Sandrine Zambou

Hi from Paris 👋 I'm Sandrine, 31, SaaS founder building Klaym AI (AI search visibility). Looking to connect with people into: • AI search & SEO • SaaS • Growth & GTM • founders • Building in public If that's you, let's connect!

ChatGPT business profiles feel like the Google My Business moment for AI. Claim yours early and write it like it's your new homepage.

The faster a new user gets their first result, The sooner they come back. The more likely they pay. And the more they tell their friends. So cut every step between signup and that first result.

Your landing page gets 1,000 visitors a week. Only 10 sign up. What do you fix first? A) The headline B) The pricing C) Who you're attracting D) The signup steps

Nobody watches your launch as closely as you do. That's why one launch is rarely enough. Launch again with every real update: a new feature, a new demo, a new answer to a question buyers keep asking. Each launch gives people a new reason to look.

Hey @grok, if a SaaS founder publishes one honest comparison page every week for 12 weeks, what happens? Can it bring more signups from Google and AI answers? Which results are realistic, and which are hype?

More than ever, lean marketing wins. Before ads, try the free channels your buyers already use: Your X account Communities where they ask for help Replies under bigger posts A free checklist A short demo video Test each for a month. Scale the one that brings users back.

Hey X! Let's connect 👋 Looking to meet more builders: Founders SaaS builders Growth marketers Indie hackers I'm Sandrine, building @Klaym_AI from Paris. What are you working on? Drop your link below. Let's discover each other's products and drive some traffic.

Hey @grok, what is one thing that will completely change how people discover new brands before 2028, but most marketers aren't paying attention to yet? Give me your most unexpected prediction.

Where to find your first users before spending on ads: 1. Your existing network. Not every friend. People who actually have the problem you solve. Ask for an introduction to someone who does. 2. A small, researched prospect list. Pick one type of buyer. Mention their specific problem. Offer to walk them through one useful task, not your entire product. 3. Communities where those buyers already ask for help. Look for questions about the problem you solve. Give a useful answer before mentioning your product. 4. Repeat the channel that brings people back. Track where each user came from and whether they return. A signup spike is not a repeatable acquisition channel. Test ads after you understand who responds and why. Your first users need a relevant invitation, not a bigger audience.

You inherit a complex codebase with almost no documentation. Which AI coding tool do you trust to make the first changes? A. Claude Code B. OpenAI Codex C. Cursor D. GitHub Copilot What makes you trust it?

Founders, let’s get some eyes on your startup 👀 What are you building? Drop your link and tell us who it’s for. Let’s discover each other’s products and drive some traffic.

Two weeks of posting every day about marketing, growth and SEO. Thank you to everyone who replied. New here? I'm Sandrine, 31, SaaS founder in Paris. Which do you want more of: marketing, growth/GTM or SEO? If you’re building in the AI space, let’s connect.

"Own nothing and stay comfortable." "Know nothing and stay comfortable." Founders cannot afford either. Use AI to understand your market before your competitors do.

Hey @grok, be brutally honest: Should a SaaS founder still hire a traditional growth agency in 2026? Yes or No, and why? No "it depends" answer.

Your AI budget just got cut in half. You’re cancelling one subscription tonight. ChatGPT or Claude: which one goes?

Before buying ads, get customers this way: Ask happy users for introductions. Reopen chats with leads that went quiet. Partner with businesses that already serve your buyers. Offer past customers something new. Create a smaller offer for people who said the price was too high. Do this first. Ads amplify what already works.

Need content ideas? Start with: “This week I learned…” Write 10 answers. Turn each into a short post. Expand the ones that start useful conversations into guides or emails. Test the idea before writing the long version.

Knowing how to use AI isn't enough to become a marketing engineer. Here are 15 skills to go from using marketing tools to building systems that attract and convert customers. 1/ Find the buying trigger Ask buyers what changed before they started looking for a solution. A missed deadline tells you more than “I wanted to save time.” Build your message around that moment. 2/ Understand the real alternative Your competitor might be a spreadsheet, an agency or doing nothing. Explain why switching is worth the effort, not just why your features are different. 3/ Design an offer people can evaluate Make the outcome, price and next step clear. If setup feels risky, show the setup process. Match the proof to the objection. 4/ Learn the economics before buying traffic Estimate what a customer contributes after delivery costs and how quickly you need to recover acquisition spend. A cheap signup can still be an expensive customer. 5/ Track the steps that matter Map the journey from visit to signup, first useful result and payment. In Google Analytics 4, test that each event fires correctly. A broken event can make a good campaign look bad. 6/ Read attribution with context Compare analytics, customer records and “How did you hear about us?” answers. They capture different parts of the journey. Use the gaps to investigate, not declare one source the truth. 7/ Write a test before launching it State what you will change, why it should work and which result decides the next move. Set a review window and a spending limit before seeing the numbers. 8/ Test reasons to buy, not just designs One ad can focus on fewer errors, another on faster setup. Keep the audience and offer comparable. Changing the font won't tell you which problem matters most. 9/ Build the missing piece Use Claude Code to prototype a calculator, landing page or interactive demo. Review the output and test the full journey before sending traffic. Shipping is not the same as working. 10/ Evaluate AI on your actual work Give models the same brief and examples. Score accuracy, usefulness and editing effort. Choose the model that makes the finished work better, not the first draft longer. 11/ Automate with boundaries Start with reporting, tagging and alerts. For actions that change ad spend, set limits, logs and human approval. A workflow should make mistakes easier to catch, not faster to repeat. 12/ Make your expertise discoverable Answer specific buyer questions with useful comparisons and evidence. For Google's AI features, pages must be indexed and eligible for a search snippet. Eligibility is not a citation guarantee. 13/ Design distribution before production Choose where a piece will reach buyers before creating it. A partner newsletter may need a practical teardown; a community may need an answer to a recurring question. Adapt to the channel. 14/ Shorten the path to value Define the first result a new user actually wants. Watch where they get stuck and remove one obstacle. For an analytics tool, that might mean seeing a useful report, not completing a profile. 15/ Check who comes back Compare groups of users who signed up in the same week. Do they repeat the useful action? Investigate drop-off before scaling acquisition. More traffic won't repair a product people stop using. The goal isn't more marketing output. It's a system that learns why people buy, then helps more of the right people do it.

Hey @grok, what is a marketing or distribution product that failed 10 years ago but would work today because of AI?