Marketing

WOW - Claude Code is an analytics beast. I just had CC (via Google Workspace MCP) analyze mountains of my inbound emails from 2024 and 2026 to find patterns of business pitches, buyer options, and sales strategies. I reviewed everything and added my behind-the-scenes intel for each piece. 📌 Save this post. My takeaways: 1. AI is the premium differentiator 👉 In 2024, companies pitched pretty generic sounding "data tools" or storage upsells. 2026, AI features were the main premium unlock 💡 AI business insight: every company can offer AI features or products (whether you should is another question) 2. "Build and create" over "read and consume" 👉 2024 premiums were all about receiving or reading or getting: read this exclusive article, watch this MasterClass, attend this event. 2026 premiums are about producing. Seeing a trend in words like write, edit, dictate, create, deploy, build 💡 AI business insight: people are overwhelmed with info & want more agency, control, and externalization 3. Team and enterprise scaling 👉 The main pitch for products (especially AI products) shifted from "get your personal edge" to "multiply this across your org" 💡 AI business insight: people feel like superusers & realize non-adopters are pulling the average down. They want to raise the system. Executives, this is a system year 4. Buyer also becomes the monetizer 👉 Similar to point 2, but seeing a lot more paths toward monetization being pitched, not just tools to consume. A lot more “hey, you can use us to make even more money” messaging 💡 AI business insight: people are worried about revenue paths & want to diversify. AI messaging is moving away from productivity toward top-line growth (took them long enough!) 5. Compliance and trust as premium features 👉 Lots of companies highlighting compliance, trust, security, or even running trust summits 💡 AI business insight: decision makers still need to check certain IT boxes. Trust in AI is not guaranteed in B2B GTM 6. Human time 👉 Claude actually found the opposite in its analysis (ie that in 2024, people were pitching human time and elite access a lot more & 2026 was more about access to 24/7 AI twins). I'm not confident that's happening across the board. Might vary by industry or stage? Still seeing a lot of office hour offerings from startups, more FDE-sounding language 💡 AI business insight: if your industry has always been built on human access & relationships, double down for your highest value customers. Run more AI avatar tests in market for 24/7 brand access 🔮 My main prediction: the "free tier" of all these pitches will be shockingly capable. It has to be. Raw AI access is racing to free. So if free tier has access to the greatest models or content (maybe not fully unlimited SOTA yet, especially in image/video/3D), then premium becomes more about autonomy (high-quality AI that works while you sleep), orchestration (complex systems and integrations), growth enablement, & trustworthiness

I used to think charging less would get me more clients. After my trip to the US I realised it just made them trust me less. when i was cheap, clients questioned everything. "why this approach?" "can we try something else?" "i'm not sure about this." so when i raised my rates, they trusted my decisions completely. same work. different psychology. so here's what i've basically realized about pricing: when someone sees a low price, their brain doesn't think "great deal." it thinks "what's the catch?" they start looking for problems. inexperience. desperation. corners being cut. low prices trigger fear of loss, not excitement about savings. but when they see premium pricing, something else happens. "if they can charge this much, they must deliver results." "other people are paying this, so the value must be there." "the risk of not solving this problem costs way more than the investment." premium pricing signals confidence in your work. think about it. rolex doesn't make better watches from a functionality standpoint. but the price tells you everything about what owning one means. same thing with services. a premium project isn't necessarily 10x better in execution. but the price signals experience, systems, proven results. and here's the shift that changed everything for me: i stopped anchoring clients to the price and started anchoring them to the outcome. not "this costs X" but "this will generate Y for your business, and the investment is X." when they're thinking about ROI, the price becomes secondary. your pricing isn't just a number. it's a signal to the market about who you are and what you deliver.

