... misallocates capital with total confidence. Here s where I ve landed so far. I d need three things before acting on an AI-generated financial lesson: The raw unit economics, visible. Customer acquisition cost, lifetime value, and churn cohorts. Not just top-line revenue summaries. The macroeconomic context at the time. A cost-cutting strategy that worked in a high-interest rate environment might stunt growth in a recovery. The lesson should date-stamp its validity. A CFO sign ... ... risk profile before it guides capital allocation. I m also wary of one trap: a revenue spike following a price hike doesn t mean customer loyalty caused it; it might just be a captive market running out of alternatives

... care about: coaching does not automatically count as mastery. After getting help, the learner must later demonstrate improvement independently. The core platform is built and entering open beta. Our live Kickstarter is funding and recruiting the founding learner cohort. I m keeping the main Product Hunt launch for when open beta is accessible. I m especially looking to reach college students. For founders who have built learning tools, how would you narrow that first cohort

... observation watching them use it is often more valuable than asking them what they think. people are bad at predicting their own behavior, but great at showing it. Curious did you notice any patterns in what users called okay vs. what experts flagged as broken? that gap is usually where the biggest product opportunities hide. Comment from Konstantin Tikhaev(@konstantin_tikhaev): @busmark_w_nika  Metrics must have clear failure conditions. Plus real validation only comes when you mesure specific ... ... hear more about that. We might be able to help. Comment from Sabber Ahamed(@sabber_ahamed): @busmark_w_nika   @abdullah_javaid3  the random-id-on-activation trick is the right call. weekly active hides exactly the churn-vs

... hundreds of campaigns, and more than 300 individual VC funds have replied to them. There is some overlap, since certain funds have responded to more than one founder. We also use the sales product heavily ourselves. Across recent email cohorts, our sequences have generated roughly an 11-14% reply rate. Not every response is positive, but it has become one of our most reliable ways to start conversations. Our growth so far has come from a mix of: Dogfooding ... ... Comment from Omri Ben-Shoham(@omri_ben_shoham1): The line about not fully trusting the Reddit ads reporting yet stood out. You already have a sales product that's good at telling whether a company/lead is a real fit versus

... build HIPAA compliant AI for healthcare, and last month I deleted a feature I had just finished. It was a journey analytics module in our internal dashboard: stage by stage funnel, cohorts, drop off between every step. The module worked as designed. I removed it anyway. The reason is that I could not name one decision it had changed. I opened it, read the stages, agreed with them, closed the tab. It described the past accurately and left me where ...

... grew Y because of Z, here is what we are doing next" is the headline. OKRs tie strategy to metrics Objectives are aspirational. Key results are measurable, time-bounded, and have an owner. The parts people get wrong: Leading vs lagging. Revenue is lagging. By the time it moves, the decisions that moved it are months old. Pick KRs you can actually move weekly. Qualified pipeline created. Activation rate. Trial-to-paid conversion. Not "annualized revenue." Track where people already ... ... unmanageable at 40. Conversely, building a warehouse with a dedicated data engineer at 30 people is usually premature optimization. Switch when : data lives across more than 3 systems and somebody is spending half their time stitching CSVs together, or cohort

... moment behavior changes. Unified dataset layer: Clean ingestion, dedupe/normalization, identity resolution, and consent tracking keep your data trustworthy. Smart recommendations: Lookalikes, bundle ideas, and AOV boosters plug straight into email, WhatsApp, and web push. Automation playbooks: Prebuilt, always-on cohorts with frequency caps, throttling, holdouts, and one-click QA previews. Data ops & integrations: Versioned segments, audit logs, RBAC, and native connectors to your CRM/store/analytics. Enterprise edition: Custom problem-solving for large orgs (private hosting, SLAs, bespoke models) and optional ...

... wait this is kinda working? Eventually, it turned into something that actually helps . So we figured hey, why not share it? What s inside the cheat sheet: 100+ use cases (DTC, SaaS, B2B, your uncle s side hustle) Cohorts, RFM, fancy-ish models When segmentation is magic and when it s totally useless Metrics to watch, traps to avoid A sprinkle of ethics and privacy (because we re good people) All wrapped up in a clickable, pretty Miro board Grab ...

... cost to handle 140000 customers? Comment from James Hawkins(@james_hawkins3): @lee_gaines  tough one to answer, but here's a point of view! we regularly have customers asking for help like this. i think the more enterprisey competitors we have would have it waaaay more though so i'd start with them. i'd probably dm their founders and be like "hey how do i convince you that i am awesome at implementing your products and you should ... ... though so would want to do that first really when we have maximum control. Comment from James Hawkins(@james_hawkins3): @will_daubney  trust is a really big deal. with what we do especially because there are gazilions of competitors