Creating Impactful Messaging

The 6 levels of messaging every product needs 👇 Strong product messaging isn't just about connecting with different stakeholders - it's about building a foundation that scales: 1. Brand Level Define who you are, why you exist, and the promise you deliver to the market. 2. Product Level Your unique value, differentiation, and the story that makes you memorable. 3. Audience Level Address your audience's pain points, goals, and what they need to get the job done. 4. Sales Level Show clear benefits, ROI, and confidently handle objections. 5. Technical Level Provide detailed answers for the technical decision-makers who need specifics. 6. Customer Level Build advocacy through success stories and post-purchase engagement. Each level builds on the previous one, creating a coherent messaging architecture. Skip a level, and the whole structure weakens. Most companies rush to talk features without this foundation. The result? Messaging that crumbles under pressure. What level do you think is hardest to get right? 💭 [Additional resource = Product Messaging Framework: https://lnkd.in/e_Q5J6tE]

Translating health science into understandable and clear health advice isn’t easy, especially on social media. And it’s not about what algorithms want us to do to engage their users. It’s about how people think. In the past three years, the World Health Organization worked on a project with Meta, using their Brand Lift Study tool to test how different kinds of message framings, built on behavioural science theories, affect how people perceive risk and act on it. In the paper below, we highlight a measles vaccination experiment in which we targeted parents of young children. We compared two types of messaging: - Verbatim: fact-based and precise “1 in 1,000 children who get measles will die.” - Gist: essence-based and emotional “Some children who get measles will die.” Both are accurate, but they communicate risk differently. Here are a few reflections from the process: - We need to design social media public health campaigns with behavioural science lenses, not just communication instinct. - We need to evaluate impact beyond likes and shares; focus on understanding and intention. - We must keep messages evidence-based but human; clarity matters as much as accuracy. What matters most isn’t how much information we share, but how people make sense of it. Small shifts in framing can change how people understand risk and how they act on it — which is the ultimate objective of public health communication. WHO project team: Simon Williams Elena Altieri Mohamed Gulaid Giselle Miguens Lisa Menning Karin Stein, MD, MScPH

I've been reflecting on one major trend from last year that I feel will be hard to ignore in 2025: Gen Z’s relationship with brands and social media. This generation doesn’t just consume content, they drive it. And they do so with a level of authenticity and transparency that demands our attention. For Gen Z, brand loyalty isn’t built on flashy ads or influencer endorsements alone. It’s about values. It’s about knowing what the brand stands for and aligning with causes they care about: be it sustainability, inclusivity, or social justice. Here’s how I’ve been thinking about this shift as an entrepreneur: For Gen Z, being true to themselves is really important. They want brands that embrace uniqueness and support personal expression. To connect with them, we need to be authentic and offer products and messages that let them express who they really are. Social Media is the New Word of Mouth: If you’re not engaging in the conversations Gen Z is having on social media, you’re missing out. They trust their peers and online communities more than traditional advertising, and their feedback is immediate and powerful. Experience Over Projection: For this generation, it’s not just about seeing an ad but engaging with a brand in a meaningful way. Whether through personalized experiences, interactive campaigns, or exclusive content, creating a connection is more valuable than ever. Gen Z is not just shaping the future of business but is redefining what it means to build loyalty and trust. Is your brand ready for this shift?