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 👇

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 

Warner Bros. Discovery is officially splitting into two companies. And the move may reshape the entertainment landscape as we know it. Announced today, WBD will separate into: 🎬 WBD Streaming & Studios – Max, HBO, Warner Bros. Pictures, DC, and content production. 📺 WBD Global Networks – CNN, Discovery, TNT Sports, and other linear TV assets. David Zaslav will lead the Streaming & Studios entity, while CFO Gunnar Wiedenfels takes over Global Networks. This isn’t just operational restructuring—it’s a signal of strategic discipline. In a media world demanding agility and specialization, WBD is choosing focus over entanglement. For years, media conglomerates tried to be everything at once. Today’s move suggests the next era belongs to leaner, purpose-built organizations: one built for growth, another for value extraction. 🔍 Key implications: ⌙ Investor signaling: The market rewarded the move immediately. WBD stock jumped on the clarity and perceived unlock of future deal potential. ⌙ Deal logic accelerant: Each company now has clearer financials and objectives, making it easier to explore mergers, content alliances, or targeted asset sales. ⌙ Creative empowerment: The Streaming & Studios entity can now prioritize storytelling and platform scale without the drag of managing linear economics. Expect more risk-taking, franchise building, and talent-led bets. ⌙ Global strategy divergence: WBD Global Networks, still strong internationally, may double down on licensing and local partnerships, while Streaming leans further into global IP as a differentiator. This also raises bigger questions about how legacy assets are valued. Linear TV isn’t dead—but it’s no longer the center of the media equation. This move implicitly reframes cable and broadcast as supporting players in a world increasingly dominated by platforms, brands, and data-rich direct-to-consumer models. 📈 In short: WBD didn’t just split its balance sheet—it split its future. One side is now primed to scale storytelling in a streaming-first world. The other is free to optimize legacy economics without pretending it’s still the future. This may be WBD’s most forward-looking move since the merger. The media chessboard just changed.

Most brands spend a lot on media, but treat landing pages as an afterthought If you’re running ads and sending traffic to a homepage or a poorly built landing page, its almost criminal. Specially when gen AI has reduced the cost and time for content creation drastically Here’s how to get landing pages right. Consistently. 1. Match Intent, Not Just Aesthetics The #1 job of a landing page? Continue the conversation you started with your ad •If your ad says “energy efficient fans”, the landing page should show highlight this feature front and center •If your Google ad targets “Mixer Grinders under ₹5000,” don’t show ₹8000 models on the page. Message match > Visual design 2. Keep the Hero Section Clean & Focused Above-the-fold matters. You need to have •Clear headline – Say what the product is and why it’s special. •Key benefits – 3 crisp points max. •Visuals – High-quality product image or demo video. •CTA – One action. Not three. Buy Now,” “Book a Demo,” or “Know More”—but pick ONE 3. Product Benefits, Not Just Features Nobody cares that your mixer uses XYZ motor tech. I mean they do care but only if they care how it helps them They care a lot more that the mixer has a coarse mode which enables silbatta like texture resulting in great taste And that BLDC or intelligent motor tech enables it 4. Solve for Trust People are skeptical by default. Give them reasons to believe •Ratings & Reviews – Show real customer ratings (4.5 stars? Flaunt it). •Media Mentions – “As seen on The Hindu / NDTV” works. •Certifications – BEE 5-Star? BIS approved? Display badges. •Guarantees – Free returns? Warranty? Mention clearly 5. Speed & Mobile Optimization Today at least 80 percent of your traffic is mobile. If your landing page loads in 4 seconds, you’ve lost half. Aim for <2s load time. Avoid fancy animations that slow things down. Test your page on Mobile (3G/4G) and in all browsers Chrome, Safari etc 6. Minimize Distractions A landing page is not your website. •No top nav bars with 7 menu items. •No footer clutter. •No exit doors—except the CTA you want. Keep it focused. Keep them moving toward action 7. Strong CTA (Call to Action) •Make it obvious. One clear button. •Use actionable language: “Get My Free Sample,” “Book a Demo,” “Shop Now.” •Repeat CTA 2-3 times as they scroll, especially after key benefit sections. 8. A/B Test, but with caution: Gen AI makes it very easy to do so. Test •Headlines •CTA text and colors •Images vs Videos •Long-form vs Short-form copy But get the fundamentals of A/B testing right. You need statistically significant sample sizes for each test A good landing page doesn’t sell the product by itself. But It removes friction so the product has a better chance of selling And when done right, your CAC drops, your ROAS climbs, and your ads finally start working to their fullest potential

