Using Market Intelligence

Most founders still follow the old playbook: 1. Have idea 2. Fall in love with idea 3. Build for months 4. Launch 5. Discover no one wants it 6. Repeat The AI validation approach flips this completely: 1. Have idea 2. Validate mercilessly 3. Kill it if data says no 4. Only build what people already want The hard truth? 90% of businesses fail because founders build products nobody wants. But that was before AI. I’ve wasted millions on bad business ideas. Now I can kill bad ideas in 72 hours, not 12 months. Here's my 5-step AI validation framework that saves you time, money, and heartbreak: 1. Problem Verification AI tools like Perplexity can search for people actively complaining about the problem you want to solve. Feed Reddit threads, forum posts, and review sites into ChatGPT. Let it extract patterns of pain. No real pain = dead idea. 2. Market Size Analysis If the pain is real, check if enough people have it. Let AI analyze Google Trends, search volume, and TAM (total addressable market) data. Create detailed spreadsheets of potential users. Too small = dead idea. 3. Competitor Assessment Feed AI your top 5 competitors' websites, pricing pages, and customer reviews. Ask it to identify gaps and oversaturation. Create a map of what's missing in the market. No clear advantage = dead idea. 4. Zero-Cost MVP Design Most founders build full products before validation. With AI, create "fake door" tests instead. Build a landing page that looks real. Create AI-generated mockups of your product. Run $50 of ads to see if people try to buy. No buyers = dead idea. 5. Early Adopter Interviews For ideas that survive steps 1-4, use AI to: - Draft perfect outreach messages to potential customers - Generate interview questions that reveal true buying intent - Analyze interview transcripts for patterns No enthusiasm = dead idea. This isn't just faster. It's an entirely different game. Come to my free AI masterclass and I'll show you my system for validating ideas and building profitable businesses in weeks, not years: https://buff.ly/THAXwgV

The Future of App Measurement: How MMM Drives Growth and Optimizes Budgets  As privacy regulations tighten, traditional methods of marketing measurement are becoming less effective, creating a need for more robust solutions. **Marketing Mix Modeling (MMM)** offers a comprehensive approach to understanding how marketing spend drives business outcomes, providing the insights necessary for growth and budget optimization. The Shift in Marketing Measurement Recent privacy regulations, such as Apple’s App Tracking Transparency (ATT) and GDPR, have limited data collection and hindered traditional attribution models. These models, which rely on user-level tracking, are no longer sufficient in today’s privacy-conscious landscape. As a result, businesses need to explore new methods for measuring marketing effectiveness, and **MMM** is quickly emerging as the solution. Marketing Mix Modeling is a statistical method that aggregates data from various sources, such as sales data, marketing activities, public competitor information, and macroeconomic factors like seasonality. By using MMM, app businesses can gain a comprehensive view of how their marketing spend and activities drive sales and optimize budgets for sustainable growth. Why MMM Is Essential for App Businesses MMM provides three key advantages for app businesses: 1. Sustainable, Privacy-Centric Measurement Unlike traditional attribution models that rely on individual-level data, MMM uses aggregated data like advertising impressions, spend, and industry trends. This approach is immune to privacy regulations, ensuring that businesses have reliable and future-proof data for measuring marketing performance. As privacy concerns grow, MMM offers a sustainable method for tracking and optimizing marketing efforts. 2. A Holistic View for Informed Decisions MMM evaluates all factors that influence revenue, including media spend, product updates, seasonality, and even competitor activity. This comprehensive approach provides a clear understanding of what drives user acquisition and engagement, enabling businesses to make well-informed, data-driven decisions about where to focus their marketing efforts. 3. Data-Driven Budget Optimization MMM doesn’t just provide performance data; it also offers recommendations for optimizing marketing budgets. By analyzing the effectiveness of various marketing activities, MMM helps businesses allocate resources more efficiently to maximize ROI. This enables companies to reduce wasted spend and ensure that every marketing dollar is contributing to growth. Real-World Examples: How MMM Drives Growth Aloha Factory, a Korean gaming developer, used MMM to adapt its marketing strategy to privacy changes and optimize its growth. By analyzing media impressions and contextual factors like weather and COVID-19, the company found that 37% of its app installs came from Google App campaigns—much higher than the 13% predicted by last-touch attribution. With this insight.

