy when the talent doesn't need you anymore?

In a MAJOR ruling for European copyright law, the Munich Regional Court has sided with Germany’s music rights society GEMA against OpenAI, finding that the company’s ChatGPT model unlawfully used copyrighted song lyrics in its training and responses. The decision, issued this morning, marks the first major European court judgment holding an AI company liable for using protected works without a licence. I got into AI through being Director of Legal Affairs and Regulatory Compliance in IMRO, the Irish counterpart of GEMA - and I know the people in GEMA - so this is very interesting to me. The case centred on GEMA’s allegation that OpenAI trained ChatGPT on its repertoire of German song lyrics, allowing the chatbot to reproduce works by artists such as Helene Fischer and Herbert Grönemeyer. The court agreed, concluding that the model’s ability to reproduce lyrics word for word demonstrated that the works had been used in training. It ruled that OpenAI is liable for copyright infringement and prohibited ChatGPT from reproducing lyrics from GEMA-represented artists unless a licence is obtained. The court also held that the European Union’s Text and Data Mining exceptions cannot shield generative AI systems that “memorise” and reproduce copyrighted material. This reasoning undermines one of the primary legal defences AI developers have relied upon in Europe. While damages will be determined in a separate proceeding, the court’s finding of liability alone sets a powerful precedent. OpenAI has announced plans to appeal. The 42nd Civil Chamber of the Munich Regional Court had indicated its position in September, when it observed that the model’s outputs could not be explained without training on copyrighted material. The final judgment confirmed that assessment. For the wider AI sector, the ruling suggests that AI companies operating in the European Union may need explicit licences for any copyrighted content used in model training or risk litigation. The decision also has regulatory implications. It aligns with growing momentum within the EU to enforce transparency and rights-holder protections under the AI Act and the Copyright in the Digital Single Market Directive. The GEMA v OpenAI ruling diverges sharply from Bartz v Anthropic in the United States. In Bartz, Judge Alsup found that AI training on copyrighted material could qualify as fair use, meaning no licence is required when the use is deemed transformative and non-substitutive. He viewed training as an analytical process that teaches the model general patterns rather than reproducing expression. The Munich court took the opposite view, holding that using protected works in AI training without permission constitutes reproduction requiring a licence. This illustrates the growing divide between the U.S. model, where fair use can exempt AI developers from licensing duties, and the European approach, which treats copyright as an enforceable economic right demanding prior authorisation.

TSMC posted a $440 million loss at its Arizona factory. American engineers called it "rigid, brutal, prison-like." Taiwanese managers complained about "lack of dedication and obedience." TSMC’s CEO Morris Chang saw this coming. "A very expensive exercise in futility," he called America's chip push. Taiwan doesn't just make chips. It breathes them. Three decades of alignment created something money can't buy. In Arizona, Americans clock out after shifts. In Taiwan, engineers sleep in the fab. In Arizona, decisions need consensus. In Taiwan, orders flow down. In Arizona, it's a job. In Taiwan, it's national service. Chang knew this at 55 when he started TSMC. The playbook worked because a nation aligned behind it: 1. Bet everything on survival Apple wanted impossible chips. Chang bet $9 billion in 2010 - half TSMC's cash. 6,000 people. 11 months. Round the clock. Because missing Apple meant Taiwan missing its future. 2. Never compete with customers Intel Corporation controlled everything. TSMC said: "We will never compete with our customers." When Nvidia shares five-year roadmaps, thousands protect them like state secrets. 3. Make enemies share factories Nvidia and AMD share production lines at TSMC. Works only when factory workers see both companies' success as Taiwan's success. 4. Turn precision into DNA TSMC's latest machines hit tin droplets 50,000 times per second. In Taiwan, this precision extends everywhere - emails, meetings, weekends. Not policy. Culture. 5. Compound for decades Every supplier grew with TSMC. Every university shaped curricula around them. Chang: "You cannot replicate this with subsidies. You cannot legislate dedication." 6. See the future through customers When Qualcomm fled IBM for TSMC in the late '90s, Chang knew IBM was doomed. Intel built walls. TSMC built bridges. TAKEAWAY: 2007: Intel rejected iPhone chip. Too low margin. Cost them mobile. Then AI. Then everything. Intel's real problem wasn't saying no to Apple. It was believing one company could do it all. Meanwhile, a 55-year-old built something stronger: a nation aligned around making everyone else successful. Today: Every ChatGPT query. Every iPhone. Every Nvidia chip. All TSMC. Not because Taiwan has the best engineers. Because Taiwan made engineering excellence a cultural value. And culture, unlike factories, can't be copy-pasted. — Want the full story of how TSMC became Nvidia's $1 trillion secret weapon? I went deep on the untold details: https://lnkd.in/epuWHu8B P.S. All research links, the audio clip, and the full archive are in the first comment below 👇

