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Is Clickbait?

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90% of your, uh, of your value comes from your knowledge.

💨 tl;dr

MarketingAI is valuable but needs improvements. AI customization is lacking, and manually crafted content is superior. Ratings and channel recommendations need refinement. Better curation and collaboration with marketing experts are essential.

💡 Key Ideas

• The product is valuable and worth its price.
• It's an info product with AI customization, though AI parts need improvement.
• Manually crafted content is more valuable than GPT-generated content, which is often generic.
• LLM ratings are unreliable and need a better accuracy pipeline.
• The channel recommendation system is inconsistent and needs refinement.
• Current AI outputs are non-deterministic and lack real customization.
• Better curation of marketing channels, subreddits, and Facebook groups is needed.
• Users might exploit the system by generating multiple outputs.
• The product should provide comprehensive info at once to prevent repeated generations.
• Collaborating with marketing experts can enhance the use of LLMs.
• Customized action plans should be genuinely tailored, not just keyword-based.
• Email communication is strong, but other channels need better tailoring.
• Brainstorming should be improved with better examples and collaboration.
• Accurate channel selection and semantic search can add significant value.

🎓 Lessons Learnt

• Make AI Outputs Deterministic: Setting the temperature to zero ensures consistent outputs for the same input, avoiding user confusion.
• Customize AI Ratings: Avoid repetitive ratings to provide more tailored and accurate assessments.
• Implement a Better Rating Pipeline: Current ratings are generic and not valuable; develop a more accurate and meaningful rating system.
• Enhance Channel Selection: Refine the selection process to avoid over-reliance on channels like Organic YouTube and provide better recommendations.
• Avoid Generic LLM Content: Tailored content is more valuable than generic LLM-generated content.
• Fix Placeholder Errors: Ensure all placeholders are accurately replaced with specific, tailored content to avoid errors.
• Personalize Content Creation: Rely on your knowledge to create more impactful content rather than solely using LLMs.
• Review LLM Suggestions: Manually review LLM classifications and recommendations for relevance and accuracy.
• Provide Multiple Content Examples: Offer a broader range of examples so users can choose what fits best for their context.
• Improve Output Specificity: Provide detailed and specific information instead of generic lists.
• Remove Outdated or Hallucinated Data: Verify data through API requests to ensure accuracy.
• Enhance LLM Usage for Channel Selection: Use semantic searches to refine channel selection results.
• Provide All Channels to Users: Offer a comprehensive list of available channels to add value.
• Prevent User Frustration: Provide all necessary information at once or allow users to see more to avoid repeated generation attempts.
• Effective Use of LLMs: Use LLMs to genuinely augment a marketer’s knowledge, not just distill it.
• Tailor Action Plans: Develop fully customized action plans specific to the user’s needs.
• Enhance Marketing Channels: Customize other marketing channels beyond just emails with better content.
• Create Clear Action Plans: Develop simple, easy-to-follow action plans that outline exactly what clients need to do.
• Go Beyond Keyword Stuffing: Include creative ideas in action plans, not just keywords.
• Enhance Brainstorming with Examples: Provide examples to improve idea generation and brainstorming.
• Seek Collaboration for Mutual Learning: Engage in collaborations to gain valuable learning opportunities and improve marketing strategies.

🌚 Conclusion

MarketingAI has potential but requires more deterministic AI outputs, better rating systems, and refined channel selections. Focus on personalized, non-generic content and comprehensive info delivery. Collaborate with experts for enhanced results.

In-Depth

All Key Ideas

Product Review Highlights

• The product is highly valuable and worth the price.
• The product is an info product augmented with AI.
• Most of the content is manually crafted with the creator's knowledge.
• The AI component customizes the content to the user's case.
• The AI-generated parts can be improved.
• The product provides different outputs for the same input due to non-deterministic LLM settings.
• The channel ratings in the reports are consistently similar.

Issues with Current Rating and Recommendation Systems

• LLMs tend to give high ratings (10, 9, 8) that are not real or valuable
• Ratings need a better pipeline to be more accurate and realistic
• Current ratings lack consistency and determinism
• The organic YouTube channel recommendation appears too often and is not always appropriate
• The selection pipeline for channels needs improvement
• Generic LLM content lacks tailored value
• There's an error with placeholders in the organic search recommendations

Criticisms of GPT-generated Content

• GPT-generated content is generic and lacks real value
• Personalization using GPT is superficial and not genuinely valuable
• The LLM's classification for channels and content types lacks determinism and reliability
• Manually crafted content is more valuable than GPT-generated content
• Examples provided by knowledgeable people are highly valuable
• LLMs are poor at generating titles and copy, producing very generic outputs
• GPT-generated lists are not as useful as having more diverse examples
• Current AI-generated content often subtracts value compared to human-generated knowledge

Product Improvement Suggestions

• The current output of the product is not satisfactory and needs improvement.
• The product should provide a comprehensive info product detailing all channel options.
• There is an issue with hallucinated data and outdated information in posts on Reddit and Facebook groups.
• A good list of subreddits and Facebook groups for marketing is needed.
• The product could benefit from a database and semantic search to filter relevant channels.
• The value provided by accurate channel selection would be significant.
• The current examples generated by GPT are not useful and need enhancement.
• The method of using LLM to choose channels needs improvement.
• Users might exploit the system by repeatedly generating new outputs, leading to increased costs.