Haldiram understood something that no one else did: a product isn’t just what it tastes like—it’s how it makes people feel. And that’s where the magic began. Bhujia was common. Every corner of Rajasthan had someone selling it. But Haldiram didn’t just want to sell bhujia. He wanted it to mean something. So, he gave it a name that would stand out in the crowded bazaars. Not just any name—Dungar Sev, after Maharaja Dungar Singh of Bikaner. Think about it. A simple snack, suddenly infused with an air of royalty. What was once just fried sev became a symbol of status, a delicacy that carried the weight of a Maharaja’s name. The people of Bikaner didn’t just buy bhujia anymore. They bought Dungar Sev. And unknowingly, they bought into an idea—a brand. At the time, words like ‘branding’ and ‘marketing strategy’ weren’t common parlance in India. There were no MBAs, no advertising agencies plotting out product positioning. But Haldiram did what modern marketers today struggle to achieve: he gave an everyday product a unique identity and a powerful story. Naming the bhujia after royalty wasn’t just clever. It tapped into something deeply psychological—the human desire for exclusivity. People weren’t just eating a snack. They were consuming something elite, something tied to the grandeur of a kingdom. But Haldiram didn’t stop there. He understood something even more profound: consistency builds trust. As the demand grew, he ensured that no matter where his bhujia was sold, it tasted the same, had the same texture, and carried the same name. And just like that, an unorganized market started getting shaped by a singular force—brand recognition. An iconic Indian-born brand

10 Ways to Use ChatGPT to Improve Your Copy: (With Simple Copy-and-Paste Examples) 1) Trimming Down Goal: Condense your copy for clarity and impact. Focus on: Complex sentences Redundant phrases Long paragraphs Example prompt: "Trim down this [phrase/sentence/paragraph] of my copy." 2) Finding Word Alternatives Goal: Find better synonyms for certain words to enhance readability and engagement. Look to replace: Fillers Jargon Clichés Adverbs Buzzwords Example prompt: "Provide [adjective] alternatives for the word [word] in this copy." 3) Doing Research Goal: Gather detailed information about your target audience to tailor your copy. Consider: Likes Habits Values Dislikes Interests Behaviors Challenges Pain points Aspirations Demographics Example prompt: "Create an ideal customer profile for [target audience]." 4) Generating Ideas Goal: Brainstorm multiple copy elements to keep your content fresh and engaging. Do this for: CTAs Stories Leads Angles Headlines Example prompt: "Generate multiple [element] ideas for this copy." 5) Fixing Errors Goal: Identify and correct any errors in your copy to maintain professionalism. Check for: Spelling mistakes Grammatical errors Punctuation issues Example prompt: "Check this copy for any [type] errors and suggest corrections." 6) Improving CTAs Goal: Make your call-to-actions more compelling and click-worthy. Play around with: Benefits Urgency Scarcity Objections Power words Example prompt: "Give me [number] variations for this CTA: [original CTA]." 7) Studying Competitors Goal: Gain insights from your competitors' copy to improve your own. Analyze their: CTAs USPs Offers Leads Hooks Headlines Example prompt: "Provide a breakdown of [competitor]'s latest [ad/email/sales page]." 8) Nailing the Voice Goal: Refine the tone and voice of your copy to align with your brand and audience. Consider: Target audience Brand guidelines Advertising channel Example prompt: "Make this copy [adjectives] to suit [target audience]." 9) Addressing Objections Goal: Anticipate and address potential customer objections to increase conversion rates. These could be about: Price Quality Usability Durability Compatibility Example prompt: "Analyze this copy to find and address potential objections." 10) A/B Testing Goal: Create variations of your copy's elements to determine what works best. Try different: CTAs Hooks Angles Closings Headlines Headings Frameworks Example prompt: "Generate variations of this [element] for A/B testing: [original element]."