Lenskart recently got sued by Titan for something most marketers don’t even think twice about. Using a competitor’s brand name in hidden meta tags to steal search traffic. Yes, it was in the backend code. Yes, it worked. But it was also illegal. So when someone searches for your brand, your competitor might show up and get clicks instead, taking away the traffic. Under Section 29 of the Indian Trade Marks Act, this counts as trademark infringement. Lenskart admitted it, removed the tags, and got a legal warning. After spending 7+ years in digital marketing, I’ve seen this playbook being used across platforms- Meta Ads, YouTube tags, Google SEO… you name it. I’ve even seen agency briefs that suggest this as a "hack" to beat the competition. But let’s be clear: This isn’t smart marketing. This is legal risk. 👉 Don’t ride on another brand’s visibility. 👉 Don’t sneak their name in tags. 👉 Don’t let short-term traffic cost you long-term credibility. It’s high time marketers start focusing upon fair ways of managing business, because shortcuts like these might take you straight to COURT this time. What are your opinions on this lemme know… #digitalmarketing #lenskart #seo

𝟭𝟬 𝗥𝘂𝗹𝗲𝘀 𝗳𝗼𝗿 𝗛𝗶𝗴𝗵-𝗖𝗼𝗻𝘃𝗲𝗿𝘁𝗶𝗻𝗴 𝗪𝗲𝗯𝘀𝗶𝘁𝗲𝘀 🔥 Most product sites don’t convert. Here’s how to fix it: 𝟭/ 𝗨𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱 𝘆𝗼𝘂𝗿 𝗯𝘂𝘆𝗲𝗿 Before designing, talk to real users. Figure out what they want, what stops them, and what triggers action. → Talk to 5 signups: “What made you try it?” → Exit survey: “What’s stopping you?” → Watch session recordings → Skim support chats → Bonus: Buy someone coffee for quick feedback ✅ Example: Users say: “I just want to send invoices and get paid.” → Don’t write: “Smart billing software” → Say: “Send your next invoice in under 60 seconds.” 𝟮/ 𝗡𝗮𝗶𝗹 𝘆𝗼𝘂𝗿 𝗵𝗼𝗺𝗲𝗽𝗮𝗴𝗲 𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 Your layout needs: → Headline: pain point → Subheadline: curiosity → CTA: single action → Visual: product in action → Body: benefits > features ✅ Example: → “Hiring is broken.” → “Our AI recruiter finds top 3 candidates in 24h.” → “Try it free” → Demo video → “Save 10+ hours/week on screening” 𝟯/ 𝗠𝗮𝗸𝗲 𝘃𝗮𝗹𝘂𝗲 𝗰𝗹𝗲𝗮𝗿 𝗮𝗯𝗼𝘃𝗲 𝘁𝗵𝗲 𝗳𝗼𝗹𝗱 Most people won’t scroll. → What is this? → Who’s it for? → Why does it matter? → What should I do next? ✅ Example: → Don’t say: “AI-powered web builder” → Say: “Launch your landing page in 60 seconds” 𝟰/ 𝗙𝗼𝗰𝘂𝘀 𝗼𝗻 𝗼𝘂𝘁𝗰𝗼𝗺𝗲𝘀, 𝗻𝗼𝘁 𝗳𝗲𝗮𝘁𝘂𝗿𝗲𝘀 People don’t want “real-time sync.” They want fewer meetings, faster work. ✅ Example: → Don't say: “Real-time collaboration” → Say: “No more back-and-forth emails. Edit together live.” 𝟱/ 𝗔𝗱𝗱 𝗽𝗿𝗼𝗼𝗳, 𝗲𝗮𝗿𝗹𝘆 Trust builds conversion. → Logos → Quotes → Counters → Screenshots → Case studies ✅ Example: → “Trusted by 4,000+ teams at Meta, Notion, and Vercel” 𝟲/ 𝗥𝗲𝗺𝗼𝘃𝗲 𝗱𝗶𝘀𝘁𝗿𝗮𝗰𝘁𝗶𝗼𝗻𝘀 Stick to one goal and cut everything else. → No blog links → No footer clutter → No secondary CTAs ✅ Example: If your goal is “Try for free,” everything should lead there. 𝟳/ 𝗨𝘀𝗲 𝗯𝗲𝘁𝘁𝗲𝗿 𝗖𝗧𝗔 𝗹𝗮𝗻𝗴𝘂𝗮𝗴𝗲 Avoid vague buttons. Make CTAs feel easy + specific. ✅ Example: → Don't say: “Start now” → Say: “Try for free” 𝟴/ 𝗗𝗲𝘀𝗶𝗴𝗻 𝗺𝗼𝗯𝗶𝗹𝗲-𝗳𝗶𝗿𝘀𝘁 60%+ of traffic is mobile. If it’s clunky, it’s broken. → Large tap targets → Sticky CTAs → Short scroll → Preview breakpoints ✅ Example: → Desktop: CTA beside video → Mobile: CTA pinned bottom → Preview with Lovable 𝟵/ 𝗧𝗲𝘀𝘁 𝗺𝗼𝗿𝗲 𝘁𝗵𝗮𝗻 𝘆𝗼𝘂 𝘄𝗮𝗻𝘁 𝘁𝗼 One version is only one guess. ✅ Example: → “The fastest invoicing tool for freelancers” vs. → “Send your next invoice in under 60 seconds” → Ship both with Lovable 𝟭𝟬/ 𝗗𝗼𝗻’𝘁 𝘀𝘁𝗼𝗽 𝗮𝘁 𝘁𝗵𝗲 𝗖𝗧𝗔 Conversion isn’t the goal. The activation flow right after is. → Pre-fill content → Show a 60s walkthrough → Highlight one key action ✅ Example: User signs up → edits sample invoice → sends in 1 click LFG