The market research industry is being torn down & rebuilt. No one is talking about it loudly. 92% of organizations are flying blind, with garbage data. Here's the no-BS explanation: Survey fatigue has reached critical mass: • Response rates dropping to 5-15% • 81% of consumers ready to unsubscribe • Declining quality as participants rush through The say-do paradox is more real than ever: • 83% of organizations face this problem • Customers post-rationalize their decisions • Social desirability bias = polished lies Traditional survey-based methodologies are increasingly failing to capture authentic customer insights, and it sucks because millions of dollars are wasted. The organizations succeeding in this environment are those that acknowledge the limitations of traditional methods and actively experiment with hybrid approaches. What's working: Ethnographic research (8.5 effectiveness) Behavioral analytics (8.1 effectiveness) Real-time feedback systems (7.2 effectiveness) Passive data collection (7.8 effectiveness) Heatseeker combines these into one platform. Our market experiments get to participants in their environment, passively collecting data based on what they do in real time. The future of market research lies not in abandoning surveys entirely, but in using them as one component of a broader, more sophisticated approach to understanding customer behavior. The conversation across Reddit, LinkedIn, and industry forums is clear: the time for relying solely on what customers say they want is over. The future belongs to understanding what they actually do. What's your experience with survey fatigue? Are you seeing response rates drop in your organization?

One of the most interesting perspectives I’ve come across on startup validation and it completely changed how I see it. Most founders validate the wrong way. They ask people, “Would you use this?” 100 polite yeses later… they think they’ve found product-market fit. But here’s the truth, saying Yes costs Nothing. People are kind. They don’t want to hurt your enthusiasm. Real validation isn’t about collecting yeses. It’s about finding why it won’t work and surviving the test. Ask sharper questions: What’s the hardest part about how you solve this problem today? → If they say “nothing,” the problem isn’t painful enough. Would you pay ₹X right now to fix it? → If they pause too long, it’s either not a real pain… or you’re talking to the wrong person. Whose decision would it be to buy this? → If it’s not them, you’re not even validating with your customer. Hesitation isn’t always bad but it’s a signal. Sometimes it means wrong pricing.  Sometimes wrong ICP. The real skill is to dig deeper and ask why three times before accepting an answer. And yes, validation isn’t about proving you’re right. It’s about finding the points of failure early. The faster you invalidate wrong ideas, the quicker you discover the right one. The founders who last don’t collect fake yeses. They collect enough nos to uncover the real yeses, the ones that sound like: 👉 “When can I start using this?” 👉 “Can you show me a demo?” 👉 “How much does it cost?” If you’re building, remember, don’t look for comfort. Look for clarity. Because polite interest won’t pay your bills, real pain will. #Startups #FounderMindset #ProductMarketFit #Entrepreneurship #startup #startupindia #Founder #CEO

Most startups don’t fail because founders lack effort. They fail because they start with unvalidated assumptions. Research consistently shows that lack of market need is one of the top reasons startups collapse. The real advantage at the idea stage is not speed of building. It is precision of validation. Bootstrapping Playbook for Idea-stage Founders - At the center of this framework is a simple but disciplined approach: 1) Find Your Edge: What's your domain expertise? Your unfair advantage? Pinpoint a pain point only you can solve. 2) Validate Mercilessly: No code. No outsourced MVP. If the idea doesn't validate? Discard. Start over. 3) Learn from Success: Study structured Case Studies, not anecdotes. Absorb lessons. 4) Refine Your Thesis: Iterate with real customer feedback loops. Is this idea strong enough for a decade of your life? 5) Immerse in Customers: Talk to at least 50 Ideal Customers. Understand their world. 6) Nail Positioning: Refine your precise positioning based on customer feedback. 7) De-risk Your Market: Master Market Sizing and Competitive Analysis. Avoid walking into a noisy market blind, hoping for funding. This is not about inspiration. It is about eliminating false positives early. The Core Principle: Validate Before You Build - Idea-stage founders often confuse motion with progress. But the real sequence follows a clear order. First, you define your edge by clarifying why you are the right person to pursue this idea. Next, you talk to real customers rather than relying on friends or assumptions. You then run structured validation before building anything, without writing code or creating an MVP. After that, you eliminate weak ideas quickly based on what you learn. Finally, you strengthen only the ideas that survive evidence. If your idea cannot survive structured scrutiny, it should not survive into development. Come talk to me at a free mentoring roundtable and ask questions of the 1Mby1M AI Mentor: https://lnkd.in/g3VwPX_S

Seven steps to validate your startup idea before you spend a dime 1. Talk to 30 potential customers. Skip market research firms; hit the street, Slack channels, WhatsApp groups, anywhere your audience hangs out. 2. Summarize their top three pain points in one sentence each. distill noise into clarity. 3. Sketch a landing page with your proposed solution. No code yet, just text and a “sign up” button. 4. Run a 5-day ad test on Facebook or LinkedIn with that page. spend $100 total, see if anyone clicks and signs up. 5. Call every single sign-up. ask, “What made you click?” then listen. 6. Refine your copy and offer based on feedback; relaunch another 5-day test. 7. If click-through stays above 2% and demo requests climb, congratulations, you’ve got early validation. If not, pivot or scrap. Validating cheaply saves months of wasted work and thousands in development costs. Do it first, build second.

