Virly's content engine is based on machine learning from 8 million+ viral LinkedIn posts and deploys the following 6 main frameworks for highly communicative content:
1. Counterintuitive insights (3.2x average share rate obtained)
- Format: "Industry recognizes X → but data proves Y → our findings Z"
- 示例：”都说客户要低价，但我们调查显示68%B2B买家更看重实施支持”
2. Mini-case studies (upgrading 45% comment interaction)
- Format: "Client Background → Core Challenges → Solutions → Quantitative Results"
- Automatic generation of data visualization suggestions (e.g. "suggest adding conversion rate graphs")
3. Career turnaround stories (2.8x increase in personal number of followers)
- Format: "Failure experience → cognitive turnaround → methodological precipitation → universal value"
- Built-in emotion curve optimizer to control narrative pacing
4. Controversial questioning (brings 120% message request)
- Format: "Do you think [the current state of the industry] is an innovation or a bubble?"
- Automatic generation of multi-stance response templates to choose from
5. Resource clearing monoliths (access to 92% collection rate)
- Format: "The 5 most common questions I get asked about [X topic] → concise answers"
- Supports dynamic updating of the latest industry data
6. Behind-the-scenes footage (to enhance 70% brand affinity)
- Format: "Unexpected discoveries in product development → team solution process → user benefit points"
- Automatic matching of media types suitable for display (motion graphics/whiteboard sketches, etc.)
Each type is equipped with an optimization checker that evaluates topic heat, keyword density and sentiment positivity in real time.
This answer comes from the articleVirly: a tool to automate LinkedIn viral content generationThe
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