Lillian Pierson, P.E., fractional CMO and growth strategist, engineers marketing systems that drive predictable growth for tech startups. With a professional engineering license and 20 years of experience driving growth for Fortune 100 and early-stage companies alike, she bridges product and growth marketing to drive real boots-on-the-ground traction. She's trained 2M+ professionals in AI and data, grown organic channels to 750K+ followers, and authored 11 books including Data Science For Dummies. Lillian helps VC-backed and bootstrapped founders (pre-revenue to $6M ARR) scale through structured playbooks and data-driven systems.
A three-bucket GTM scorecard—Production, Distribution, Conversion—that pinpoints the single constraint, assigns owners, and fixes pipeline issues before forecasts slip.
Curious what is a GTM Engineer? Read this to learn how GTM Engineers design tracking, automation, and data pipelines to turn messy tool stacks into predictable, scalable revenue systems.
Explore how AI-driven dynamic segmentation enhances marketing strategies, boosts ROI, and addresses the limitations of static methods.
Series A fundraising can drags on for 60+ extra days when founders don’t have an AI due diligence checklist. This post breaks down what changed after recent settlements and what readers should audit now
Marketing mix modeling tells you which channels actually drove revenue — not just last-click credit. Here’s what it is, how it works, and when B2B teams should use it.
Why vendors are pushing you to cloud ERP faster than you’re ready, and the AI readiness gap they’re leaving behind
See exactly which AI tools for startups are reshaping business growth as we edge closer to 2025.
Learn how to test a new product idea using landing pages and a $100 ad budget for effective market insights.
Explore how real-time data revolutionizes market predictions, enabling businesses to respond swiftly and accurately to changing trends.
Optimizing for AI citations (GEO) is a different visibility game than SEO—structure, facts, and entities, not links, win.
Learn how to select the right cross-channel attribution tools for B2B marketing, enhancing ROI and understanding the buyer’s journey.
The hiring mistakes that kill AI startups are rarely about skills — they’re about timing, incentive structure, and founder blind spots. Here are the four to avoid.
Transform your marketing operations with an AI marketing strategy that drives unparalleled efficiency and effectiveness.
Learn effective strategies to generate your first 100 B2B SaaS leads without a marketing budget by leveraging your network and data-driven approaches.
2026 benchmarks and practical levers to improve Magic Number, Rule of 40, NRR and Burn Multiple across ARR stages.
Most SaaS founders track too many metrics and optimize the wrong ones. Here are the 13 revenue metrics that actually predict growth — and how to read them correctly.
Are you ready to start monetizing some SERIOUSLY profitable new revenue models in your startup? Read up on powerful revenue model options — comes complete with real-life examples and clear explanations on how these models elevate a startup from struggling to a scalable and profitable.
How Mrinal Wadhwa spent 6 years solving the authentication problem for distributed systems, then pivoted to build the platform making long-horizon AI agents possible
Enterprise Sales Strategy for Startups: How Planoverse Founder Howjer Gu Built Trust with Australia’s Biggest Retailers
Compare AI search visibility tools by use case—agency, in-house, and startups—covering pricing, features, and best-fit recommendations.
Marketing mix modelling isn’t just for enterprise budgets anymore. Here’s how to get started with MMM from scratch — tools, data requirements, and first model outputs.
