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🤖 GPT

Trending Topic Analyzer

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🔥Unveil the secrets of viral trends with the Trending Topic Analyzer! 🚀 Perfect for social media marketers, content creators, and trend enthusiasts. 🌟This prompt helps you dive deep into trending topics on various social media platforms. 📈Analyze key aspects like audience engagement, sentiment, and potential reach. ✅ Customizable for any topic. ✅ Ideal for strategizing content creation and marketing efforts. 💪Transform insights into action!
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5 months ago

Prompt Details

Model
Chat - (gpt-4-turbo)
Token size
60 ($0.00180 / call)
Example input
[topic name] - "Sustainable Fashion" [platform] - "Instagram" [date range] - "October 1-10, 2023"
Example output
After an extensive search and analysis of the available resources, here is the synthesized information regarding the "Sustainable Fashion" trend on Instagram for the period of October 1-10, 2023. Audience Engagement: The trend of sustainable fashion has been gaining traction, with a notable presence of sustainable fashion brands on social media. An analysis of 25 global fashion retailers, categorized as sustainable fashion brands, sustainably aware mainstream brands, and traditional fashion brands, was conducted based on their Instagram posts over a three-week period, which likely includes the specified timeframe. Engagement benchmarks and strategies for optimizing Instagram posts, including formats, caption lengths, and hashtags, were outlined in the Instagram Engagement Report 2023, which could provide insights into how sustainable fashion trends have been received and engaged with by the audience. Public Sentiment: While specific sentiment analytics for the given period are not readily available, general media discourse on sustainable fashion tends to emphasize the negative aspects, highlighting the problems within the industry. This could reflect a critical public sentiment that sustainable fashion attempts to address. Trending Hashtags: The Instagram Engagement Report 2023 likely provides insights into which hashtags have been most effective for engagement, but specific trending hashtags for sustainable fashion during the specified time period are not detailed in the publicly available information. Potential Reach: Reach is a crucial metric defined as the number of unique accounts that have seen a post. This is a direct measure of awareness and value gained from content. For sustainable fashion, this would indicate how widespread the trend is and its penetration into different audience segments. Strategic Recommendations: Content Creation: Focus on creating content that not only showcases sustainable products but also educates the audience on sustainability practices. Utilize storytelling to highlight the positive impact of sustainable fashion. Engagement Optimization: Use the insights from the Instagram Engagement Report 2023 to tailor your content for maximum reach and engagement. Pay attention to the best times to post and the most effective hashtags. Leverage Analytics: Regularly track Instagram metrics such as reach and engagement rates to understand how your content performs and where there is room for improvement. Address Negative Sentiments: Since the discourse around sustainable fashion can be negative, use your platform to offer solutions and positive messages that counterbalance prevalent issues. Diversify Content: Analyze successful sustainable fashion brands and mainstream brands that are sustainably aware to see how they engage with their audience. Diversify your content to include various themes and formats that resonate with different segments of your audience. Unfortunately, while I endeavored to locate specific data points and analytics from the exact dates requested, such information is not readily available in open sources and would typically require access to proprietary social media analytics tools or reports that are not publicly accessible. For detailed statistics and analytics, content creators and marketers might need to use specialized social media analytics services or tools that can provide real-time and historical data for the specified period.
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