Marketing School - Digital Marketing and Online Marketing Tips

Neil and Eric break down Hamilton Helmer’s 7 Powers framework for building a durable competitive business: branding, process power, switching costs, scale economies, cornered resources, network economies, and counter positioning. They apply these strategy concepts to agencies, then shift to AI moats and vertical integration, noting why Google stands out across the AI stack (apps, models, cloud, and chips like TPUs). The conversation closes with practical leadership lessons on AI fluency programs, hackathons, KPI-driven adoption, and avoiding “AI theater” so automation actually drives revenue and profit. Key takeaways: -7 Powers = clearer moat strategy -AI fluency must move KPIs -Vertical integration wins AI stacks Chapters (00:00) 7 Powers moat framework (00:26) Counterpositioning examples (00:36) Network effects and platforms (00:47) Cornered resources explained (01:04) Switching costs in agencies (01:22) Process power in manufacturing (03:12) AI leader and best moat (05:40) AI fluency hackathons (10:35) KPI-first AI adoption (12:30) Don’t give up, stay alive

Neil and Eric break down their biggest marketing predictions for 2026, covering SEO’s rebound, AEO reality checks, AI workflow automation, community building, in-person events, and why switching costs now matter more than product market fit. Recorded on Christmas Eve, this episode dives into how agencies, SaaS companies, and enterprise brands should adapt as AI accelerates feature parity and channels evolve. From go-to-market engineers to owned communities, this conversation is a practical roadmap for marketers planning the year ahead. Key takeaways: • SEO and AEO will coexist, not replace each other • In-person events and community will outperform algorithms • Switching costs beat features in modern SaaS Chapters: (00:00) Christmas Eve kickoff (00:30) SEO uncertainty and recovery (02:12) 2026 marketing predictions (03:26) Go-to-market engineers (05:40) AEO vs SEO reality (08:44) Community strategy mistakes (10:45) AI product market fit shifts (13:29) Switching costs over features (16:20) Final 2026 outlook

Neil and Eric break down why “storyteller” is suddenly the hottest corporate job title, from a Wall Street Journal trend to LinkedIn listings doubling in a year and Vanta paying up to $274,000 for a Head of Storytelling. They unpack why storytelling matters more in an AI-heavy marketing world, how to create tension using “but” beats, and why MrBeast-style narrative hooks keep viewers glued. Then they shift to YouTube strategy data: ideal video length by niche, tighter titles, and what thumbnails really do. singlegrain.com Key takeaways: -Storytelling is the AI-era differentiator. -Tension beats “and then” every time. -YouTube winners optimize length, titles, and thumbnails. Chapters: (00:00) Corporate storytellers surge (01:19) Emotional roller coaster writing (02:19) MrBeast storytelling formula (03:20) “But” creates tension (06:47) Enterprise sales de-risking (10:00) Viral YouTube data study (12:13) Best video length ranges (13:39) Titles, faces, thumbnail text (16:01) Closing thoughts

Neil and Eric break down smart bets from a work and investment perspective, why crypto still has upside potential, and why hiring great people only works at the right stage of business. They share real numbers behind outbound email, gift card incentives, and ROI, then unpack the biggest marketing wins and losses of 2025. The episode wraps with how podcasts actually make millions through ads, brand trust, and backend conversions, plus lessons from growing agencies, software, and global marketing strategies. Key Takeaways • Crypto and self-investment beat most external bets • Lead quality matters more than lead volume • Podcasts drive millions beyond ad revenue Chapters (00:00) Work and investment gambles (00:14) Crypto vs people investments (01:15) Hiring timing mistakes (03:14) Best investments in business (04:01) Biggest marketing wins 2025 (05:45) Outbound email ROI breakdown (10:38) Biggest marketing losses (14:44) How podcasts make millions

In this episode, Neil and Eric break down the rise of AI hype versus real usage, using Harvey AI, Microsoft Copilot, and ZoomInfo as case studies. They discuss $8B AI valuations, low user adoption, retention challenges, and why paying for AI does not equal value. The conversation covers venture capital incentives, SaaS economics, AI theater, and what actually drives ROI in sales, marketing, and engineering. The key question: are companies buying AI for results or optics, and when will real value show up? Key Takeaways: -AI revenue ≠ AI usage -Valuations are outpacing adoption -Monthly recurring value matters more than ARR Chapters: (00:00) Harvey AI valuation surge (01:06) AI usage vs paid licenses (02:20) VC incentives vs PE reality (04:06) Retention and adoption issues (06:22) Copilot enterprise usage data (07:58) AI impact on sales teams (10:01) ZoomInfo AI ROI breakdown (16:25) AI SEO vs traditional SEO