Where to Learn Marketing in 2023
Marketing School - Digital Marketing and Online Marketing Tips
In episode #2385, we are telling you where you can learn about marketing in 2023! We share some informative newsletters you can read to make you a better marketer, give you some amazing resources that will help you experiment with your websites, talk about what YouTube channels will help you be most informed, and discuss why working at agencies teaches you so much. We even delve into how having your website torched can be both a painful and educational process before reminding you that shortcuts don’t work! To hear all about how you can learn marketing in 2023 and be reminded to learn from your mistakes, tune in now!
TIME-STAMPED SHOW NOTES:
- [00:20] Today’s topic: Where to Learn Marketing in 2023.
- [00:39] A reminder to read the Stacked Marketer Newsletter, Demand Curve Newsletter, and the Wall Street Journal.
- [01:04] Why you need to implement, practice, and experiment in order to learn marketing and what resources can help you.
- [02:56] Why you should focus on watching YouTube videos about marketing.
- [03:19] How working at an agency helps you learn a lot about marketing.
- [05:52] Why getting your website torched, while terrible, can teach you a lot about marketing.
- [06:39] A reminder shortcuts don’t work!
- [07:27] That’s it for today!
- [03:24] Go to https://www.marketingschool.io to learn more!
Links Mentioned in Today’s Episode:
- Subscribe to our premium podcast (with tons of goodies!): https://www.marketingschool.io/pro
- Stacked Marketer Newsletter
- Demand Curve Newsletter
- The Wall Street Journal
- Wordpress
- Bluehost
- Dreamhost
- WP Engine
- Chat GPT
- All-in-one SEO
- Yoast SEO
- Marketing School on YouTube
- Neil Patel YouTube
- Leveling up YouTube
- Matt Diggity on YouTube
- HRS on YouTube
Leave Some Feedback:
- What should we talk about next? Please let us know in the comments below.
- Did you enjoy this episode? If so, please leave a short review.
Connect with Us:
Learn more about your ad choices. Visit megaphone.fm/adchoices
See omnystudio.com/listener for privacy information.
Available Results
Generated results are saved to your library for reuse and search.
Choose Template
Pick the result you want. You can review provider and model before generating.
A concise first-pass summary for understanding the episode quickly.
A comprehensive, source-grounded extraction of the reusable knowledge in an episode.
Technologies, AI models, technical methods, capabilities, limitations, and adoption implications.
Repeatable methods, frameworks, mental models, processes, and systems.
A dedicated analysis of warnings, limitations, trade-offs, weak evidence, and uncertainty.
A dedicated inventory of concrete resources named in the episode.
A concise first-pass summary for understanding the episode quickly.
A detailed readable summary organized by chapter or topic.
A navigable map of subjects, topic flow, and suggested chapters.
A comprehensive, source-grounded extraction of the reusable knowledge in an episode.
Reusable atomic knowledge units extracted from the episode.
A comprehensive extraction focused on health practices, protocols, claims, and safety caveats.
A comprehensive extraction focused on opportunities, strategy, markets, and company building.
Explicit actions, next steps, habits, recommendations, and things to avoid.
A dedicated inventory of concrete resources named in the episode.
A dedicated analysis of warnings, limitations, trade-offs, weak evidence, and uncertainty.
A concise first-pass summary for understanding the episode quickly.
A detailed readable summary organized by chapter or topic.
A navigable map of subjects, topic flow, and suggested chapters.
A comprehensive, source-grounded extraction of the reusable knowledge in an episode.
Reusable atomic knowledge units extracted from the episode.
A comprehensive extraction focused on health practices, protocols, claims, and safety caveats.
A comprehensive extraction focused on opportunities, strategy, markets, and company building.
Scientific findings, mechanisms, studies, hypotheses, and the limits of the evidence discussed.
Technologies, AI models, technical methods, capabilities, limitations, and adoption implications.
Investment theses, assets, catalysts, valuation reasoning, time horizons, and risks.
Chronologies, actors, causes, consequences, turning points, and competing historical interpretations.
Policies, proposals, stakeholders, arguments, implementation constraints, and predicted effects.
Career paths, skills, hiring signals, workplace decisions, transitions, and limitations of the advice.
Behavioral mechanisms, biases, motivation, habits, emotions, interventions, and evidence limitations.
Economic mechanisms, incentives, indicators, market structure, forecasts, and uncertainty.
Leadership principles, team systems, organizational design, culture, feedback, and failure modes.
Audience, positioning, messaging, acquisition, retention, experiments, metrics, and failed approaches.
Teaching methods, learning strategies, practice, feedback, assessment, and effectiveness evidence.
Theses, premises, arguments, objections, values, thought experiments, and unresolved questions.
Communication patterns, conflict, boundaries, expectations, repair methods, and contextual limitations.
Books, papers, authors, courses, and other learning resources mentioned in the episode.
Repeatable methods, frameworks, mental models, processes, and systems.
Explicit actions, next steps, habits, recommendations, and things to avoid.
Memorable statements and important claims with attribution and source context.
A dedicated inventory of concrete resources named in the episode.
A dedicated analysis of warnings, limitations, trade-offs, weak evidence, and uncertainty.