The biggest problem with LLM-based apps? It’s not the model. It’s not the framework. It’s not even the prompt. It’s everything around them. We’re not just calling an API. We’re integrating a stochastic system into a world that expects deterministic behavior. 𝗟𝗟𝗠𝘀 𝗮𝗿𝗲 𝗻𝗼𝘁 𝗱𝗲𝘁𝗲𝗿𝗺𝗶𝗻𝗶𝘀𝘁𝗶𝗰 𝗰𝗼𝗺𝗽𝗼𝗻𝗲𝗻𝘁𝘀 Same prompt ≠ same output. They predict tokens, not answers. You don’t pass parameters—you design prompts. That makes it hard to predict outputs, validate correctness, or reproduce behavior. 𝗣𝗿𝗼𝗺𝗽𝘁𝗶𝗻𝗴 𝗶𝘀𝗻’𝘁 𝗽𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴 No function signatures. No modular reuse. Tiny prompt changes can break results. Long prompts increase latency. And prompts don’t always work the same across workflows or chains. 𝗥𝗲𝘁𝗿𝗶𝗲𝘃𝗮𝗹 𝗮𝗱𝗱𝘀 𝗺𝗼𝗿𝗲 𝘂𝗻𝗰𝗲𝗿𝘁𝗮𝗶𝗻𝘁𝘆 In RAG, you’re combining semantic search, reranking, and formatting. Each step adds noise. You’re generating over possibly irrelevant context. Now the system is doubly stochastic: retrieval + generation. 𝗧𝗲𝘀𝘁𝗶𝗻𝗴 𝗟𝗟𝗠𝘀 𝗶𝘀𝗻’𝘁 𝘀𝘁𝗿𝗮𝗶𝗴𝗵𝘁𝗳𝗼𝗿𝘄𝗮𝗿𝗱 There’s no .assertEqual(). Heuristic metrics are flawed. Human evals are expensive and inconsistent. Even stable outputs might still be wrong. 𝗦𝗰𝗮𝗹𝗶𝗻𝗴 𝗺𝗮𝗸𝗲𝘀 𝗶𝘁 𝗲𝘃𝗲𝗻 𝗵𝗮𝗿𝗱𝗲𝗿 LLMs are slow, expensive, and limited by token windows. You need chunking, caching, windowing, reranking, fallback logic. You’re not calling a model—you’re orchestrating a distributed system. 𝗗𝗲𝗯𝘂𝗴𝗴𝗶𝗻𝗴 𝗶𝘀 𝗮 𝗯𝗹𝗮𝗰𝗸 𝗯𝗼𝘅 No stack traces. No explanations. Logs give you input/output, not reasons. Prompt tweaks can cause side effects far from where you made the change. 𝗘𝘅𝗽𝗲𝗰𝘁𝗮𝘁𝗶𝗼𝗻𝘀 ≠ 𝗿𝗲𝗮𝗹𝗶𝘁𝘆 People expect memory, perfect instructions, stable outputs, and truth. LLMs forget, hallucinate, and drift based on sampling. Without scaffolding, they feel brittle and inconsistent. 𝗜𝗳 𝘆𝗼𝘂'𝗿𝗲 𝗹𝗼𝗼𝗸𝗶𝗻𝗴 𝗳𝗼𝗿 𝘃𝗶𝗯𝗲𝘀, 𝗹𝗲𝘁 𝗺𝗲 𝘁𝗲𝗹𝗹 𝘆𝗼𝘂 𝗶𝘁'𝘀 𝗼𝗻𝗹𝘆 𝗽𝗮𝗶𝗻 LLMs are probabilistic pattern matchers—not deterministic components. Building with them means thinking in systems, not functions. It means controlling chaos, not eliminating it. If your LLM system feels fragile, you’re not alone. You’re just facing reality. And it’s solvable—if you design for it. ♻️ Repost to share these insights. ➕ Follow Shivani Virdi for more.

🧠 LLMs still get lost in conversation. You should pay attention to this, specially when building AI Agents! A new paper just dropped, and it uncovers something many of us suspected: LLMs perform way worse when instructions are revealed gradually in multi-turn conversations. 💬 While LLMs excel when you give them everything up front (single-turn), performance drops by an average of 39% when the same task is spread across several conversational turns. Even GPT-4 and Gemini 2.5 stumble. Why? Because in multi-turn chats, models: ❌ Make premature assumptions ❌ Try to “wrap up” too soon ❌ Get stuck on their own past mistakes ❌ Struggle to recover when they go off-track The authors call this the “𝗟𝗼𝘀𝘁 𝗶𝗻 𝗖𝗼𝗻𝘃𝗲𝗿𝘀𝗮𝘁𝗶𝗼𝗻” effect, and it explains why LLMs sometimes seem great in demos, but frustrating in real-world use. 🔍 If you’re building agentic AI products, this is a wake-up call. Most evaluation benchmarks don’t reflect how users actually interact with messy, evolving, often underspecified prompts. 📄 Paper link in comments.