99% of founders struggle to find product-market fit. Here's the #1 reason they crash their business off a cliff: ↓ Most skip the crucial step of market research. They don’t talk to their prospects. They don’t listen to the exact words of their audience. 7 ways you can avoid this fatal mistake (and stay in the game long enough to win): ↓ 1. Research is the foundation of success. Skipping market research is like building a house without a foundation. • Talk to your prospects. • Understand their pain points. • Use their language, not your interpretation. Your offer must resonate with their reality. ↓ 2. Direct engagement reveals the truth. While building Brain Apes, I spent countless hours interviewing prospects. Their insights shaped our services. • I didn’t assume—I asked • I listened to their frustrations • I used their words to craft our messaging This connection built our brand’s authenticity. — Example: Just 2 days ago, I asked for help on the new book I'm writing about moving from a job—to having the business, the freedom, and the life you want. And the support has been amazing and absolutely unreal. (My calendar is PACKED with calls.) And that's how we deliver magic! ↓ 3. Here’s the magic source: People tell you what they want. But you have to ask and listen. • Direct convos reveal unmet needs • Surveys can provide a broader perspective • Social media interactions can highlight trends Every word they share is a clue to success. And the exact words are like spells in messaging. ↓ 4. You can’t sell what hasn’t been validated. Validation saves you from costly mistakes. • Test your ideas with a small audience • Gather feedback and iterate • Adjust based on what you learn Your offer evolves with every interaction. ↓ 5. Extend your runway by selling validated products. In the early days, I solved problems firsthand. Then built leverage on those proven services. • This strategy funded our growth • It gave us time to refine and perfect our unique offers • Stability came from products people already wanted Those were the things I personally needed too. Sell what’s needed to fuel innovation. ↓ 6. Language is your strongest tool. Your audience’s words are the keys to their hearts. • Show them you understand their struggles • Use their exact phrases in your messaging • Reflect their emotions and experiences This builds trust and connection. ↓ 7. Market research is not a one-time task. It’s an ongoing process that evolves with your business. • Regularly engage with your audience • Stay updated on their changing needs • Adapt your offers to meet these new demands Continuous research keeps you aligned with your market. ↓ ♻️ Smash that repost button! ♻️ Follow me for more insights and tips! 🔔 Then hit the bell—never miss a post 🔔 ↓ Hot take: ChatGPT isn't market research. Agree/Disagree 💬 ↓ P.S. How do you perform market research? 💬 Tell me in the comments. ↓