Product Improvement Suggestions

• Prevent users from generating again by providing all the value at once or offering an option to see the rest
• Current customization in the product is not providing real value
• LLMs can provide value but are not being effectively used in the current setup
• The report might benefit from separating LLM value as another tool
• Comparison with a competitor's product shows that while Desmond's info product is better, neither effectively uses LLMs for added value
• The need for collaboration between marketing experts and LLM experts to better integrate knowledge and provide more tailored value
• Creating customized action plans is crucial for user cases
• Challenges in perfectly using LLMs within non-winged social scripts due to various limitations

Feedback on Communication and Improvement

• Email is very good.
• Other channels can be improved on the tailoring part.
• LLM should decide on one good action plan.
• The action plan should be really customized and not just use keywords.
• Improve brainstorming of the ideas and augment with examples.
• Collaboration is welcomed for mutual learning and product improvement.
• Marketing is essential and can be challenging to learn.

All Lessons Learnt

AI Improvement Suggestions

• Make AI Outputs Deterministic: Setting the temperature to zero can ensure consistent outputs for the same input, avoiding confusion for users.
• Customize AI Ratings: Avoid repetitive ratings (e.g., 10, 9, 9, 8) across different reports to provide more tailored and accurate assessments.
• Leverage Manual Expertise: Combining manually crafted content with AI customization can enhance the value and reliability of the product.

Improvement Suggestions

• Implement a Better Rating Pipeline: Current ratings (10, 9, 8) are generic and not valuable. An improved pipeline is needed for more accurate and meaningful ratings.
• Realistic Rating Acceptance: It’s okay to give realistic ratings (e.g., 7 out of 10) based on specific characteristics rather than always high ratings.
• Enhance Channel Selection: Organic YouTube appears too often and is not suitable for all cases. The selection process needs refinement for better recommendations.
• Avoid Generic LLM Content: Tailored content is more valuable than generic LLM-generated content, which should be avoided.
• Fix Placeholder Errors: Ensure placeholders like 'Rice, your company' are accurately replaced with tailored content to avoid errors.

Content Creation Tips

• Customize content personally, not just using LLMs: Relying solely on GPT can produce generic outputs that don't add real value. Personalized content from your own knowledge is more impactful.
• Use LLMs for classification, but review their suggestions: LLMs can classify content types and channels, but their recommendations should be manually reviewed for relevance and accuracy to your specific needs.
• Provide multiple content examples for better decisions: Instead of limited LLM-generated suggestions, offer a broader range of examples so users can choose what fits best for their context.
• LLMs are weak at generating specific content elements: Titles and copy generated by LLMs are often generic and not very useful. Manual crafting of these elements is preferable.
• Focus on your knowledge over LLM content: The main value comes from your expertise, not the automated outputs of LLMs. Rely on your insights to create more valuable content.

Recommendations for Enhancing LLM Outputs

• Improve Output Specificity: Instead of generic lists, provide detailed and specific information, such as a comprehensive list of subreddits and Facebook groups relevant to marketing.
• Avoid Outdated or Hallucinated Data: Remove outdated or hallucinated content from outputs. Verify data through API requests if necessary.
• Enhance LLM Usage for Channel Selection: Better utilize LLMs for selecting channels by filtering through a large database and performing semantic searches to refine results.
• Provide All Channels to Users: Offer all available channels to users instead of a limited selection to add more value and avoid repeated generation attempts.
• Improve Generated Examples: Ensure examples provided by the LLM are useful and relevant by enhancing the input knowledge used in the GPT pipeline.

Key Points for Improving User Experience and Product Development

• Preventing User Frustration: Provide all necessary information at once or offer an option to see more to avoid user frustration from generating content repeatedly.
• Customization Needs Improvement: Customization should add real value, not just minor tweaks to an info product.
• Effective Use of LLMs: LLMs should be used in a way that genuinely augments the marketer's knowledge, not just distill it.
• Collaboration Between Experts: Combining expertise from marketing and LLMs can lead to better product development and value.
• Action Plans Must Be Tailored: Develop action plans that are fully customized to the user's specific use case for maximum effectiveness.

Marketing Strategy Enhancements

• Tailor other marketing channels more specifically: Emails are good, but other channels need better customization beyond generic content.
• Create a clear, simple action plan: Develop an easy-to-follow action plan for clients that outlines exactly what they need to do.
• Go beyond keyword stuffing: Customized action plans should include more than just keywords; they should offer deeper, more creative ideas.
• Enhance brainstorming with examples: Improve idea generation by providing examples, which can help in brainstorming better content.
• Seek collaboration for mutual learning: Engaging in collaboration can provide valuable learning opportunities and help improve marketing strategies.