Best prompts for YouTube for titles using audience engagement analysis

You are a YouTube title specialist. Given the video topic: "{video_topic}", target audience: "{audience_description}" (age, interests, viewing habits), channel tone: "{tone}" and goal: "{goal}" (increase CTR, improve watch time, attract subscribers), generate 12 title variations grouped by intent: Click-first (high curiosity), SEO-first (keyword-rich), Value-first (clear benefit), Emotional-first (emotion-driven). For each title include: predicted CTR uplift (low/medium/high), ideal character count, and 1-line rationale tied to the audience data. Output as a simple bullet list grouped by intent.

You are given: current_title="{current_title}", video_topic="{video_topic}", analytics_summary: {ctr_percent}, {average_view_duration_seconds}, top_viewer_age_group, top_traffic_sources. Propose 6 optimized titles ranked by expected CTR improvement. For each title include: predicted CTR change (+/- %), recommended thumbnail concept (one short sentence), suggested tags (5), and why it fits the analytics pattern. If analytics are missing, explain which metrics you need.

Create 10 title options for a YouTube Short about "{short_topic}" limited to 35 characters each. Prioritize punch, emojis (if appropriate), and one-word power hooks. For each title list: best placement of emojis (start/end), expected CTR (low/med/high) for mobile viewers, and a 10-word thumbnail overlay suggestion. Provide 3 A/B pairs to test on Shorts.

You are given primary keywords with monthly search volumes: {keyword1: volume1, keyword2: volume2, ...}. Video topic: "{video_topic}", and primary audience intent (learn/buy/compare). Produce 8 SEO-optimized titles ranked by predicted search impressions. For each title provide: primary keyword used, estimated search intent match (high/med/low), ideal length for SEO, and a 1-line meta description under 120 characters.

Produce 6 title variants for "{video_topic}" targeting viewers "{audience}". For each variant list: expected CTR, rationale, and thumbnail recommendation. Then produce an A/B test plan: required sample size per variant (assume baseline CTR={baseline_ctr%}), minimum detectable uplift (e.g., 10%), significance level (95%), test duration recommendations, and how to interpret results.

For video_topic="{video_topic}", audience_profile="{audience_profile}", produce 5 title + thumbnail-text + image-concept combos. For each combo include: 1-line thumbnail description (subjects, props, facial expression), 5-word overlay text, title (max 60 chars), predicted CTR (low/med/high) and why the combo works for the audience.