𝐅𝐨𝐫 𝐲𝐞𝐚𝐫𝐬, 𝐦𝐚𝐫𝐤𝐞𝐭𝐢𝐧𝐠 𝐫𝐚𝐧 𝐨𝐧 𝐡𝐢𝐧𝐝𝐬𝐢𝐠𝐡𝐭. Dashboards told us what already happened—open rates, MQLs, churn numbers. By the time we saw the problem, it was too late. 𝐋𝐞𝐚𝐝𝐬? 𝐃𝐞𝐚𝐝. 𝐂𝐮𝐬𝐭𝐨𝐦𝐞𝐫𝐬? 𝐆𝐨𝐧𝐞. 𝐁𝐮𝐝𝐠𝐞𝐭? 𝐁𝐮𝐫𝐧𝐞𝐝. But AI and predictive analytics are flipping the game. 𝐌𝐚𝐫𝐤𝐞𝐭𝐢𝐧𝐠 𝐢𝐬𝐧’𝐭 𝐫𝐞𝐚𝐜𝐭𝐢𝐯𝐞 𝐚𝐧𝐲𝐦𝐨𝐫𝐞. 𝐈𝐭’𝐬 𝐩𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐯𝐞. 🔹 𝐋𝐞𝐚𝐝 𝐅𝐨𝐫𝐞𝐜𝐚𝐬𝐭𝐢𝐧𝐠 Traditional lead scoring is broken. A whitepaper download? That’s not intent—it’s noise. When we actually analyzed behavioral data using platforms like HubSpot, we found that multiple pricing page visits and engagement with onboarding content predicted conversions 3x better than generic lead scores. 𝐖𝐢𝐭𝐡 𝐦𝐮𝐥𝐭𝐢-𝐭𝐨𝐮𝐜𝐡 𝐚𝐭𝐭𝐫𝐢𝐛𝐮𝐭𝐢𝐨𝐧 𝐦𝐨𝐝𝐞𝐥𝐬 and 𝐛𝐞𝐡𝐚𝐯𝐢𝐨𝐫𝐚𝐥 𝐜𝐨𝐡𝐨𝐫𝐭 𝐚𝐧𝐚𝐥𝐲𝐬𝐢𝐬 ✔ Leads with 𝐫𝐞𝐩𝐞𝐚𝐭 𝐯𝐢𝐬𝐢𝐭𝐬 𝐭𝐨 𝐭𝐡𝐞 𝐩𝐫𝐢𝐜𝐢𝐧𝐠 𝐩𝐚𝐠𝐞 had a 𝟑𝐱 𝐡𝐢𝐠𝐡𝐞𝐫 𝐥𝐢𝐤𝐞𝐥𝐢𝐡𝐨𝐨𝐝 𝐨𝐟 𝐜𝐨𝐧𝐯𝐞𝐫𝐬𝐢𝐨𝐧 ✔ Prospects engaging with 𝐢𝐧𝐭𝐞𝐫𝐚𝐜𝐭𝐢𝐯𝐞 𝐝𝐞𝐦𝐨𝐬 moved through the funnel 𝟒𝟐% 𝐟𝐚𝐬𝐭𝐞𝐫 ✔ Combining 𝐢𝐧𝐭𝐞𝐧𝐭 𝐬𝐢𝐠𝐧𝐚𝐥𝐬 𝐰𝐢𝐭𝐡 𝐟𝐢𝐫𝐦𝐨𝐠𝐫𝐚𝐩𝐡𝐢𝐜𝐬 increased lead quality 𝐰𝐢𝐭𝐡𝐨𝐮𝐭 𝐢𝐧𝐟𝐥𝐚𝐭𝐢𝐧𝐠 𝐚𝐜𝐪𝐮𝐢𝐬𝐢𝐭𝐢𝐨𝐧 𝐜𝐨𝐬𝐭𝐬 We stopped chasing the wrong leads. And our pipeline? Tighter than ever. 🔹 𝐂𝐮𝐬𝐭𝐨𝐦𝐞𝐫 𝐑𝐞𝐭𝐞𝐧𝐭𝐢𝐨𝐧 A churn report tells you what you lost. But by then, it’s a post-mortem. Advanced platforms flag disengagement before it happens. A simple tweak—triggering check-ins for inactive accounts—cut churn by 15% in six months. A simple intervention—𝐭𝐫𝐢𝐠𝐠𝐞𝐫𝐢𝐧𝐠 𝐚𝐮𝐭𝐨𝐦𝐚𝐭𝐞𝐝 𝐫𝐞-𝐞𝐧𝐠𝐚𝐠𝐞𝐦𝐞𝐧𝐭 𝐰𝐨𝐫𝐤𝐟𝐥𝐨𝐰𝐬 when customers showed 𝟑+ 𝐝𝐢𝐬𝐞𝐧𝐠𝐚𝐠𝐞𝐦𝐞𝐧𝐭 ��𝐫𝐢𝐠𝐠𝐞𝐫𝐬—led to a 𝟏𝟓% 𝐫𝐞𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐢𝐧 𝐜𝐡𝐮𝐫𝐧 𝐢𝐧 𝐬𝐢𝐱 𝐦𝐨𝐧𝐭𝐡𝐬. 🔹 𝐏𝐫𝐨𝐝𝐮𝐜𝐭 𝐅𝐢𝐭 Guessing what users want is a waste of time. Predictive analytics showed us which features had a 𝟒𝟎% 𝐥𝐢𝐤𝐞𝐥𝐢𝐡𝐨𝐨𝐝 𝐨𝐟 𝐚𝐝𝐨𝐩𝐭𝐢𝐨𝐧 before launch. The result? No wasted dev cycles, no misfires—just 𝐝𝐚𝐭𝐚-𝐛𝐚𝐜𝐤𝐞𝐝 𝐝𝐞𝐜𝐢𝐬𝐢𝐨𝐧𝐬. If you’re still relying on past data to drive strategy, 𝐲𝐨𝐮’𝐫𝐞 𝐩𝐥𝐚𝐲𝐢𝐧𝐠 𝐲𝐞𝐬𝐭𝐞𝐫𝐝𝐚𝐲’𝐬 𝐠𝐚𝐦𝐞. 𝐌𝐚𝐫𝐤𝐞𝐭𝐢𝐧𝐠 𝐢𝐬𝐧’𝐭 𝐚𝐛𝐨𝐮𝐭 𝐥𝐨𝐨𝐤𝐢𝐧𝐠 𝐛𝐚𝐜𝐤. 𝐈𝐭’𝐬 𝐚𝐛𝐨𝐮𝐭 𝐤𝐧𝐨𝐰𝐢𝐧𝐠 𝐰𝐡𝐚𝐭’𝐬 𝐧𝐞𝐱𝐭. #PredictiveAnalytics #MarketingStrategy #DataDriven #Growth

