The Vanity Metrics Trap
đ When Engagement Becomes a False Signal, Perplexity AI Integrates DeepSeek AI Model, and more!
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đ The Vanity Metrics Trap: When Engagement Becomes a False Signal
đ§ Perplexity AI Integrates DeepSeek AI Model
đ Tweet of the Day
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đ The Vanity Metrics Trap: When Engagement Becomes a False Signal
A TikTok goes viral, an Instagram post racks up thousands of likes, and the comment section is buzzing. It looks like a huge winâuntil you check sales. Crickets. The brutal reality? Engagement without buying intent is just noise.
While social media rewards visibility, visibility without conversions burns marketing dollars and creates a false sense of success. To scale profitably, DTC brands need strategic engagementânot just more of it.
đ„ Use âPurchase-Primingâ Engagement Instead of Broad Reach
Most brands celebrate high engagement, but what matters is who is engaging. Instead of chasing general reach, trigger high-intent micro-actions. Example: Instead of asking users to âlike if they agree,â prompt âDM us âYESâ to unlock a secret offer.â This instantly filters passive scrollers from potential buyers, creating a self-segmenting audience for retargeting.
đ Train the Algorithm to Prioritize Buyers, Not Lurkers
Your social engagement is training the platformâs AI on what audience to show your content to. If your viral posts attract non-buyers, the algorithm starts favoring the wrong people. Fix this by running engagement ads targeting past buyers and high-LTV customers. Every piece of viral content should be seeded to an audience that actually converts.
đŹ Force Engagement to Work for You With Reverse CTA Strategies
Instead of passively waiting for engagement to turn into sales, make engagement an entry point for purchase intent. Example: Instead of linking to a website, brands like OLIPOP use comment-triggered DMs to move users directly into Messenger flows.
âComment âGUTHEALTHâ below, and weâll DM you an exclusive code.â This moves engagement from the public feed to a one-on-one conversion opportunity.
đŻ Engineer Intent-Driven UGC That Funnels to Sales
Most UGC boosts engagement but doesnât guide users to buy. The fix? Pre-sell the product inside the content.
Instead of general lifestyle shots, create UGC that mimics the âconsideration stageââunboxings that answer doubts, influencer content that directly calls out why they chose your brand over others, or a âTry It vs. Skip Itâ format that builds trust. The best UGC isnât just engagingâitâs a direct response ad in disguise.
Conclusion
Engagement shouldnât be the goalâit should be a mechanism to filter, qualify, and convert. The smartest brands donât just get attention; they engineer it to drive action. Because at the end of the day, likes donât pay the billsâbut strategic engagement does.
đ§ Perplexity AI Integrates DeepSeek AI Model
Insights from SEJ
Perplexity AI has introduced the Chinese DeepSeek R1 reasoning model for its Pro users, offering a new self-hosted AI option. While this expands its AI capabilities, the move has sparked controversy over censorship and data privacy concerns.
The Breakdown:
DeepSeek R1 Joins Perplexity Pro: Users can now choose DeepSeek R1 alongside models like OpenAI o1 and Claude 3.5, with hosting restricted to U.S. and European data centers.
Censorship Concerns Addressed â While the original DeepSeek R1 model includes censorship typical of Chinese AI, Perplexity CEO Aravind Srinivas confirmed that their hosted version is uncensored, as demonstrated in public tests.
Misconceptions About Data Security â Some users speculated that Perplexityâs integration could allow Chinese government oversight, but as an open-source, self-hosted model, all data processing remains within Perplexityâs infrastructure.
Perplexityâs adoption of DeepSeek R1 fuels debates over AI governance, censorship, and open-source AIâs future. While it broadens access to competitive AI models, it also highlights concerns about political influence in training data.
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