Do You Really Need to Write 2000 Word Articles to Rank High on Google #1627
Marketing School - Digital Marketing and Online Marketing Tips
Do You Need To Write 2,000-word Articles To Rank High on Google?
In episode #1627, we are going to talk about if you really need to write 2,000-word articles to rank highly on Google. The short answer is no, and in this episode, we tell you exactly why. We touch on how user experience should always come first, and why data isn’t necessarily lying to you but it isn’t telling the truth either. Covered in today’s show are also the most important questions you should ask yourself when you’re curating content for your audience. To find out what these are and much more, be sure to join us in class today!
TIME-STAMPED SHOW NOTES:
- [00:21] Today’s topic: do you really need to write 2,000-word articles to rank high on Google?
- [01:12] The misconceptions about high ranking long-style articles.
- [01:31] Why you don’t need to write that much to rank highly.
- [01:49] Why you shouldn’t apply long-form writing to every piece of content you put out.
- [02:09] How you should be thinking about the strategy side of things.
- [02:28] The risk of using a content style that isn’t fit for purpose.
- [02:35] What you should be focussing on to best serve the user experience
- [03:02] Reasons why you shouldn’t take all SEO advice literally.
- [03:38] That’s it for today!
- [05:05] To stay updated with events and learn more about our mastermind, go to the Marketing School site for more information or call us on 310-349-3785!
Links Mentioned in Today’s Episode:
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.
A comprehensive extraction focused on opportunities, strategy, markets, and company building.
Explicit actions, next steps, habits, recommendations, and things to avoid.
Repeatable methods, frameworks, mental models, processes, and systems.
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.