$2.7 billion was wasted on failed startups last year. Most could have been saved by this one practice. Y Combinator analyzed 3,200+ startup post-mortems and found the #1 reason for failure wasn't running out of cash or competition, but it was building something nobody wanted. The graveyard of failed startups is filled with beautiful products nobody wanted. When I first landed in Canada, I had a law degree but zero knowledge of how to build a business here. I quickly learned that my assumptions about the market were mostly wrong. Steve Blank (who mentored the founders of Airbnb and Udacity) outlines validation as the "build, test, learn" cycle. Here's how successful companies implement it: 📌Problem validation first: Airbnb's founders couldn't pay their rent, so they put air mattresses in their living room and charged people to stay. This simple experiment validated that people would pay for alternative accommodations. 📌The mom test technique: Slack began as an internal tool at a gaming company. Instead of asking if the product is useful, they observed how their team actually communicated, revealing the gaps in existing solutions. 📌 Build a "Concierge MVP": Before building their platform, Instacart founder Apoorva Mehta manually fulfilled orders himself, buying groceries and delivering them personally to understand the process. 📌 Measure actual behavior: Buffer's founder Joel Gascoigne didn't build his product until he had paying customers. He put up a landing page explaining the concept and a "plans and pricing" page to see if people would actually click "subscribe." As an immigrant entrepreneur working with limited capital, I've learned this validation approach is actually crucial for survival. When my team pivoted our visa program after direct feedback from 50+ international founders, our client acquisition cost dropped by 60%. ✔️What business assumption are you treating as fact that should actually be tested? Video Courtesy: startuparchive instagram ♻️Repost and follow Dev Mitra 🇨🇦 for more insights on immigrant entrepreneurship, startup strategy, and cross-border business development.

Top marketing technology isn't just for giants. It's your unfair advantage too: Identity resolution has become the core of performance marketing in 2025. Why? Ads cost more. Privacy updates limit what you can track. And user journeys are more fragmented than ever. The giants like Amazon and Walmart have already cracked the code. But if you think these strategies are only reserved for billion-dollar brands... Think again. Here's how big brands build hyper-personalization,  And what you can steal for your next campaign: 1. Unified Customer View ↳ Target combines in-store and online data with centralized identity graphs. ✅ Build a single customer view even if your data is across platforms. 2. Cross-Device Recognition ↳ Amazon tracks users across devices to personalize offers. ✅ Connect journeys across mobile, desktop and tablet. 3. Real-Time Personalization ↳ Walmart adapts deals live according to user behavior. ✅ ID resolution enables adaptive content and discounting on the fly. 4. Lookalike Modeling for Acquisition ↳ P&G leverages ID resolution to power audience modelling + high-fit prospect targeting. ✅ Use AI to find your best-fit prospects. 5. Privacy-First Targeting ↳ Unilever uses consent-based ID resolution via LiveRamp. ✅ Choose tools with privacy built-in. 6. Rescuing Abandoned Carts ↳ Nike uses identity-based flows to re-engage high-intent site visitors, logged-in or not. ✅ Turn unknown visitors into email leads and potential conversions. 7. Omnichannel Orchestration ↳ Macy’s connects email, ads, and in-store with ID resolution. ✅ Create consistent experiences across email, SMS, and paid. 8. Predictive Lead Scoring ↳ Best Buy uses behavior-based insights to personalize outreach and optimize targeting. ✅ Use data-driven scoring to prioritize your hottest leads. These top brands KNOW their customers. Not just clicks, but the full identity behind them. Identity resolution turns traffic into trust... And trust into growth. Which of these tactics do you need to add to your stack? ♻️ Share this to help more DTC marketers level up their identity strategy. Follow me, Francesco Gatti, for more on identity resolution & ecommerce growth.