Small variations in prompts can lead to very different LLM responses. Research that measures LLM prompt sensitivity uncovers what matters, and the strategies to get the best outcomes. A new framework for prompt sensitivity, ProSA, shows that response robustness increases with factors including higher model confidence, few-shot examples, and larger model size. Some strategies you should consider given these findings: 💡 Understand Prompt Sensitivity and Test Variability: LLMs can produce different responses with minor rephrasings of the same prompt. Testing multiple prompt versions is essential, as even small wording adjustments can significantly impact the outcome. Organizations may benefit from creating a library of proven prompts, noting which styles perform best for different types of queries. 🧩 Integrate Few-Shot Examples for Consistency: Including few-shot examples (demonstrative samples within prompts) enhances the stability of responses, especially in larger models. For complex or high-priority tasks, adding a few-shot structure can reduce prompt sensitivity. Standardizing few-shot examples in key prompts across the organization helps ensure consistent output. 🧠 Match Prompt Style to Task Complexity: Different tasks benefit from different prompt strategies. Knowledge-based tasks like basic Q&A are generally less sensitive to prompt variations than complex, reasoning-heavy tasks, such as coding or creative requests. For these complex tasks, using structured, example-rich prompts can improve response reliability. 📈 Use Decoding Confidence as a Quality Check: High decoding confidence—the model’s level of certainty in its responses—indicates robustness against prompt variations. Organizations can track confidence scores to flag low-confidence responses and identify prompts that might need adjustment, enhancing the overall quality of outputs. 📜 Standardize Prompt Templates for Reliability: Simple, standardized templates reduce prompt sensitivity across users and tasks. For frequent or critical applications, well-designed, straightforward prompt templates minimize variability in responses. Organizations should consider a “best-practices” prompt set that can be shared across teams to ensure reliable outcomes. 🔄 Regularly Review and Optimize Prompts: As LLMs evolve, so may prompt performance. Routine prompt evaluations help organizations adapt to model changes and maintain high-quality, reliable responses over time. Regularly revisiting and refining key prompts ensures they stay aligned with the latest LLM behavior. Link to paper in comments.

I’ve reviewed 3500+ LinkedIn posts in 2025 so far that have generated over 25 million impressions. Here’s the Hook Framework I give our team that you can copy so you get people to actually read your content:  1. Work out the post type first Every post should be clearly framed as either a story post or an insight-driven post. Not both. Story posts should include: -Visual detail -Transformation -Emotional stakes -First-person voice Insight posts should: -Start with real-world context or credibility and call out their ICP (e.g. “Last week, I spoke with a founder scaling a 10-person AI company…”) -Include actionable IP or insider knowledge (make it feel exclusive) -Highlight why someone should care or listen (what is in it for the reader?) 2. The hook must earn attention Use transformation + numbers + emotion (e.g a client’s hook: “We just hit 7-figures. But two years ago, I had $0 and was scammed by my first client.”) Avoid generic or vague phrases — specificity signals credibility Pack the hook full - don’t space it out - tighten for impact Lead with the line that answers: Why should I keep reading this? 3. Show don’t tell Work out what you want to be associated with and make sure the hook signals this. Reference industries and disciplines to anchor your expertise with hard numbers or named examples (e.g. “Through influencer marketing, we scaled Gamma from 3M to 50M users in under 12 months — here’s the 5-step method that got us there.”) 4. Reframe generic phrases Instead of “I often get asked…”, say: “Here’s the question I get asked most on 1:1 $1000/hour strategy calls with (target persona)...” This makes the post feel more like privileged insight than common advice - and shows you are a real person growing a real business. 5. Speak directly to your audience Call out the target reader (ICP) explicitly (e.g. “Here’s why AI tech brands should listen”) Tailor examples to their world and challenges. Tapping into their desires/goals (getting to 100m ARR) and their pain/problems - show you understand that specific persona. 6. Packaging matters Consider wrapping key ideas into a clearly labelled methodology / IP / frameworks (e.g. “Here are the 5 Authority-Building™ steps we used to scale…”) and showing what is in it for the reader. Makes it feel more savable and shareable. 7. Use names that have existing attention Use people’s names — and give them context (why they matter) Leverage their existing attention - but make it clear & obvious why someone should pay attention to them. Eg if referencing Stan Store, explain why they matter using numbers Example of client hook: “Stan Store is on track for $100M ARR. Here’s how they’re using influencer marketing differently.” Remember, hooks matter.  But only if what follows is genuinely great, relevant, unique content. (Save this & send it to your marketing team!)

