Why Blogging Too Often Will Hurt Your Rankings | Ep. #776
Marketing School - Digital Marketing and Online Marketing Tips
In episode #776, Eric and Neil discuss why blogging too often may hurt your rankings. Tune in to hear why you should consider blogging less.
TIME-STAMPED SHOW NOTES:
- [00:27] Today’s Topic: Why Blogging Too Often Will Hurt Your Rankings
- [00:45] A site has “x” amount of authority.
- [01:05] You’ll find that if you start blogging more over time, a lot of your content will become outdated.
- [01:32] Old pages will drop in rankings, but eventually your whole site will suffer because of outdated posts.
- [02:20] Refer to the Content Reusage Framework.
- [02:22] A VC named Tomasz Tonguz did a study on the value of temporal content vs. evergreen content.
- [02:47] The difference between a news site and an evergreen site is that your rankings will spike from time to time, whereas evergreen content stacks in rankings over time.
- [03:25] Focus on writing better content, which will help your rankings.
- [03:45] The majority of your posts will not generate much traffic.
- [03:55] 20% of your content will make up 70% of your traffic.
- [04:13] Go to SEMRush or Ahrefs and look at what is popular on your competitors’ sites.
- [04:30] BuzzSumo will also show you what people love.
- [05:02] Follow the data.
- [05:19] That’s it for today!
- [05:35] Go to here to see how many downloads the show is getting. Also rate and review to help Eric and Neil meet their goal of 1 Million downloads per month. They will throw a live event once they reach their goal.
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.
Scientific findings, mechanisms, studies, hypotheses, and the limits of the evidence discussed.
A dedicated analysis of warnings, limitations, trade-offs, weak evidence, and uncertainty.
Memorable statements and important claims with attribution and source context.
Technologies, AI models, technical methods, capabilities, limitations, and adoption implications.
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.