Marketing

Decathlon chose to zoom in (literally) and take a different perspective. Their “Choose Your Way” campaign doesn’t push product features or promotions. Instead, it invites you in through close-up, tactile moments that make you feel something. These are memory triggers. Emotional cues. It’s simple, sensory and surprisingly powerful. A reminder that the most effective creative work doesn’t just show what something is. It makes you feel something about it. This shift didn’t come out of nowhere. Last year, Decathlon rebranded and it marked the beginning of a new chapter for a brand that had always been big, but rarely emotional. This campaign builds on that foundation. It shows what happens when you stop trying to say everything and focus instead on creating a feeling. You don't have to lead with product to make people care. You just need to show up in a way that resonates. Other brands are doing this too. British Airways rolled out its “A British Original” campaign with eye-catching out-of-home executions that use minimal branding and focus on expressions of wonder from people gazing out of plane windows. PepsiCo also nailed it with work that zoomed in on their logo hidden in plain sight on other brand packaging. A smart, subtle flex. It's all about shifting the perspective and zooming in to bring something visually interesting to life. What brand have you seen recently that made you feel something without saying too much?

A very easy way to improve your Amazon ads efficiency by at least 10% Let’s say you’re spending ₹4–5 lakhs/month on Amazon ads. Your ACoS looks okay. Conversion rate seems fine. But your gut tells you—you’re still wasting some money on irrelevant traffic You’re not wrong At Atomberg, we had found that some of our Amazon spend was going toward search terms that had no business seeing our ads: - “cheap fan” -“rechargeable fan” - “usb fan under 1000” None of these users were in-market for a ₹3,000+ BLDC ceiling fan. But we were still showing up. And paying for those clicks. And it’s not just us. I’ve seen 6–7 brands' Amazon ad accounts across categories over the last few years—same problem, every single time The fix? N-gram analysis Takes less than an hour. You don’t need to be a performance marketing expert. But the results compound What’s N-gram analysis? It’s breaking down every search term into its word components—1-grams, 2-grams, 3-grams—and then identifying patterns that consistently drive waste… or conversion. Example: “cheap rechargeable fan for hostel room” turns into: 1-grams: cheap, rechargeable, fan, hostel, room 2-grams: rechargeable fan, hostel room 3-grams: fan for hostel, etc. When you do this across all your search terms, you start seeing the real picture. Why this matters more than just checking your search term report: Search terms ≠ keywords a) One keyword can trigger 100s of different queries. Some convert. Most don’t. You need to find the patterns. b) Waste is diluted across low-volume terms. Maybe “rechargeable fan for hostel” spent ₹300. You ignore it. But what if 12 other queries with “rechargeable” spent ₹6,000 in total with zero conversions? c) Long-tail is infinite. N-grams are finite. You can’t negate every bad search. But you can block the core terms—“cheap”, “usb”, “mini”—once and be done with it. d) It helps you scale campaigns too. You can find goldmine phrases like “white ceiling fan”, “silent BLDC fan”, “fan for living room”—with 5x+ ROAS. Those became exact match campaigns What you should do: a) Pull last 3 months of search term data b) Break them into unigrams, bigrams, trigrams c) Create a pivot with spend, orders, ROAS by N-gram d) Negate high-spend, low-conversion N-grams (e.g., “cheap”, “rechargeable”) e) Boost high-ROAS ones (e.g., “bldc”, “ceiling fan white”) f) Add exact match campaigns g) Rinse and repeat monthly Try it. Guaranteed to improve efficiency at whatever scale you are operating If you want to read an expanded version of the post, link is in the first comment