“If you won’t share it on your own Instagram story, don’t post it!” This was our content team’s philosophy at Dr. Vaidya's by RPSG Group. Marketing used to be simple: Big budget = Big impact. Gen Z changed that forever. The marketing stack now looks completely different, and brands must understand this to succeed. Look at the numbers: - India has one of the world’s youngest populations with an average age of 28. - We have 37.7 crore GenZs. - They influence 43% of household spending decisions. - By 2030, they'll drive $1.4 trillion in consumer spending. This shift has made traditional marketing ways pretty much irrelevant. Today, marketing isn't measured in ROI reports, but in memes and reels. If your campaign isn't shareable, it's forgettable. Here’s what I’ve seen this means for brands: 1. Authenticity > Production Value A creator with 100K loyal followers drives more sales than a Bollywood celebrity with millions. Trust beats reach. Finding those true ‘influencers’ — the needle in the haystack — will determine the success of your content team. 2. Local > Global Brands can't just translate Hindi to Tamil anymore. What works in Mumbai might not click in Madurai. Each community needs its own cultural context, and understanding this is what’ll make your brand connect. 3. Tribes > Demographics Forget age and income brackets. Today's segments are sneakerheads, plant parents, and coffee enthusiasts. Communities are the new micro-markets. When I tell someone I play pickleball, the conversation changes. 😂 4. Production Value Doesn’t Matter I remember telling my dad he should do reels for his luxury jewelry brand. He said, “Do one video but do it very well”. That’s not how it works. Even content shot from a phone will trend. The brands that understand this are growing 3x faster. It's not about marketing to Gen Z anymore. It's about learning from them! Do you agree? Have you seen this play out? PS: Shohit Raina ran content for us at DRV. Saw him again after a while last week in Abu Dhabi. :) #india #marketing #content #brand 

All brands are trying to decipher GenZ. But most are getting it wrong. Let me explain. They say – GenZ wants premium. They want aspiration. Yes, they want premium, but only when it provides value. There’s data around people willing to pay upto 12% Premium for Sustainable Products. But that’s not the whole story. One will pay this premium provided that the sustainable products solves their core everyday problem first and is easily accessible. Businesses forget the basics and try to lure GenZ with the “sustainability” aspiration. It won’t work unless your product actually works. —------------ They say – GenZ wants personalisation. They want “me” specific content Yes, they want personalisation, but a one-size-fits-all approach based solely on age falls short. This gen is deeply divided along geographical and socioeconomic lines. – Location Matters: "Personal" for a Gen Z consumer in Delhi differs vastly from someone in Pondicherry. Ignoring this geographic context leads to generic messaging that resonates with no one. – Socioeconomic Background: 1) The "posh, upmarket" Gen Z goes more YOLO and craves experiences. 2) The “ambitious, middle-class” GenZ wants to get serious shit done. Get access beyond their locality & birth certificate. —------------ Bottomline – The content strategy will vary. Content language will vary. Content approach will vary. PS - Now the audience is looking beyond aesthetics. Sure, a sleek Instagram feed is nice, but if your brand doesn't stand for something people care about, it's just noise. They also see through brands that are trying too hard to be relatable. Forced lingo is "out of touch." #branding #genz #startups

Gen Z's purchasing power was $143 billion in the U.S. alone in 2023. Here’s a blueprint for building a big Gen Z brand: Building a brand that not only resonates with Gen Z but also retains them is crucial for any business looking to thrive in the years to come. 1) Creating content: Gen Z loves engaging, shareable content that speaks to them. Create viral, fun content that captures their attention and encourages them to share it with their peers. Zomato's content is a prime example of this strategy in action. 2) Prioritise user-generated content: Gen Z craves a sense of community and belonging. Encourage user-generated content to foster an engaged community within your brand. Hollister Co.'s collective, where customers can share photos and stories, is a great example. 3) Embrace inclusivity and diversity: Gen Z values representation and wants to see themselves reflected in the brands they use. Fenty Beauty's inclusive range of foundation shades caters to a wide range of skin tones, resonating with this generation. 4) Be authentic and transparent: Gen Z seeks to uncover the human side of brands and ensure they align with their values. Patagonia's commitment to sustainability and transparency has attracted Gen Z customers who appreciate authenticity. 5) Storytelling over Selling: Gen Z cares more about the story behind the product than the product itself. They want to connect with the brand's ethos, purpose, and mission. Canva's brand strategy, which includes personality, voice, identity, and values, serves as an excellent framework. I believe that as the market continues to evolve, the brands that successfully communicate with Gen Z will be the ones that thrive in their respective industries. By following this blueprint, you'll be well-equipped to connect with Gen Z on a deeper emotional level, cultivate brand loyalty, and drive sales. What strategies have you seen work effectively in engaging Gen Z? #brandbuilding #GenZmarketing #agency