AI reads live campaign data at fine grain and produces recommendations across three content dimensions. For messaging, natural language processing analyzes captions, comment sentiment, and engagement to surface the words, phrases, and hashtags that track with better results, and proposes alternative phrasing in the creator’s own voice when a message underperforms. For visuals, computer-vision models plus performance data correlate choices — product placement, color, lighting, faces, backgrounds — with engagement and rank formats against the goal. For CTAs, it evaluates wording and placement together because the two interact. Crucially, this is framed as collaborative input carrying a data-backed reason, not a directive — a rationale earns the adjustment while an order erodes the relationship.
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