Introducing the web's first market map of the Product Analytics Market: I was floored when I couldn't find one of these online. Surely, Gartner or CBInsights or A16Z would have created one? It turns out not. So I spent the past 3 months: • Talking with 25 buyers • Researching the space myself • Interviewing 5 product leaders at key players This is what I learned about the most significant players in each space: (that PMs and product people need to know) 1. Core Product Analytics Platforms     The foundational tools for tracking user behavior and product performance Amplitude : The leader, an all-in-one platform for PMs to master their data Mixpanel : The leader in easy UX and pioneer in event-based analytics Heap | by Contentsquare: The automatic event tracking and real-time insights leader 2. A/B Testing & Experimentation     Platforms for analysis Optimizely : The premier tool for sophisticated A/B and multivariate testing VWO : The best for combining A/B testing with heatmaps and session recordings AB Tasty: The all-in-one solution for testing, personalization, and AI-driven insights 3. Feedback & Session Recording     Capture qualitative insights and visualize user interactions Medallia: The top choice for comprehensive experience management Hotjar | by Contentsquare: The go-to for visual feedback and user behavior insights Fullstory: The best for detailed session replay and user interaction analysis 4. Open-Source Solutions     Customizable, free analytics platforms for data sovereignty Matomo: The robust, privacy-focused open-source analytics platform Plausible Analytics: The lightweight, privacy-first analytics solution PostHog: The versatile, open source product analytics tool 5. Mobile & App Analytics     Specialized tools for mobile and app performance analysis UXCam: The best for in-depth mobile user interaction insights Localytics: The leader in user engagement and lifecycle management Flurry Analytics: The comprehensive, free mobile analytics platform 6. Data Collection & Integration     Gather and unify data across platforms Segment: The top choice for effortless customer data unification Informatica: The enterprise-grade solution for data integration and governance Talend: The flexible, open-source data integration tool 7. General BI & Data Viz     Non-product specific tools for data analysis and visualization Tableau: The leader in interactive, rich data visualization Power BI: The best for deep integration with Microsoft tools Looker: The modern BI tool for customizable, real-time insights 8. Decision Automation & AI     Systems for automated insights and decisions Databricks: The unified platform for data and AI collaboration DataRobot: The leader in automated machine learning and AI Alteryx: The comprehensive solution for analytics automation Check out the full infographic to see where your favorite tools fit and discover new platforms to enhance your product analytics stack.

Last week, I shared how Gen AI is moving us from the age of information to the age of intelligence. Technology is changing rapidly and the way customers shop and buy is changing, too. We need to understand how the customer journey is evolving in order to drive customer connection today. That is our bread and butter at HubSpot - we’re deeply curious about customer behavior! So I want to share one important shift we’re seeing and what go-to-market teams can do to adapt. Traditionally, when a customer wants to learn more about your product or service, what have they done? They go to your website and explore. They click on different pages, filter for information that’s relevant to them, and sort through pages to find what they need. But today, even if your website is user-friendly and beautiful, all that clicking is becoming too much work. We now live in the era of ChatGPT, where customers can find exactly what they need without ever having to leave a simple chat box. Plus, they can use natural language to easily have a conversation. It's no surprise that 55% of businesses predict that by 2024, most people will turn to chatbots over search engines for answers (HubSpot Research). That’s why now, when customers land on your website, they don’t want to click, filter, and sort. They want to have an easy, 1:1, helpful conversation. That means as customers consider new products they are moving from clicks to conversations. So, what should you do? It's time to embrace bots. To get started, experiment with a marketing bot for your website. Train your bot on all of your website content and whitepapers so it can quickly answer questions about products, pricing, and case studies—specific to your customer's needs. At HubSpot, we introduced a Gen AI-powered chatbot to our website earlier this year and the results have been promising: 78% of chatters' questions have been fully answered by our bot, and these customers have higher satisfaction scores. Once you have your marketing bot in place, consider adding a support bot. The goal is to answer repetitive questions and connect customers with knowledge base content automatically. A bot will not only free up your support reps to focus on more complex problems, but it will delight your customers to get fast, personalized help. In the age of AI, customers don’t want to convert on your website, they want to converse with you. How has your GTM team experimented with chatbots? What are you learning? #ConversationalAI #HubSpot #HubSpotAI