We analyzed 4 million recruiting emails sent through Gem. Most get opened. But only 22.6% get replies. Half those replies are "thanks, but no thanks." We dug into what actually works. Here are 8 factors that drive REAL responses: 1. Strategic timing beats everything else - 8am gets 68% open rates. 4pm hits 67.3%. 10am lands at 67% - Most recruiters blast at 9am when inboxes are flooded - Avoiding peak times alone can boost your opens by 7-10% 2. Weekend outreach is criminally underused - Saturday/Sunday emails get ≥66% open rates consistently - Why? Empty inboxes. Zero competition. Candidates actually have time - Yet few recruiters send on weekends. Their loss is your gain 3. Keep messages between 101-150 words - Shorter feels spammy. Longer gets skimmed - You need exactly 10 sentences to nail the essentials - Every word beyond 150 drops performance 4. Generic templates kill response rates - Generic templates: 22% reply rate - Personalized outreach: 47% increased response rate - Even adding name + company to subject lines boosts opens by 5% 5. Subject lines need 3-9 words - Include company name + job title for highest opens - "Senior Engineer Role at [Company]" beats clever wordplay - 11+ words can work if genuinely intriguing, but why risk it? 6. The 4-stage sequence is optimal - One-off emails are dead. Send exactly 4 follow-up messages - You'll see 68% higher "interested" rates with proper sequencing - After stage 4, engagement completely flatlines. Stop there 7. Get the hiring manager involved - Having the hiring manager send ONE follow-up boosts reply rates by 50%+ - Yet most recruiters don't use this tactic - Weekend advantage: Minimal competition for attention 8. Leadership involvement is a cheat code - Role-specific timing (tech vs non-tech) matters - Technical roles: 3 of 4 best send times are weekends - Engineers check email differently than salespeople. Adjust accordingly TAKEAWAY: These aren't opinions. This is what 4 million emails tell us. Most recruiting teams are stuck in 2019 playbooks wondering why their reply rates won't budge. Meanwhile, recruiters who implement these 8 factors see dramatically better results. The data is right there. The patterns are clear. The only question is: will you actually change how you operate? Or will you keep sending the same tired emails at 9am on Tuesday? Your call.

The ABCs of Greenwashing 🌍 Greenwashing weakens trust and slows down meaningful progress. When companies present overstated or unverified claims, it creates confusion across markets, misleads stakeholders, and reduces pressure for real change. The cost is not only reputational, it also undermines the credibility of sustainability efforts more broadly. As sustainability becomes a business priority, the risk of misleading communication continues to increase. The pressure to report progress has led to claims that are not always backed by substance. Recognizing the signals of greenwashing is essential to ensure integrity in reporting, communication, and strategy. The ABCs of Greenwashing is a practical reference that outlines common red flags, from vague wording and selective data to unverifiable targets and weak transparency. These signs often appear in sustainability reports, websites, product labels, and corporate campaigns. There is a growing demand for better sustainability communication. However, clarity must come with accuracy. Narratives that focus on ambition without showing results raise concerns. Authentic communication requires alignment between commitments, measurable progress, and public disclosures. Expectations are shifting. Stakeholders, regulators, and investors expect more than general statements. Claims must be supported by credible data, meaningful metrics, and consistent reporting. The absence of independent verification or full scope analysis is no longer seen as acceptable. Regulatory frameworks are evolving to address this. New directives and standards are increasing pressure on companies to validate their statements with clear evidence. This shift will affect how sustainability is communicated, measured, and governed across sectors. Avoiding greenwashing requires clear internal structures, cross functional accountability, and regular review of communication practices. Sustainability performance must be integrated into operations, not added as a marketing layer. This is not a communication issue alone. It is a strategic and operational matter. Claims must reflect business decisions, investment priorities, and outcomes that can be tracked over time. The ABCs of Greenwashing is a reminder of the need for precision, transparency, and consistency. Improving the quality of sustainability communication is essential for building trust, reducing risk, and advancing long term business goals. #sustainability #sustainable #business #esg #greenwashing 

