Why We Don't Blog Daily (and You Shouldn't Either) | Ep. #698
Marketing School - Digital Marketing and Online Marketing Tips
In episode #698, Eric and Neil discuss why daily blogging is unnecessary. Tune in to hear what pace at which you should be producing content.
TIME-STAMPED SHOW NOTES:
- [00:27] Today’s Topic: Why We Don't Blog Daily (and You Shouldn't Either)
- [00:36] Neil used to blog seven times per day as an experiment.
- [00:55] It got him a ton of traffic, but he burnt out working at that pace.
- [01:15] HubSpot gets a ton of traffic and posts multiple articles on a daily basis, but they are able to keep that pace.
- [01:40] If you want to scale up and generate more traffic, blog every single day.
- [01:52] If you’re in the B2B world, don’t blog every day. It’s unnecessary.
- [02:13] The Kleiner-Perkins Internet Trends report comes out every year.
- [02:35] It is a popular guide that serves a huge community.
- [02:50] If you want high-quality leads, don’t blog every day. Write content that shows off how smart you are and what you have to offer.
- [03:15] Techcrunch is no longer the end-all, be-all that it used to be.
- [04:05] When you are starting out, doing one really good piece per week or month will do the trick.
- [04:25] Eric and Neil record three times every two months and record in batches of 20. This gives them a lot of shows in advance.
- [04:55] This helps them stay top-of-mind and provide high-quality content.
- [05:15] If you can’t provide value, don’t blog or podcast.
- [05:45] Everything has been done to death, which is why blogging is a hard game.
- [05:59] That’s all for today!
- [06:02] Go to Singlegrain.com/Giveway for a special marketing tool giveaway!
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.