🍱 How To Organize Your Design System At Scale (https://lnkd.in/e9343uqv), a fantastic case study on how to set up a design system with 900 shared components and 25 designers — with product-specific domain components and shared ownership between the design system guild and product designers. Written by Jérôme Benoit ↓ Key takeaways: ✅ 1 design system, 8 design libraries, 1 library serves 1 goal. ✅ Each library has owners, editors (edit/publish), users (view-only). ✅ All designers have access to all resources from all files. ✅ Product team has domains, each domain has feature teams. ✅ Foundations + Core components are owned by design system team. ✅ Domain components are product-specific, owned by product designers. ✅ Each feature team has its own frame (not a page!) on a Domain page. ✅ Domain components are structured [Instance name] 💠 [Core name]. ✅ The work by product teams can move up to the Core level, too. In many products, different feature teams often have very different needs, and that’s why secondary design systems emerge. With this set-up, all teams are still working within 1 single design system, pulling and pushing components between levels and having search across all design work in all domains at once — without an organizational overhead! 👏🏼👏🏽👏🏾 Useful resources: How To Organize 1250+ Design Screens in Figma (+ File examples), by Lorenzo Palacios Venin https://lnkd.in/e7X4fKcj Booking.com: Multi-Platform Design System (+ Figma), by Nicole Saidy https://lnkd.in/edueYQPG Frog: Building A Global Design System, by Anthony Nguyen https://lnkd.in/etkiTxfB Doctolib Figma Files Organization Tips, by Jérôme Benoit https://lnkd.in/eK7bhQeS Multi-Brand Design System, by Pavel Kiselev https://lnkd.in/eShgnPnW Design System Structure for Teams, Projects and Files, by Luis Ouriach https://lnkd.in/eFZUjUCU How to Organize Your Figma Files For Design System, by Jules Mahé https://lnkd.in/eeHG2VzU Organizing Design System For Scalability, by Allie Paschal https://lnkd.in/eeAtakGs Design That Scales (Book), by Dan Mall https://lnkd.in/eeFrqFfP And kudos to the wonderful design team at Doctolib and all the wonderful designers above for sharing their insights for everyone to learn from!👏🏼👏🏽👏🏾 #ux #design #designsystems

Everything we know about online brand discovery is about to break. People aren’t browsing pages anymore. They’re asking AI. And that means the entire digital value chain is being rebuilt. Users are no longer starting with a Google search, clicking on links, and browsing websites. Increasingly, they’re turning to AI tools like ChatGPT, Perplexity, and Gemini to get direct answers, summaries, and recommendations. No links. No websites. No page one rankings. That shift is forcing a rethink of how visibility works online - and where SEO (Search Engine Optimization) fits. Traditionally, SEO has been about helping businesses appear higher in Google results. That meant optimizing websites to match search terms, earn backlinks, load quickly, and convert well once the user arrived. But that model depends on one thing: people clicking on search results. AI tools don’t work that way. When users ask ChatGPT for help - “compare project management tools,” “what’s the best CRM for startups,” “find me a cheaper alternative to X” - they’re not browsing. They’re expecting a direct, summarized answer in the chat itself. That’s where the biggest shift is happening. Data from Profound shows how user intent is evolving in AI environments: 1. Generative intent now leads at 37.5%. These are prompts where users ask AI to create or do something directly: write an email, summarize a document, recommend a product. 2. Informational intent - traditionally the most common in Google - is down to 32%. These are questions looking for facts or explanations. 3. Navigational intent - looking for a specific website - has collapsed from 32% in traditional search to 2% in AI. In chat, people don’t say “take me to X.com.” 4. Transactional intent has jumped 9x (to over 6%). That includes prompts like “buy running shoes,” “find deals on laptops,” or “compare prices.” 12% of prompts are conversational: things like “thanks,” “make it shorter,” or “can you add a joke?” - which play a subtle but growing role in shaping how AI interprets tone, preferences, and even brands. Why does this matter? Because all of this happens before a user visits a website - if they visit at all. In this new model, there’s no clear click path. No landing page. No bounce rate. That makes most current marketing KPIs and tools largely obsolete. A new wave of startups is helping brands adapt - decoding how AI models reference products and content. The focus has shifted from rankings to being included in AI-generated responses. The move from SEO to “AI visibility” is early, but accelerating. The question now isn’t: “How do I get more search traffic?” but “What do AI systems say about the brand - and is it even part of the answer?” Because soon, it won’t just be users asking. It will be AI agents deciding - on their / our behalf. Are you ready? Opinions: my own, Graphic source: Profound 𝐒𝐮𝐛𝐬𝐜𝐫𝐢𝐛𝐞 𝐭𝐨 𝐦𝐲 𝐧𝐞𝐰𝐬𝐥𝐞𝐭𝐭𝐞𝐫: https://lnkd.in/dkqhnxdg