Netflix Is Going Physical — And It Might Just Rewrite the Experiential Playbook At Cannes Lions, Netflix unveiled more details about its boldest move yet in fan engagement: Netflix House — permanent, immersive venues launching this fall in Philadelphia and Dallas. Think “Stranger Things” escape games, “Squid Game” obstacle courses, “Wednesday” carnivals, mini-golf through your favorite titles, themed cocktails, exclusive merch, and yes — a TUDUM Theater to host fan events and screenings. But this isn’t just a cool activation. It’s a strategic pivot that’s worth unpacking: ✅ Strategic Intent: Netflix isn’t trying to build a theme park empire. This is about deepening emotional ties with fans, amplifying buzz, and future-proofing its brand beyond the streaming wars. These venues aren’t just fun — they’re fan conversion engines. ✅ A New Content Loop: Every attraction is designed to be shared — built for UGC, influencer walkthroughs, cosplay, TikToks, and viral moments. Fans become marketers. Data becomes feedback for future IP development. The venue becomes a living R&D lab. ✅ Not Just Eyeballs — Wallets: With exclusive merch, themed dining, and potential collabs (think Netflix x Funko or Netflix Bites F&B), the monetization flywheel is in motion. Even modest visitor volume could generate $25–30M/year per location — and that’s before you count the uplift in brand love or viewership. ✅ Global Signals: This could be the first step toward regional pop-ups, international localization (imagine a “Lupin” heist experience in Paris or “Money Heist” in Madrid), and even a Netflix-con-branded event model. It’s fandom scaled offline. 💡 Big Picture? Netflix is building something Disney mastered decades ago — real-world storytelling at scale. And if this works, it unlocks a new dimension: streaming IP that lives, breathes, and sells in the physical world. 📊 Our modeled impact: ⌙ ~1M visitors in Year 1 ⌙ 100M+ earned impressions ⌙ 10–15% churn reduction among local superfans ⌙ $5–10 lift in ARPU among engaged segments ⌙ Payback in ~3–5 years — with marketing ROI baked in 🎯 This isn’t about “content” anymore. It’s about building culture. Kudos to Marian, Greg, Josh, Mitzi, Emily, Nidia, Lauren, Jessica, Nikki and team. #Netflix #Cannes #Media #Licensing #ConsumerProduct

Website traffic was a valuable metric correlated to growth. Now it may be a vanity metric, not correlated to growth. Search has been disrupted. Visits to your website are declining. So, marketers - what now? The search landscape was already shifting (I talked about this at INBOUND last year). Now, the change is accelerating dramatically: - AI Overviews appear in 43% of Google searches – when they do, organic CTR drops by nearly 35%. - Google’s AI Mode and audio AI overviews are coming – they will cause clicks to collapse further. - More buyers are using LLMs to find information, ChatGPT search in Europe grew 3.7x in six months. So, what should marketers do? And how can AI help? 1. Be everywhere and diversify your channels The days of relying solely on Google search are way over. You need to show up on YouTube, LinkedIn, Instagram, podcasts, and in niche communities. The good news? AI makes multi-channel, multi-format content creation scalable – even for small teams. 2. Be specific with context In the past, broad informational content was the way to rank in Google. Today, buyers expect results deeply relevant to them, whether they’re on Google, LLMs, or Reddit. You need specific content that reflects your expertise and resonates with your buyers. 3. Optimize for conversion, not clicks Traffic was once the lever you could pull. Now, conversion is where the opportunity lies. AI enables you to deliver personal messages that drive better conversion. Don’t ask, “How do we get more blog visits?” Ask, “How do we convert more prospects into customers across all channels?” The changes in search are sending shockwaves across marketing teams and media companies everywhere. The era of traffic-based marketing is ending. But a new era full of opportunity is just beginning. Super exciting times for marketers to reinvent the playbook!