If your content isn't converting... Look at your Product Marketing <> Content Marketing collaboration. Great content rarely fails because of writing quality. It fails because of gaps between PMM and Content teams. Here's the collaboration checklist I created with Content Marketing pro, Pierre Herubel. → Research  PMM: Deliver buyer research & customer voice Content: Build journey-based content plan → Messaging Development PMM: Own core value prop & positioning Content: Adapt for channels & formats → Competitive Intel PMM: Identify market gaps & differentiators Content: Develop unique narrative & comparisons → Product Launches PMM: Drive objectives & positioning Content: Align calendar & track performance → Feature Updates PMM: Flag changes & validate technical details Content: Audit & optimize existing content → Product Insights PMM: Share usage data & success metrics Content: Develop customer stories Product Marketing 🤝 Content Marketing Two different functions. One critical partnership. Save this checklist to nail the collaboration that delivers powerful GTM results.

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.

Most people think that you need a huge audience to monetize your knowledge. They couldn't be more wrong. The truth is, with the right strategy, a small (but engaged) audience can support a business. This platform is oversaturated with broad content, so a dedicated niche audience is your secret weapon. Here’s how you can capitalize on your unique expertise, even with a small following: 1. Identify Your Core Expertise: Zero in on what you know best & what your audience values most. This is the specialized content you should be sharing daily. 2. Create High-Value, Low-Volume Products: Think ebooks, niche-specific courses, or personalized 1:1 consulting. These offerings don't require broad appeal but can generate incredible income from a smaller audience. 3. Leverage Direct Engagement: Use your closeness with your audience to your advantage. Use personalized interactions or small group sessions to be more valuable and attractive than broad, impersonal offers. 4. Host Specialized Events or Workshops: It doesn't matter if they are in-person or virtual. The key is to offer a deep dive into topics your audience cares about, which they can't find elsewhere. Monetizing a small audience isn't just possible, it's often more sustainable and fulfilling. I've been doing it since 19,000 followers. The key was always to focus on depth, not breadth. What unique strategies have you seen or used in monetizing a niche audience? ~~~ If you found this helpful, consider resharing ♻️ and follow me Justin Welsh for more content like this.

There are always situations in which you need to communicate fast and clearly. Especially in a crisis, in new situations, or when there is time pressure. The STICC protocol helps you achieve this. The STICC Protocol was developed by psychologist Gary Klein as a tool for managing the unexpected. STICC stands for: Situation, Task, Intent, Concerns, Calibrate and is a technique for productive communication about what to do when you face a new, unexpected situation. This is what it means: S - Situation = Here’s what I think we face. The leader summarizes how they see the situation, problem, or crisis at hand. T - Task = Here’s what I think we should do. The leader explains their plan for addressing the situation, problem, or crisis at hand. I - Intent = Here’s why I think this is what we should do. The leader explains the reasons why they think this is the best way of addressing the situation, problem, or crisis at hand. C - Concerns = Here’s what we should keep our eyes on. The leader mentions possible downsides or future consequences of the solution suggested to be taken into account as well. C - Calibrate = Now talk to me and give me your views. The leader asks others in the team to give their feedback and viewpoints, and especially invites them to disagree and add. This technique helps you in managing pressured situations in three ways: First, once something unexpected happens, it helps to develop appropriate responses. The five steps are aimed at discussing with a team what to do in cases that are not familiar. Through its focus on concrete action, on gathering different viewpoints, and on speed, the STICC protocol is a quick way to take appropriate action in new situations. Second, in step 4 (Concerns), you open up the discussion for further uncertainties and other changes that may follow. In this way, you mentally prepare people that there will always remain uncertainties. This helps in developing a crisis-ready mindset that is not only helpful in the current crisis, but also in the next. Third, the fact that a constructive dialogue takes place also facilitates communication and mutual learning. Even though the leader brings the suggestions here, it is the team together that comes to a solution. And while doing that, they learn together and from each other in an open and adaptive way, which helps further prepare them for future crises. My advice: use STICC whenever you have to communicate fast and clearly. === Follow me or subscribe to my Soulful Strategy newsletter for more: https://lnkd.in/e_ytzAgU #communicationtips #agile #teamexercise